If you lead a technology or product team, chances are you’ve already adopted AI tools in your daily operations – to speed up tasks, generate insights, or automate parts of the workflow. But the true transformation brought by Artificial Intelligence is not superficial. It goes far beyond the tools. It lies at the very core of how we build software. 

And that changes everything. 

I speak from the perspective of someone who has been leading and driving technological transformations for over three decades. I have been programming professionally since 1992 and founded SoftDesign in 1997 with the purpose of delivering technical excellence to companies seeking innovation through technology. I’ve witnessed many transitions: the rise of commercial internet, the mobile revolution, agile methodologies, and cloud computing. But none of these shifts has reshaped the Software Development Life Cycle (SDLC) as profoundly as Artificial Intelligence. 

AI is reorganizing phases, redirecting efforts, and redefining the roles of those who work in software development. 

This shift demands more than a new mindset; it requires a new delivery capability. 

The real impact of AI on software development 

The traditional SDLC follows well-defined stages: research, ideation, design, coding, testing, release, and maintenance. These are complementary activities that require different skill sets and diverse professional profiles. Each stage brings its own technical, business, and user alignment challenges. 

With the rise of generative and predictive AI, we are experiencing an unprecedented transition: a large portion of analytical, repetitive, or interpretive work is being automated or dramatically accelerated. 

At SoftDesign, we’ve spent the past two years testing and applying AI across every phase of the AI-augmented SDLC. The results have been significant: 

• Efficiency gains ranging from 30% to 70% across processes. 
• Full squads achieving up to 55% more productivity and 3x faster time-to-market for MVPs. 
• A proprietary AI agent accelerating API test creation by 70%, ensuring higher-quality code in production. 
• Up to 90% of manual refactoring in legacy modernization projects fully automated. 

These outcomes are not internal wins. They directly impact our clients’ digital products. We deliver software faster, with greater accuracy, and at a lower cost. That means real business results: quicker user validation, risk reduction, and earlier ROI. 

To achieve this, it wasn’t enough to adopt tools. We had to change our teams’ mindset and rebuild the way we deliver software. 

A new SDLC, augmented by AI 

For a long time, the differentiator of a software development company was the robustness of its process. That remains our foundation. The difference now is that this process is intensely augmented by AI. 

Evolving from our mature and highly structured development framework, SoftDesign professionals now work hand in hand with AI agents, from opportunity discovery to live system maintenance. 

We’ve created AI-Augmented Squads that build platforms, APIs, mobile products, and legacy modernization solutions with greater scale, consistency, and speed. 

In this new model, AI does not replace humans. Instead, it amplifies the creative, technical, and analytical capabilities of our teams, further boosting productivity and delivery quality. 

The democratization of code 

AI tools that understand and respond to natural language have simplified countless tasks. Research, content production, video and image generation, and translation are just a few applications of Large Language Models (LLMs) that have increased productivity and reduced costs. 

The software development cycle is no exception. 

AI agents are automating tasks that were once manual, while LLM-based tools are making activities once exclusive to specialists accessible to a broader audience. 

Vibe coding is a prime example. With a simple prompt, it’s possible to generate anything from a webpage to more complex products, such as an online banking interface or a real estate pricing calculator. 

But does that mean anyone can become a software development expert overnight? Certainly not. 

While AI can generate code, particularly for front-end applications, individuals without programming experience often cannot assess its quality, security, or maintainability. 

In corporate environments, this becomes even more critical. For mid- and large-sized companies, there are serious security risks because many tools skip essential steps, such as input validation and proper error handling. 

At SoftDesign, we understand that our expertise in product strategy combined with deep technical knowledge allows us to leverage vibe coding responsibly, as an accelerator. 

It’s highly valuable for rapidly generating a functional MVP. But assessing how that delivery affects user experience, ensuring code scalability, and deciding next steps all require expertise. 

AI is a powerful ally, but it does not replace the critical judgment of professionals in technology, design, and product. 

Unlock your AI projects with augmented teams 

The innovation we’ve embedded into our development process, enhancing human skills with AI copilots, also impacts our ability to deliver AI-augmented solutions more seamlessly. 

We help unlock AI initiatives by identifying opportunities with our AI Discovery service, organizing data, and prioritizing initiatives. And for companies already advanced in AI adoption, we accelerate backlogs with specialized teams. 

No matter where your organization is in its innovation journey, SoftDesign can help you: 

• Map strategic initiatives and structure adoption to ensure security and ROI. 
• Build applications with Machine Learning, generative AI, and custom agents to deliver intelligent reports, interpret large data sets, automate decision-making, and boost operational efficiency. 
• Develop solutions with AI-augmented squads that accelerate time-to-market and increase delivery quality. 

Continuous innovation as a commitment 

None of this would be possible without the internal engine driving our evolution. Our Innovation & Research division tracks trends, tests technologies, develops new competencies, and prepares teams for the future. We validated dozens of AI tools to enhance our SDLC, adopting only those that deliver exponential impact. 

This foundation allowed us to redesign our entire service portfolio with AI at its core. It also ensures we’re not offering the market experiments. We’re delivering consistent innovation with a solid foundation, proven methodology, and a focus on business results. 

Our commitment to effective innovation is already recognized. SoftDesign is ranked among the 80 most innovative companies in Southern Brazil in the 2025 Champions of Innovation list by Grupo Amanhã. 

This award validates what we believe: using new technologies to deliver real value. 

That’s why we help our clients go beyond the hype and build practical AI adoption strategies, mapping opportunities, setting priorities, preparing data, and validating hypotheses. From there, we create solutions that solve real business problems with intelligence, performance, and impact. 

AI is already shaping the future of software development. Companies that recognize this early will secure a competitive advantage that will be difficult to replicate later. 

If you’re still treating AI as a standalone initiative, the risk isn’t just losing efficiency. It’s losing relevance. 

At SoftDesign, we are fully committed to this transformation. We’ve restructured how we think, develop, and deliver software. We1ve embedded AI agents across every phase of the AI-augmented SDLC, and trained professionals with new capabilities and built services that amplify client results. 

We know this journey is only beginning. But we’ve already taken important steps, and we’re ready to move forward with you. Let’s build the future together. 

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In today’s rapidly evolving competitive landscape—and with the fast rise of AI—modernization has become an urgent priority. However, updating legacy systems remains a complex challenge. In this context, AI helps overcome these hurdles with greater depth and lower risk, accelerating the understanding of existing systems, freeing time for more strategic decisions, and driving improvements in speed and quality. 

According to Gartner, 50% of CEOs are prioritizing integration, innovation, and modernization of enterprise applications and software by 2025. In large organizations, where legacy systems support critical operations, the challenge lies in innovating without compromising stability. A difficult but essential step for digital transformation. 

In this article, we explore how AI-powered modernization enables organizations to integrate analytics, automation, and intelligent decision-making without requiring disruptive system rebuilds. 

Why modernize with Artificial Intelligence? 

Companies are undergoing a paradigm shift: we’ve moved past the digitalization phase—focused on migrating processes to digital—and entered the era of intelligent automation, powered by Artificial Intelligence. This new phase demands speed, scalability, and the ability to innovate consistently. 

In this context, modernizing legacy systems is no longer a technical choice, but a strategic necessity. Outdated technologies bring risks due to lack of vendor support and qualified professionals, fail to meet user expectations, increase infrastructure costs, and hinder the adoption of innovations such as cloud, AI, and third-party APIs. 

Legacy code also directly impacts scalability and the speed of delivering new features. When applied to modernization efforts, Artificial Intelligence reduces manual effort and significantly accelerates the software delivery lifecycle. 

At SoftDesign, we leverage AI to accelerate deliveries across multiple fronts. On the back end, unit test generation is automated: developers only need to name the test, and Copilot completes the implementation based on context. We also migrate legacy code to modern standards, ensure compliance with architectural patterns, and accelerate scaffolding by automatically creating repositories, services, and endpoints. 

On the front end, Copilot assists in generating models and services from Swagger documentation, while also providing contextual suggestions for building interfaces with reusable components. In Quality Assurance, AI automatically generates end-to-end test cases with Cypress, increasing test coverage with less manual effort. 

For business leaders, this is a critical moment: digital transformation with AI is a matter of survival in increasingly dynamic markets. Organizations driving this modernization with AI-augmented squads release products faster, improve delivery quality, and reduce project costs. 

Benefits of AI-powered modernization 

According to Red Hat’s The State of Application Modernization report, 78% of organizations are using AI as part of their modernization efforts. Among them, 53% use AI to support application modernization processes, while 42% are adding AI to legacy systems to update them. 

At SoftDesign, we apply intelligent automation and advanced software engineering to modernize systems in a secure and effective way. Our process directly impacts speed, quality, and alignment with business strategy. 

Key benefits of AI-powered modernization include: 

• AI-assisted engineering: up to 60% faster coding, automated test coverage, and support throughout the development cycle. 
• Adoption of modern technology standards: user experience–focused interfaces, cloud-first architecture, and DevSecOps practices ensure scalability, security, and operational efficiency. 
• AI for data-driven decision-making: predictive models and advanced analytics enable faster, more accurate, and insight-driven decisions. 
• Strategic, phased alignment: our approach ensures modernization without disruption, with incremental deliveries aligned with business objectives. 

Use cases and real-world applications 

As shown, AI-powered modernization is already driving change across corporate environments. Some practical examples include: 

• Modernization of legacy systems with AI: companies are using algorithms to map dependencies, suggest refactorings, and identify critical issues in aging systems, reducing risks and accelerating digital transformation. 
• Machine Learning applied to legacy systems: predictive models are being used on historical ERP, CRM, and operational data to anticipate demand, optimize inventory, and improve customer service. 
• AI in the Software Development Life Cycle (SDLC): AI-powered tools optimize every stage of the software lifecycle—from requirements analysis to automated testing, continuous validation, and intelligent documentation. 
• Cloud-first infrastructure as a foundation for modernization: migrating to the cloud and embedding native AI services accelerates time to market, enhances scalability, and enables integrations with modern analytics and automation solutions. 
• AI-augmented engineering: software engineers now rely on AI copilots for code generation, automated security reviews, and continuous integration, boosting productivity while reducing errors. 

At SoftDesign, modernization involves applying AI strategically across every stage of the SDLC. In practice, we use Artificial Intelligence from prototyping and data analysis to MVP creation with low-code tools. 

Our AI agents also assist in backlog writing and prioritization, legacy code analysis, assisted coding, code review and refactoring, and automated test generation. 

Phases of an AI-powered modernization strategy 

Case study: modernizing with AI 

Spring Point, a U.S.-based company specializing in software for the electromechanical industry, modernized its legacy ERP system MotorBase—originally built in the 1990s with a client–server architecture. With SoftDesign’s support, the company developed the first version (MVP) of a new cloud-based SaaS solution, redesigned with a user experience–driven interface. 

• AI Augmented: AI was applied to convert Visual Basic code into .NET Core, generate automated tests, and document business rules, accelerating coding by up to 90%. 
• Lead time reduction: feature delivery cycles dropped from 4 days to 2, doubling development speed. 
• Results: ERP transformed into a SaaS platform, with easier access for global clients. The beta version is already being used by Spring Point’s three largest clients, with a commercial launch planned for 2025. 

According to Troy D. Locke, CEO and co-founder of Spring Point Solutions, integrating AI into software is highly strategic to improve predictability and optimize client operations. SoftDesign’s partnership drives this evolution through testing and experimentation with intelligent features. 

Challenges and risks in AI adoption 

Implementing Artificial Intelligence brings significant opportunities, but also requires attention to critical challenges to ensure sustainable and ethical results: 

• Technical debt and risks: integrating AI into legacy systems can be complex, requiring infrastructure investments, platform upgrades, and process reviews. Poor integration may lead to inefficiencies or even operational failures. 
• Security and compliance: AI-based solutions must strictly follow privacy regulations (such as GDPR or LGPD). Handling sensitive data demands strong protection mechanisms against leaks and misuse. Vendors must also ensure robust protection of source code and business rules. 
• AI and data governance: effective governance involves defining clear responsibilities, monitoring model performance, and ensuring transparency in automated decision-making. It is crucial to mitigate algorithmic bias and maintain continuous audits. 
• Team training and cultural change: AI adoption goes beyond technology. It requires workforce upskilling, leadership involvement, and a culture of experimentation that embraces continuous learning. 

Measuring the results of AI-powered modernization 

The adoption of AI in modernization must generate measurable impact. Some key metrics to track ROI include: 

• Operational cost reduction: automation of repetitive tasks and more efficient use of resources reduce expenses in maintenance, rework, and support. 
• Shorter lead time: AI-assisted code generation and intelligent testing shorten the cycle from conception to solution delivery. 
• Increased engineering efficiency: with AI-augmented tools, teams produce more with less effort, focusing on strategic challenges instead of manual tasks. 
• Faster innovation: AI integration accelerates experimentation, validation, and launches, strengthening organizational competitiveness. 

At SoftDesign, we transform legacy systems into modern platforms by combining intelligent automation with cutting-edge software engineering. By embedding AI into every stage of development, we accelerate coding by up to 60%, automate tests with wide coverage, and deliver scalable solutions with excellence in UX, cloud, and architecture. 

Building the future with Artificial Intelligence 

AI-powered modernization is a strategic path for companies seeking agility, efficiency, and continuous innovation. By combining intelligent automation, integration with legacy systems, and skilled teams, organizations can cut costs, accelerate time to market, and significantly increase productivity. 

SoftDesign is a global software development company that combines design, strategy, and Artificial Intelligence to build impactful digital products. We integrate AI agents across our entire SDLC, boosting squad productivity by up to 55%. 

If you’re ready to take the first steps in an AI-powered modernization plan, count on our expertise in app development, platforms, data solutions, intelligent agents, and Machine Learning models. 

Frequently asked questions on AI-powered modernization 

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But chances are you already know this. So instead of simply highlighting the risks of resisting change — like the threat to your company’s survival — this article will guide you through what it takes to lead a successful digital transformation.

Below, you’ll discover practical strategies for driving innovation, agility, and competitive advantage in today’s digital landscape.

Why bringing digital transformation to life is essential

Digital innovation is more than just modernizing processes. With a strategic approach to digital transformation, your organization can redefine operating models, improve user experience, and build long-term operational resilience.

You might ask, “That sounds great – but how do we make it happen?”.

It starts with identifying the barriers that are slowing your business growth. Common barriers include:

• Scalability challenges: a lack of process automation and system integration across departments can hinder business expansion.
• Overreliance on spreadsheets, paper documents, and disparate systems: manual workflows increase rework, errors, and wasted time.
• Inefficient decision-making: without integrated data and real-time analytics, decisions are made based on outdated or incomplete information.
• Competitive risk: companies that fail to invest in digital transformation will fall behind more innovative competitors.

The impact of digital transformation across industries

Digital transformation affects every business model and operation in a unique way. While some industries are already reaping the benefits of digitalization, others continue to face significant modernization challenges.

To better understand the speed and impact of these changes, let’s take a closer look at how digital transformation is reshaping key industries.

Retail

The retail industry was among the first to fully embrace digital transformation. Online sales platforms, integrated management systems, and data analytics tools are just a few examples of technologies that have driven innovation in several areas, including:

• Personalized customer experiences;
• Optimized and automated logistics;
• Automated inventory management.

Financial Services

The financial sector has undergone massive disruption, driven by the rise of fintechs and digital banks.

Key innovations in this space include the digitization of processes such as account opening, payments, and credit analysis.

In addition, emerging technologies like blockchain and artificial intelligence are enabling a revolutionary shift in how financial transactions are conducted and how risks — including fraud and corporate cybersecurity — are managed.

Here’s a real-world success story that SoftDesign was proud to be a part of:

Sicredi, one of Brazil’s largest financial cooperatives, needed to overhaul its supplier management process. Manual workflows were leading to costly inefficiencies, including the repeated hiring of outsourced professionals and difficulties with financial tracking and accountability.

To address these issues, SoftDesign developed two custom digital solutions:

• Timesheet: a platform to automate vendor billing and payment tracking.
• MGPT (Third-Party Professional Management Module): A solution to professionalize the recruitment and selection of outsourced workers.

As a result, Sicredi achieved an 80% reduction in operational effort related to supplier reporting and completely eliminated manual work in contract creation and modification.

In addition, the platform provided greater transparency, data traceability and access to key performance indicators (KPIs) to support strategic decision-making. Today, more than 900 professionals and 20 suppliers are actively using the solutions, managing more than R$ 200 million annually in supplier invoicing and reporting.

Technology

Unsurprisingly, the technology sector is one of the most advanced when it comes to digital transformation.

Companies like Google, Microsoft, and Apple are at the forefront of innovation, consistently leveraging big data, machine learning, and the Internet of Things (IoT) to develop software, apps, and digital tools.

Industries struggling to modernize

On the other hand, it’s important to examine which industries still need attention to accelerate their digital transformation journey. A prime example is Agribusiness, which scored the lowest in digital maturity among industries.

Key issues cited include a lack of connectivity in rural areas and continued resistance to adopting new technologies.

Healthcare also remains an area of concern. While progress has been made in digitizing medical records, scheduling, and remote diagnostics, significant improvement is still possible.

Technologies driving digital transformation

Business modernization is only possible with digital strategies that enable faster, more integrated, and more efficient processes. Let’s explore the technologies that are driving more resilient and future-ready businesses.

Artificial intelligence in business

Artificial intelligence (AI) is a core pillar of digital transformation. By 2024, 72% of businesses worldwide are already using AI – an increase of 17% compared to 2023.

AI’s ability to process and learn from large data sets has revolutionized customer engagement and operational efficiency. For example:

• Machine learning algorithms can analyze historical data to predict demand, optimize inventory, and identify bottlenecks in production processes.
• Virtual assistants, chatbots, and recommendation engines enhance personalized customer experiences.
• AI-powered forecasting enables companies to identify market trends and predict consumer behavior.
• Talent acquisition benefits from AI tools that streamline resume screening and help identify top candidates.
• Real-time transaction monitoring uses AI to detect suspicious activity and combat fraud.

A clear example of the impact of AI is Liberum Ratings, a leading credit risk rating agency. The company was challenged with managing massive amounts of data, resulting in time-consuming and error-prone analysis.

To address this, SoftDesign implemented machine learning and generative AI solutions that automated report generation and improved analytical accuracy.

As a result, Liberum Ratings reduced analysis time for investment funds by 75% and began to anticipate critical variations that could impact ratings – allowing analysts to focus on higher priority cases.

Cloud computing: the digital infrastructure for innovation

Cloud computing is the backbone of modern business infrastructure, enabling flexibility, scalability, and enhanced security.

By migrating to the cloud, organizations can focus on innovation while relying on a robust and adaptable infrastructure. Key benefits include:

• Scalability, which allows companies to scale resources as needed – especially useful for growing businesses.
• Security, as cloud providers offer advanced protection against cyber threats and data loss.

There are also different cloud computing models to suit the unique needs of each business:

• Public cloud: resources are shared among multiple organizations – ideal for startups or companies with limited budgets.
• Private cloud: infrastructure is dedicated to a single organization, providing greater control and security.
• Hybrid cloud: combines public and private cloud capabilities for maximum flexibility and strategic alignment.

Not sure which cloud model is right for you? Talk to us about it!

SoftDesign offers customized cloud computing solutions to help your organization safely migrate and realize the full potential of the cloud.

Process automation: efficiency and cost reduction

Process automation replaces manual tasks. In other words, it redefines processes by eliminating repetitive, error-prone tasks. The real value is in freeing up talent to focus on what really matters: innovation, strategy and high-impact decision-making.

So how does this work in practice? For example, financial companies use automation software to ensure that processes such as bank reconciliations, invoicing, and payments are completed without human intervention.

This is possible because Robotic Process Automation (RPA) tools simulate human interaction and automate transaction reconciliation. In addition, these tools are designed with compliance processes in mind, ensuring adherence to current regulatory requirements.

RPA robots are programmed to perform repetitive tasks such as form filling, data extraction, and system updates. They operate 24/7 without error and can be deployed quickly.

Another important tool is Business Process Management (BPM), a methodology for mapping, analyzing, and optimizing business processes. With BPM, companies can visualize workflows, identify bottlenecks, and implement continuous improvements.

There’s also the concept of intelligent automation, which combines RPA with technologies such as AI and machine learning to automate more complex processes. For example, automating contract analysis, identifying critical clauses, and suggesting changes.

Chatbots are widely used to handle simple customer queries in real time, and quickly escalate more complex cases to human agents – improving the overall customer experience.

Automation can also be applied to logistics to assist with order tracking and even route optimization. Systems can predict demand, adjust inventory in real time, and coordinate deliveries based on varying conditions such as local traffic.

Key pillars of digital transformation in businesses

For digital transformation to be truly successful, it’s critical to look beyond technology – starting with the most critical factor: behavior.

In this article, we’ll explore how a solid digital culture and a data-driven management approach are essential to driving innovation and positioning your company ahead in the marketplace.

Digital culture and encouraging innovation

Digital transformation isn’t just about technology – it’s about culture. And like all disruption, it faces resistance. This was the case with the steam engine, electricity, the internal combustion engine, and more recently, the computer.

So the real breakthrough is behavioral. To overcome this barrier, your company needs a digital culture that naturally values innovation and experimentation. Some effective practices include

• Cross-disciplinary teams: regular meetings between departments foster collaboration and the exchange of strategic ideas.
• Internal challenges and hackathons: competitions encourage the creation of innovative solutions to real business problems.
• Awards and recognition: have your employees come up with innovative ideas or projects? Reward them to encourage continued interest in innovation.

Finally, a critical point: leadership must be the first to embrace change. It’s up to leaders to communicate the benefits of digital transformation, align the strategic vision, and ensure the resources needed for consistent innovation.

Digital Strategy and the Digital Transformation Journey

Without a clear and well-structured vision, digital initiatives can become fragmented, inefficient, and fail to impact business results. To avoid this, every digital strategy should follow a defined path. Here’s a step-by-step guide:

1. Initial diagnosis: assess the organization’s digital maturity by identifying strengths and areas for improvement. This mapping serves as the basis for more accurate strategic decisions.
2. Set Goals: establish clear and measurable goals that align with the diagnosis. These goals can focus on operational efficiency, cost reduction, or improving the user experience, but always with a strategic direction.
3. Prioritizing initiatives: select actions with the highest impact and feasibility, ensuring a focus on what will truly create value and accelerate digital transformation.

Digital transformation roadmap

A roadmap helps visualize each phase and ensures that initiatives are aligned with business goals. Here’s an example:

Data-driven companies: the power of data in decision-making

The ability to collect, analyze, and interpret data is embedded in the DNA of digital transformation. By 2025, intelligent workflows and seamless human-machine interactions are expected to be as common as a balance sheet.

Want to see how this “prediction” is already a reality?

• Companies like Amazon and Spotify are using data to make personalized recommendations and improve the customer experience.
• Companies are using real-time data to optimize delivery routes, reduce fuel costs, and improve driver safety (e.g., avoid high-risk areas).
• Market data and customer feedback are used to develop products and services. For example, Netflix uses viewing data to create content tailored to its audience’s preferences.

In addition, tools are updated automatically, making compliance easier.

But how do you know if your organization is on the right track when it comes to using data to make decisions? Here are the seven key characteristics of data-driven companies:

1. Data is embedded in every decision and process;

2. Networks of connected devices enable advanced, real-time analytics;

3. Modern databases (such as graph databases and NoSQL) support rapid queries and reveal new relationships between data;

4. Data is organized as a product, with dedicated teams ensuring quality, accessibility, and continuous improvement;

5. The Chief Data Officer (CDO) is focused on creating value and new revenue streams from data;

6. Data is shared (internally and externally) on collaborative platforms that drive innovation on a global scale;

7. AI tools automate data protection, recovery and compliance.

Software development as the driver of digital transformation

As we’ve seen, user experience is at the heart of digital transformation and in software development, it plays a critical role in a company’s competitiveness.

Your ability to understand (and anticipate) the needs of your target audience will set your product apart. In doing so, it goes beyond the obvious and helps your brand turn challenges into competitive advantages.

For example, a fintech can evolve its basic credit scoring system to incorporate machine learning, allowing it to predict defaults based on its customers’ historical data.

In summary, we have three main elements: opportunity, integration and scalability. However, digital culture needs the best support, and here we believe there are methodologies that are 100% capable of accelerating the delivery of digital solutions.

This is where agile methodologies like Scrum and Kanban come in. Scrum breaks software development into short cycles (typically 2-4 weeks), allowing organizations to test and adapt solutions quickly.

Kanban, on the other hand, visualizes the workflow on a board: an easy way to identify bottlenecks and improve overall operational efficiency.

When we talk about agility, we can’t overlook DevOps, which integrates development and operations to accelerate software delivery and ensure better quality.

With DevOps, e-commerce companies, for example, can quickly release updates to their websites without disrupting sales. Test automation and deployment automation reduce human error, while collaboration between teams improves system stability and performance.

The future of DevOps is even more promising with practices like GreenOps, which focus on reducing the energy consumption and environmental impact of IT operations.

Governance and Security in Digital Transformation

Without proper digital governance, organizations face regulatory and operational risks that can jeopardize the entire digitalization journey.

That’s why it’s essential to establish a strong digital governance model in advance of software development, which should include the following elements:

• Clear definition of roles and responsibilities;
• Data management policies;
• Monitoring tools;
• Full alignment with the regulations of the countries involved in your digital product – such as the General Data Protection Law and the ISO 27001 standard (which sets strict standards for data protection and information security).

Business cybersecurity: protecting data and operations

Digitalization also increases exposure to cybersecurity risks such as ransomware, phishing, and data breaches.

Threats like these can cripple operations, cause financial loss, and damage a company’s reputation.

To mitigate these risks, your organization must employ the best prevention and defense strategies, such as

• Advanced firewalls;
• Continuous monitoring;
• Threat intelligence.

Measures like these help identify and neutralize attacks before they cause damage. In addition, good security practices such as multi-factor authentication, backups, and employee training help protect critical infrastructure.

Digital transformation: the path to innovation and competitiveness

Innovation through digital transformation goes beyond process modernization. It’s about redefining business models, improving customer experience, and ensuring market leadership and competitiveness.

To be successful, however, this journey requires a well-defined strategy, agile methodologies, and customized solutions that meet the specific needs of your organization.

Frequently asked questions about digital transformation

Digital transformation generates many questions. Here are the main answers.

O post Digital Transformation: understanding the impact, key technologies, and why your business should invest in innovation apareceu primeiro em SoftDesign.

AI’s predictive capabilities enable future scenario simulations based on historical data and real-time patterns, leading to more accurate diagnoses, personalized treatments, and improved hospital management. 

Healthcare companies embracing AI are at the forefront of innovation, optimizing processes, reducing costs, and, most importantly, saving lives. From patient triage to surgical robotics, AI is driving the evolution of modern medicine—creating significant opportunities for healthtech companies and technology solution providers in the sector. 

Understanding AI in Healthcare 

The healthcare industry is undergoing rapid digital transformation, with AI playing a central role. In June 2024, the G20 extensively discussed the potential and challenges of AI in healthcare, emphasizing its global significance. 

According to Socorro Gross, representative of the Pan American Health Organization (PAHO) in Brazil: 

“An example of AI being used effectively was in the diagnosis and treatment of COVID-19. By leveraging AI responsibly, we can ensure safety for all citizens across the Americas. G20 countries must contribute to harnessing the benefits of these technologies while ensuring no one is left behind.”

To fully leverage Artificial Intelligence in Healthcare, key concepts must be understood. Find out what they are below.

Architectures and Technologies 

AI models in healthcare rely on various architectures and technologies. Innovations like TensorFlow, PyTorch, and Scikit-learn support Machine Learning models, assisting with data processing, training, and validation. 

Interoperability standards like FHIR enable data collection from multiple sources, improving model training and accuracy. 

Integration with Hospital Systems 

Seamless integration with electronic health records (EHRs), telemedicine platforms, and IoT medical devices is crucial. Large datasets fuel predictive models, but challenges include minimizing data noise and ensuring high-quality inputs. 

Missing or poorly formatted data can compromise AI models, highlighting the importance of reliable and structured information. After all, the accuracy and reliability of predictions are directly linked to the quality of the data provided to the model.

Key Applications of Artificial Intelligence in Healthcare 

AI is transforming various medical fields, enhancing efficiency and safety when implemented with proper methodologies and risk management. Below are its main applications: 

1. Medical Imaging Diagnosis

AI has revolutionized imaging diagnostics, improving X-ray, CT scan, and MRI analysis. Solutions like DeepHealth and CheXNet enhance accuracy and facilitate early disease detection by analyzing vast datasets and comparing images to historical records. 

This means that radiologists rely on these systems to detect subtle signs of pathology that might go unnoticed by the naked eye. In this context, AI in X-ray imaging enhances diagnostic reliability and streamlines workflow—benefiting both patients and healthcare professionals.

2. Telemedicine and Virtual Assistants 

AI-driven remote consultations optimize scheduling and automate triage, reducing wait times and streamlining patient access to care. Clinical chatbots further enhance efficiency by managing initial patient interactions. 

This approach not only reduces patient wait times but also establishes a direct connection between patients and the medical team—without overwhelming staff with simple requests.

3. Natural Language Processing (NLP) 

NLP enables AI to analyze medical records and generate clinical reports. Tools like MedBERT and BioBERT extract critical insights, supporting accurate diagnoses and aiding clinical decision-making. 

This technology also supports clinical decision-making by presenting organized data and insights that assist the physician’s reasoning.

As a result, text analysis becomes a strategic tool for patient management and follow-up, enabling greater personalization of care and treatment.

4. Surgical Robotics 

AI enhances robotic-assisted surgery by improving precision and reducing risks. Systems like Da Vinci enable minimally invasive procedures, leading to faster recovery times and improved outcomes. 

In this context, the use of algorithms and sensors to guide movements makes surgical procedures safer and more efficient, bringing significant benefits to both the success of the operation and the patient’s recovery.

5. Predictive Analytics in Healthcare 

AI-powered predictive models identify health risks based on historical and behavioral data, helping hospitals allocate resources more effectively and enabling proactive patient care. 

For example, hospital readmission—when a patient is hospitalized again after discharge—can be minimized through predictive analytics-driven protocols. This approach enhances resource efficiency and ensures more precise, personalized patient care.

6. AI-Assisted Drug Development 

AI accelerates drug discovery by analyzing molecular interactions and identifying promising compounds. Platforms like Atomwise streamline pharmaceutical innovation, reducing time to market for new treatments. 

7. Remote Patient Monitoring and IoMT 

The Internet of Medical Things (IoMT) integrates wearable sensors and home monitoring devices with AI-driven analytics. This allows real-time health tracking and early intervention for at-risk patients. 

Practical examples include smart wristbands that monitor heart rate and connected scales that track weight and body composition.

When analyzed by specialized software, this data enables quick and accurate interventions by doctors.

8. Smart Hospital Management

AI enhances hospital efficiency by automating administrative tasks, from appointment scheduling to bed management. AI-driven triage systems further optimize patient flow and resource allocation. 

In addition to these applications, chatbots and automated triage systems assist with initial care by filtering information, categorizing, and directing patients as needed.

This organization enhances workflow and enables more efficient resource allocation to improve operational efficiency and elevate the quality of service provided.

9. Healthcare Data Security 

Protecting medical information is, undoubtedly, a top priority for all professionals in the field. AI strengthens cybersecurity by detecting fraud patterns and monitoring data traffic for potential threats, ensuring medical record integrity and compliance with regulatory standards. 

10. Personalized Medicine 

Machine Learning models analyze genetic data and patient history to tailor treatments, maximizing efficacy and minimizing side effects—advancing precision medicine. 

By considering the unique variables of each patient, AI in healthcare transforms medical practice, adapting to specific needs and ensuring better therapeutic outcomes.

11. AI-Driven Medical Education

AI-powered simulations and adaptive learning tools provide continuous training for healthcare professionals, enhancing skills and improving patient outcomes. Adaptive learning tools and AI-driven simulators offer practical, interactive training.

Additionally, simulating complex scenarios in virtual environments enhances the training of skilled and confident professionals, while driving continuous improvement in healthcare delivery.

Challenges of AI in Healthcare

Despite its advantages, AI adoption in healthcare requires compliance with regulatory frameworks such as HIPAA. Organizations must prioritize: 

• Data transparency and governance;
• Secure data lifecycle management;
• Protection against unauthorized access;
• Algorithmic fairness to prevent biases.

Balancing innovation with ethical considerations is crucial to maintaining patient trust and ensuring equitable AI-driven healthcare solutions. 

The Future of AI in Healthcare

AI’s future in healthcare promises even greater advancements, including more versatile models and expanded IoMT applications, leading to enhanced medical precision and efficiency. 

The MedTech sector is emerging with solutions that combine diagnostic automation and clinical decision support software.

Solutions such as IBM Watson Health, Huna AI (breast cancer detection), and Neomed (automated medical report processing), demonstrate AI’s potential to revolutionize clinical management and healthcare delivery, creating opportunities for the emergence of innovative businesses.

Preparing for the AI Revolution in Healthcare

To maximize AI’s value, healthcare executives must move beyond isolated technology adoption and implement a comprehensive digital transformation strategy. Key steps include: 

• Investing in scalable infrastructure with interoperable systems;
• Continuously training teams to leverage AI-driven insights;
• Monitoring KPIs like diagnostic accuracy and operational efficiency.

Proactive modernization, guided by measurable performance indicators, ensures innovation while maintaining the security and reliability required in healthcare services. 

AI-Driven Healthcare Transformation: The Next Step

AI is reshaping healthcare by driving operational efficiency, personalized treatment, and enhanced clinical decision-making. Investing in AI is essential for maintaining competitiveness and improving service quality. 

To explore how Artificial Intelligence can transform your healthcare organization, discover SoftDesign’s customized solutions. Our experts are ready to take your company to the next level. 

FAQs About AI in Healthcare

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Its main healthcare software is an electromyography sensor that quantifies information from muscle data. The sensor captures the electrical activity of the muscles, both contraction and relaxation, and presents such data to the health professional.  

To boost innovation to its product, in 2019, Miotec joined forces with SoftDesign to create Mioflux, a piece of equipment connected to the electromyography sensor capable of measuring urinary volume and flow. The goal is to support pelvic physiotherapists in the treatment of children with urinary difficulties, people in the postoperative period, and adults with voiding disorders.  

We spoke with Fabiano Ergoni, CEO & Founder of Miotec, to learn more about the challenges and achievements of this project. Watch the video below and learn about the history of Mioflux. Don’t forget to turn on the subtitles.

Why work with SoftDesign? 

Miotec had an achilles heel: talent retention. The company set up internal hardware and healthcare software teams to develop its equipment. However, after a few months, the professionals ended up leaving the company and taking their knowledge about the products away. 

Fabiano Ergoni, CEO and Founder of Miotec, understood that this problem should not be his and that, as an entrepreneur, he needed to dedicate himself to business objectives and to the launch of new products. When talking to SoftDesign, he felt safe with the company’s transparency:  

“Osmar (A. M. Pedrozo – SoftDesign’s CEO) was able to listen to me and understand my vision of the future for Miotec. He didn’t want to sell me a ready-made product, he offered me a solution that could be expanded in the future, and warned me about the importance of making a conscious investment”.  

A Creative Planning Process 

With the partnership established, the first step was to start Product Inception a creative process that SoftDesign has been carrying out since 2016. Its purpose is to define the objectives of the project, plan the software development, and define the necessary investment.  

Initially, the idea of Mioflux was quite broad: a healthcare software that could receive several applications and serve the most different types of hardware. But, through market research carried out with health professionals, it was possible to understand the actual pains and needs of the personas.   

In this way, technical and design requirements were prioritized for the first MVP (Minimum Viable Product). SoftDesign’s team of Designers created the product prototypes, focusing on an easy and intuitive interface. The Product Manager, in partnership with the development team, focused on backlog estimates and release strategy. 

Focus on Healthcare Software Development 

While the Miotec team worked on the hardware, the SoftDesign team developed the healthcare software. A communication protocol was created in partnership, so the information transaction had the best performance.  

The SoftDesign team opted for development with Electron, a multiplatform web technology; and used  React to create the interfaces. The visualization of the graphs was done in  D3.js, and its creation in real-time uses HTML5 associated with Canvas. The database chosen was NeDB, as it is lightweight and allows working with documents (exams).  

Following the Agile Method, fortnightly meetings were held, in the sprint deliveries, for alignments and route corrections. Through the Jira tool, everyone was able to monitor the evolution and speed of work daily. According to Fabiano:  

“All of this provided transparency, both for Soft’s managers and for us, the project’s investors. So it was possible to fix problems quickly, and we achieved our goal. The product is already on the market and we have received many compliments”.  

The Future of Mioflux 

The Mioflux is a kind of scale, with a measuring cup, connected to the electromyography sensor (hardware). When the patient urinates in this equipment, it measures the time for the first drop to fall, the volume, and the urinary flow; and transmits this data to the system (software).   

With this information, the physiotherapist prescribes the appropriate treatment, which can often be performed with the aid of Mioflux. This is because the equipment also has a visual biofeedback: a screen with colored circles that the patient can follow to learn to relax or contract the pelvic muscle.  

Hundreds of physiotherapists already have the equipment in their offices. In a constant dialogue with users, Miotec receives feedback and works on the evolution of the product.  

The next step is to extend home care, as many people are not comfortable urinating in clinics. With that in mind, an application will be developed soon, which will enable the sending of information between the patient and the healthcare professional.  

We will continue working together with Miotec to support the implementation of its manifesto: taking care of subjectivity through technology.   

Let’s develop your digital product? Fill out the form below.

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The software has a set of requirements that are divided into Functional (FRs) and Non-Functional (NFRs). This classification makes it easier to understand them, as we will see below. 

Do you need help defining your Software Requirements? Fill in the form so we can help you.

Functional Requirements

Functional requirements concern the functions and information that the software must have, that is, its behavior: how it must react to specific inputs, how it will behave in certain situations, and even establish what the system must not do. 

For example, an application for a financial institution must be able to carry out transactions, payment slips, and make investments. These are three digital product requirements that allow users to perform such functions. 

Functional Software Requirements can still be classified according to their level: the most common differentiation is in relation to business requirements, user requirements, and technical requirements. 

Non-Functional Requirements

Non-Functional Requirements can refer to the criteria that qualify the functional requirements: they are related to specific qualities and restrictions that the software must meet, that is, they do not refer to functionalities themselves, but are part of the product’s scope. 

Non-Functional Software Requirements are sometimes called quality attributes, which means that they are a structured and categorized definition of what is needed to express that a product has quality, according to its specific context. 

Like Functional Requirements, they are subdivided into product requirements such as reliability, efficiency, portability, usability, performance, and space; organizational requirements such as delivery, implementation, and standards; and external requirements such as interoperability, ethical, security, privacy, and legislative requirements. 

We can exemplify by citing compliance with the GDPR (General Data Protection Regulation), which is a very common NFR nowadays. Another example is stating that software needs to be cross-platform, operating on Android and iOS. Yet another is when we define that a solution needs to use encryption because it handles sensitive user data. 

The Transversality of Non-Functional Requirements

For the team building the product, Non-Functional Requirements can be restrictions, standards to follow, or requiring very specific solutions. It is normal, for example, that they need to be resolved at the software architecture level and not in programming because NFRs are “transversal”, that is, they affect all functionalities. 

Once, we developed a product that had a very critical Non-Functional Requirement in relation to availability: the application needed to operate 24×7, for three months, as it was one of the applications used in the operation of a reality show. For this type of requirement, an architectural analysis is needed: you need to identify and remove points of failure, create fallback (plan b), and self-healing solutions. The requirement even affects the hardware and infrastructure, which need to work with high-availability solutions so that maintenance can be carried out without affecting the availability of the software. 

Where Are the Requirements?

Have you noticed that, despite being one of the central concepts in Software Engineering, it is not so common to hear about requirements? This happens because they ended up associated with a waterfall workflow model, which is bureaucratic and predictive. 

It’s not the requirements that are to blame, it’s the professionals: analysts who expected the customer or user to define their requirements and then stick with that list until the delivery. There was no room for learning, feedback, or strategic changes. 

This behavior became meaningless when the technology market evolved towards agile, product-focused approaches. The area sought other tools that would help change the relationship between the team and stakeholders, adopting concepts such as OKRs (Objectives and Key Results), product metrics, business objectives, user stories, BDD (Behavior Driven Development), and acceptance criteria. 

However, that doesn’t mean the “end of requirements’. These tools represent yet another evolution in the way of defining them, as well as other techniques that had previously appeared. Regarding current tools, they have the following advantages: 

● Data-driven and more focused on business impact; 

● User-centered – focused on people; 

● Less verbose, more focused on interaction than documentation; 

● More collaborative, because the work is less centralized in an analyst, as it is more distributed in an interdisciplinary team; 

● More change-friendly, that is, they create a dynamic that better accepts product changes and evolutions. 

Who Defines the Requirements and When?

This depends on the type of process and life cycle adopted; two concepts that also come from Software Engineering. In an older lifecycle, the norm was for requirements to be defined all at the beginning of the project. It was common to use the term “collect” or “elicit”, that is: the idea was that a Systems or Business Analyst would obtain requirements from users. 

Nowadays, in current methods, we start from slightly different assumptions. We understand that for innovative products it is impossible to discover all the requirements at the beginning of the project; that the user needs to provide usage feedback; and that it is the product team’s job to translate that feedback into requirements. 

For this reason, building requirements is a collaborative process. The configuration varies a lot, but we can have a Product Manager (PM) working at the business level, defining the product vision, metrics, and business objectives. The Product Owner (PO), who is in direct contact with the development team, facilitates the process of turning big goals into user stories. Finally, the team participates in this refinement, as it is responsible for defining the technical solution that will meet the proposed needs. 

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Amid a scenario full of uncertainties and risks, the event brought more than 71,000 people (42% women) together to discuss the role of technology in the future of society. In times of the pandemic, wars, and political, economic, and environmental crises around the world, experts and global leaders shared trends and pointed out paths for 2023.

Opening Night

During the opening ceremony, Paddy Cosgrave, CEO and Founder of the Web Summit, highlighted in his speech that this year’s edition was the largest ever. In addition, he highlighted the significant increase in the number of Brazilian and Ukrainian startups at the conference.

Among the speakers at the opening ceremony were the Minister of Economy of Portugal, António Costa Silva, the Mayor of Lisbon, Carlos Moedas, Apple’s VP of Environmental Initiatives, Lisa Jackson, and Binance Co-founder & CEO, Changpeng Zhao. Even with so many distinguished presences from the world of business and public administration, the highlight of the night was the surprise participation of Olena Zelenska, First Lady of Ukraine.

In her speech, Olena shared reports of the war that the country is experiencing, which started in February this year, and appealed to the audience for technology not to be used in the service of terrorism. “Your innovations move the world and, more than that, you have the power to determine the direction in which this world moves”, she said, on the central stage of the Altice Arena.

Data Accessible to All

On the first day of lectures at Web Summit, François-Xavier Pierrel highlighted in the “D is for Data” panel that it is time to decentralize and democratize data. However, JCDecaux’s Group Chief Data Officer explained that this does not mean that we will have the answers to all questions. “For the last two years, we couldn’t predict what was going to happen, and it had a huge impact on our lives. The question is: how will we react to these unpredictable scenarios?”.

For Pierrel, the answer is through data division. “What we’ve built through data analysis is the ability to respond to any scenario as quickly as possible, to make sure we can overcome any crisis and keep the business running. The unpredictable can be extremely negative, but also surprisingly positive. This will depend on our ability to find answers and opportunities”.

Collect, activate, structure, transform, leverage, and explore are key steps in a data-driven strategy. After reaching this cycle, JCDecaux set a new goal: to implement the D Strategy – Decentralize, Democratize, Demultiply. This strategy has three main objectives: 1) expand the data community within the organization; 2) expand access to data to as many people as possible, and 3) enhance the ability to drive innovation.

According to Pierrel, data is a fantastic lever to achieve any business objective. “I’m not suggesting that people become Data Analysts, but I think it’s important that all levels of the organization realize the value of data. This can be put into practice through a click, learn, export, and get back to work. There is no need to dive deep into data because what we really want is for them to support people’s decision-making in their areas of expertise”, he concluded.

Turn Uncertainties into Opportunities

The Fintech market — considered a global phenomenon — has become a saturated and highly competitive environment. With an economic recession on the way, the MoneyConf stage gathered a significant audience in the 2022 edition of Web Summit. To discuss the future of the sector, experts shared analyzes and forecasts in the “Fintech 2023: what next?” panel.

According to Tegan Kline, Co-founder of Edge & Node, Fintechs experienced a huge boom due to the inability of large banks to take advantage of technology. “Traditional banks do not serve individual users, as they are concentrated in customer volumes and corporate accounts. That’s why platforms like PayPal, which basically charge no transaction fees, are successful”.

Tegan pointed out that it is difficult to predict how the market will react, but guarantees that there are many opportunities in the crisis. “Businesses are emerging and there are areas that we are not paying much attention to yet: NFTs and Cryptocurrencies, for example, a branch where many people invest millions of dollars”.

According to Carolyn Rodz, Founder of Hello Alice, we all want freedom of choice, as well as knowing how banks operate and share our information. “Right now, the market is terrible, and we’re likely to be impacted one way or another. We represent a very small slice of the financial market (2%), but there are opportunities emerging, and we need to be attentive while the economy recovers”.

Carolyn highlighted that the market will react and that the key to this is understanding how Fintechs can work together with banks and governments, as they have a lot of power and influence. Tegan agrees that systems need to be decentralized. “I believe in the potential of the metaverse and the blockchain. What Google does for the decentralization of the web, The Graph does for Web3. Decentralized networks guarantee open data, always available and easily accessible”.

Brazil In Focus

Even with the forecast of a challenging economic scenario for the next year, Brazil was represented at the event in prominent stands, and by thousands of entrepreneurs and hundreds of startups. In the panel “Brazil in focus: why is the startup ecosystem booming?” Felipe Matos, President of the Brazilian Association of Startups (Abstartups) said he believes there are many reasons why the Brazilian ecosystem is growing so much.

For Matos, the pandemic boosted this growth. “We had an increase in digital demand at a time when the macroeconomic scenario in our country was favorable. With that, we managed to attract a lot of investments during the last two years. In 2021, Brazil raised 9.8 billion dollars in Venture Capital investments, and now we already have 16 unicorns, and in 2018 this number was basically zero”.  

Mariana Vasconcelos is the Founder & CEO of Agrosmart, and when she started as an entrepreneur, there was practically no ecosystem. “I come from the countryside and in Brazil there is a lot of business concentration in São Paulo, which makes access to institutions like Abstartups, for example, difficult. So we went through a different step-by-step process starting at the local university, which connected us with a startup accelerator, which then introduced us to investors. When we started, there was little capital available, angel investors and the legal framework for startups was not regulated yet”.

Brazil represents a giant market. We are 214 million people, and there are many bureaucratic and tax-related challenges. According to Mariana, in the future, our country will be a power in the provision of ecosystem services. “Brazil is a huge agricultural producer and exporter. I believe we have an opportunity to increase our market value through the intersection of agriculture and technology. This will allow us to create business models to finance a transition that will result in the export of more environmental services.”

The Future of Marketing

On the second day of lectures at Web Summit, one of the main featured panels was Marketing in 2023, with Sir Martin Sorrell, Founder of S4 Capital, and Julia Goldin, Global Chief Product & Marketing Officer of Lego. The experts spoke about trends for the future and discussed the economic recession and the political crisis.

According to Sorrell, 2023 will be a very difficult year. “The next ten years will be very different from today’s reality, due to new technologies and the fragmentation of the world. I believe that the North and South American markets will be more relevant. We have more than ever to be strategic when making bets on how to invest and where to expand geographically.”   

Julia pointed out that for the Lego Group, diversification into multiple markets is important, mainly to achieve the purpose of impacting the largest possible number of children around the world. “We opened a new factory in Vietnam, aiming to have more representation and visibility. The Asian market is certainly expanding”.

Julia also highlighted that in times of economic uncertainty, it is normal for companies and consumers to be afraid. “Thinking about business, this means that we need to pay even more attention to the experience we deliver along with products and services. We are very focused on creating the best products, taking into account important points such as passion and desire to buy, delivering an incredible holistic experience”.

The evolution of the digital environment and the metaverse are also opportunities to expand markets, as they facilitate the segmentation of audiences, which is excellent for marketing. “These spaces will be enabled with new technologies that will be more immersive and advanced. This will create opportunities for people to engage across different devices and connect with millions of people at the same time”, Julia concluded.

The Future of Software

Another talk that gathered many participants at the Web Summit was “Software may be eating the world, but low-code could eat software”. According to John Brisco, Co-founder & CEO of Coherent, software companies have begun to break ties with traditional organizations: “What we have seen in the last ten years is the creation of companies like Netflix, Airbnb, and Uber, which use software to promote a disruption in business models”, he explained.

However, as time went by and with the emergence of low-code and no-code, the software also began to experience a disruptive process. For Christine Spang, Co-founder & CTO of Nylas, in the last decade many people started to have interactions with software, mainly when creating businesses. This resulted in a high shortage of professionals. “We don’t have enough people to create that much code anymore. Low-code requires little knowledge of programming languages and, therefore, has become a solution for those who need to develop”.

According to experts, in the future, we will all be developers. “The reality is that there are not that many programmers in the world. Therefore, we need alternatives that can help in the more efficient use of these professionals. Low-code will be present in 65% of new applications by 2024. This will happen because it is easier, simpler, and more efficient”, emphasizes Brisco. 

Programming remains one of the most promising careers in the modern world. However, for Brisco, in the universe of startups, it is not just programmers who develop businesses. “The successful professionals of the future will be those who manage to translate traditional programming languages, while learning new technologies such as low-code and no-code, for example. Teams will be increasingly collaborative. If you transit between these two worlds, you will certainly have a guaranteed job”, he concluded.

The Future of Social Networks

Finally, we will share important insights from the lecture “Search beyond the search: the biggest opportunity in digital marketing”, in which Neil Patel, Co-founder of NPD (Neil Patel Digital), highlighted that users are more active on social networks than on search sites. “Google searches appear in the 5th position of the list that ranks the use of media on the internet, where videos watched on TikTok are in first place”.

Patel pointed out that marketing is becoming increasingly crowded and expensive, and with so much competition, there are many sites sharing the same information. With that in mind, how can we become relevant among those who really matter to our business? 

The answer lies precisely in the search for information. “From the moment we are born, we seek knowledge. And an important fact is that 15% of all searches on Google have never been searched before. This is important because if you are always chasing what others are doing, it becomes very competitive”.

Neil Patel said he believes search engines transform us. “During the journey of discovery, people change as they learn. The same happens with the algorithms, which adapt according to what the user is looking for. If they see that the second result was considered more valuable, they automatically start changing what will be shown to you and millions of other people. That’s the power of the search engine”.    

Over time, patterns of behavior change, and so do algorithms. Ever wonder if your product users are searching for information via voice, text, on a computer, or with the help of Alexa? For Patel, original content can be the key to standing out among so many repeaters.

Resilience to Drive Businesses and Boost Innovation

According to the speakers who spoke at the event, the coming years will be full of challenges, which is why resilience remains on the list of essential behavioral skills for professionals in the technology sector. However, not everything is in crisis; in 2023 Web Summit will have its first event outside Europe.

The summit will be held in Rio de Janeiro between the 1st and 4th of May and should bring 15,000 people together. In November of the same year, the conference will return to the stage of the Altice Arena, in Lisbon. We are already looking forward to these next editions, and we hope to meet our Anexth partners again, who in this year’s edition were part of the Beta startups team.

If you need help developing transformative digital solutions, contact us using the form below. Maybe next year, your business may also make it to the list of startups at the largest technology conference in Europe.

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Startups, scale-ups, and corporates have this goal in common. Therefore, through technology, they seek ways to improve, increase and innovate processes, products, and services. This is an exercise that requires expertise and a lot of discipline and, of course, extra doses of courage, authenticity, and entrepreneurship.

However, the innovation journey does not have to be undertaken alone. At SoftDesign, we combine experience, strategic vision, and a Collaboration Culture to deliver the best products. In this sense, in the following article, we explain how we can help your business become more innovative, from idea to result.

Startups: Developing Your New Digital Business

According to Ries, “a startup is a human institution designed to create a new product or service under conditions of extreme uncertainty”. In other words, if the journey of creating startups is full of doubts and risks, it is essential to seek support throughout the entire process, from investigation and analysis, whether on market or target audience; up to software development. After all, the main objective is to drive new products and services to market-fit.

Finding a market and developing a product capable of satisfying it may seem like something simple, but it is not. Currently, about 90% of startups end up not surviving their first years. To minimize this risk, we offer services that support the entire journey of creating new digital businesses:

• In our Product Conception service, we develop the business model and the product idea, exploring the problem it solves, identifying users and defining the value proposition. To achieve this, we use Design Thinking, Lean Startup, User Research, and UX Design approaches.
• In Product Experimentation we create prototypes or No-Code/Low-Code MVPs to validate business models, considering the feedback from the first users, which allow us to test the product’s acceptance in the market.
• In addition, we also support startups in the Development of their digital solutions, using the best technologies, always with squads that work with the Agile Method.

To evolve through all these phases, it is important to have skills and expertise in different areas. Therefore, teams formed by multidisciplinary and diverse professionals are much more than a must-have to develop innovative businesses.

In real life, a startup is a world of possibilities, where everything happens simultaneously: the creation of new features, operational adjustments, attracting new customers, and marketing strategies. With the ideal partner, these challenges can be overcome.

Scale-ups: Accelerating Your Product

In the case study The Scale-Up Report, Sherry Coutu (2014) defines scale-ups as “companies that sustain long periods of rapid expansion”, as they have an average growth in job creation (or turnover) of more than 20% per year over a period of three years. For the author, this type of business drives economic advancement by allowing a greater number of companies to reach the stage of global scale. 

Unlike the startup, a company in the scale-up stage already has a validated and more sustainable business model. At the same time, scaling a digital product is a decision that implies changes and challenges. After all, once you reach this stage, growing pains quickly begin to surface. To overcome the limits of scale and boost the product, it is necessary to work on solving Design, Architecture, Product Marketing, and Cloud bottlenecks, for example.

At SoftDesign, in addition to the Software Development service, we also work with several Consulting services in these key areas:

• Design: we create or improve the experience of your users, through User Research, User Experience, and User Interface;
• Architecture: based on technical objectives to be achieved or impediments related to stability, continuity, or scalability, we propose possible solutions;
• Marketing: we evaluate strategies, personas, attraction, and conversion channels and suggest a specific go-to-market plan;
• Cloud: we promote collaboration between development and maintenance functions, working with the largest providers: AWS, GCP, and Azure.

To accelerate innovative businesses and create a competitive advantage over the competition, it is essential to scale safely and with quality. After all, growing digital products are under pressure, as they need constant deliveries. In this sense, it is necessary to develop methods and tools that help work organizations in such a way that it is possible to increase the rates of productivity and predictability.

Corporates: Digital Transformation In Practice

The search for innovation affects all types of companies, including well-established ones. Corporates also need to develop processes, while improving and expanding their offer of products and services. This is one of the main strategies to stay alive and competitive in a market full of players that were already born and fully adapted to the digital world.

According to Franco (1991), “a company is any entity established under any legal form for the exploitation of an economic activity, whether commercial, industrial, agricultural or the provision of services”. For these businesses, the challenge is to maintain the essence by sustaining operations that are already well-established and in operation, while creating a more disruptive future, capable of keeping the organization profitable and attractive among the next generations of customers. To achieve the best of both worlds, collaborative innovation is an important ally.

In this sense, we can support your organization with Agile Consulting, which accelerates the adoption of agile methods, through mentoring, to transmit our knowledge in frameworks such as Scrum, Kanban, and DevOps to your team.

In addition, we work with Outsourcing, completing development squads with high-performance professionals, who work in the areas of Software Architecture, Programming, Quality Assurance, UX/UI Design, Products, and Projects. This is an essential resource for companies with an in-house IT team, which suffer from demand fluctuations, often requiring a professional with specific hard skills.

We know that the challenges of innovating in well-established businesses are diverse, but being part of an innovative business team has its advantages. One of them is constant learning. With that in mind, don’t leave your corporate heritage and leadership lost in the past. 

Let’s innovate together.

We know that innovative businesses generate complex challenges that require a lot of understanding of the product or service in question. Moreover, in contemporary society, consumer habits and behaviors change as fast as the technologies in use. Therefore, understanding it in its essence is a key strategic factor that allows us to launch products that will actually be used by users.

Count on us to create transformative digital solutions with design, strategy, and technology.  At SoftDesign, we have the best option to meet your needs, as we work with startups, scale-ups, and corporates in a personalized way. Fill out the form below and chat with one of our experts. 

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In this scenario, some questions are inevitable. Did all the startups that emerged in recent years really have innovative potential? Could it be that so many digital products were effectively suited to their market and optimized for users?

The truth is that glamorized innovation is a trap. When the responsibility for a product’s success rests with the genius entrepreneur or creative inventor, business failure is always close at hand. True innovation, driven by multidisciplinary teams and based on continuous experimentation, brings success closer – and makes it possible to create digital products that will be loved and generate value.

Need support to really innovate? Fill in the form below:

How to Drive Innovation?

The first step is knowledge. Relying on the work of researchers who are at the forefront of developing innovation frameworks is essential to achieving satisfactory results. Since the 1980s, the area has been studied by theorists around the world, and real experiments have been conducted to validate such theories.

Already in the book Innovation and Entrepreneurship (1985), by Peter Drucker, it was discussed the orientation that innovation should be developed through scientific thinking focused on empirical data, and not based on personal opinions or passions. The following year, Hirotaka Takeuchi and Ikujiru Nonaka released the article The New New Product Development Game, in which they advocated the development of complex products with multidisciplinary teams engaged in iterative experimentation.

Approximately ten years later, in Discovery-Driven Planning (1995), Rita McGrath and Ian McMillan introduced the title’s concept, arguing that in new ventures it is more important to learn about assumptions than to make long-term plans. Soon after, through a multiple case study, Gary Lynn contributed to the article The Probe and Learn Process, saying that he identified that companies capable of innovating in a stagnant economic scenario were those that were using such a process – testing and learning – experimenting with initial and unfinished versions of the product and iterating in this process.

However, it was only from the 2000s onwards, that experimentation practices for Discovery and Validation finally gained the attention of the public. They are among the most current in the area of innovation in digital products.

Customer Development Process

In 2003, Steve Blank presented his newest framework for the technology market. Based on four steps, the Customer Development Process (CDP) aims to discover and validate if: you have identified a need that your potential customer actually has; you have built the right product to satisfy this need; you have tested the correct methods to convert this customer; and implemented the right features in development to meet the demand for your product.

The CDM is still used today and serves so that businesses do not base the creation of their products on premises and/or assumptions.  We can see these four steps more clearly below:

• Customer Discovery: understanding potential customers and the needs you can satisfy;
• Customer Validation: validate if your product really satisfies the customer’s need;
• Company Creation: determine whether you will create this product;
• Company Building: grow your business to support your product.

Source: https://learn.marsdd.com/

Business Model Canvas

A few years later, Alex Osterwalder and Yves Pigneur created the Business Model Canvas (2004). According to them, a Business Model is a conceptual tool that contains a set of elements and their relationships and allows the expression of an organization’s moneymaking logic.

It is a description of the value that a company offers to one or several customer segments. Moreover, it expresses the architecture of the company and its network of partners to create, market, and deliver that value and relationship capital to generate profitable and sustainable revenue streams.

The Business Model Canvas, which allows the creation of a more complete business proposal, is important to identify hypotheses that need to be tested. For the theorist, it is not only the products and services of an organization that make it competitive in the market: the Business Model is also decisive.

Source: Book Business Model Canvas (2004).

The Lean Startup

Eric Ries revolutionized the market the following year in 2011 when he released the famous book The Lean Startup, in which he detailed the build-measure-learn cycle. The method proposed by the author aims to shorten product development cycles and quickly discover whether a Business Model is viable or not.

In practice, the framework involves a cycle of hypothesis creation and testing, in which something small is built (MVP) for potential customers to test. Their reactions are documented by the team, to generate learning and drive new improved cycles.

The Lean Startup idea is to continually improve the product’s offering so that you eventually deliver exactly what your customers want. Thus, the picture of savings becomes a reality, as resources are only used with data that justify them.

Source: https://tinytracker.co/blog/

Testing Business Ideas

Finally, in 2020, in the book Testing Business Ideas, Osterwalder continues his Business Model Canvas and proposes a new framework to innovate Business Models. It aims to minimize the importance of “building” (the Lean Startup) and make the relevance and meaning of “experimenting” clear. According to the author, “testing is the activity of reducing risks chasing ideas that sound good in theory. You test ideas by conducting quick experiments that allow you to learn and adapt.”

In the framework in question, in the lower left corner are the entrepreneurs and in the upper right corner is the positive result of the business. To follow this path, decisions need to be made and Osterwalder proposes that they be carried out based on two cycles: in the first, by creating hypotheses for the Business Model Canvas and, in the second, by testing these hypotheses to learn.

After the round of experiments, the Business Model Canvas must be revised, so that the cycles are repeated until you have data on which to base decisions. This means that through this method, it is possible to discover if the direction we imagine makes sense (Discovery) and validate if the chosen paths have evidence of success (Validation).

Source: Book Testing Business Ideas (2019).

Chasing True Innovation

Conducting such practices within the business is not an easy task. It is necessary to have at least one person who masters the frameworks and leads the team through the development and innovation process.

At SoftDesign, we offer distinguished services that can support true innovation, as they are based precisely on the Customer Development Process, the Business Model Canvas, the Lean Startup, and the Testing of Business Ideas. We act from the idea or problem, carrying out the Product Conception of the solution; then we go on to Experimentation to validate the feasibility of this solution; and finally, we work on Development, from the quickest, which are the MVPs, up to the more robust solutions, evolving from data and user feedback, adding new features and a better user experience.

Contact us! Our multidisciplinary professionals have the necessary skills to support the digital innovation journey of your business.

This article was based on the Final Paper for the MBA in Digital Business (USP/ESALQ), by Karina Klein Hartmann, entitled The adoption of experimentation practices for discovery and validation of digital products in Brazil (Adoção de práticas de experimentação para descoberta e validação em produtos digitais no Brasil).

O post Innovation Beyond Glamour: Frameworks and Practices apareceu primeiro em SoftDesign.

But first, some background

Source: Own image.

What is a Business Model?

Source: Book Business Model Canvas (2004).

So we need to create a Business Plan, right?

Source: Book Testing Business Ideas (2019).

How to innovate in Business Models?

Experiment before you build

Source: Book Testing Business Ideas (2019).

Source: Own image.

Step by step to test innovative business ideas

• From the Business Model Canvas and the Value Proposition Canvas, identify the hypotheses that you want to test;
• Take these hypotheses to a prioritization tool that differentiates what is evident from what is not, and what is important from what is not;
• Start experimenting the hypotheses that are most important to your business and that you do not have evidence, as they have a big impact – if there are many hypotheses with such conditions, start with those “desirable”, that is, start by testing what is related to the customer’s desire.

What is a hypothesis?

• An assumption on which the value proposition, business model or strategy is based;
• A statement we need to learn about in order to understand whether our business idea can actually work;
• Is related to the desirability, feasibility and practicality of the business idea – It is testable (evident), its success indicator is clear, and it describes only one thing (not many).

Source: Own image.

What is an experiment?

• A procedure to reduce risk and uncertainty of a business idea;
• Produces evidence (weak, opinion, or strong, facts) that support or refute a hypothesis;
• It can be fast or slow, cheap or expensive.

The ideal setting for testing ideas

Conclusion

O post The Osterwalder Framework to Innovate in Business Models apareceu primeiro em SoftDesign.