How Relevant Software Uses AI to Give Clients a Strategic Edge
When a new client comes to Relevant Software, the questions are almost always the same: what the project will require, where the risks are, and whether the idea is worth pursuing. AI now helps us answer these points from the very first conversation. It analyzes initial requirements, delivers quick effort estimates, and creates early visual prototypes. Clients get a clear, realistic view of their options right away, while many competitors are still running small AI experiments or showing rough internal drafts.
Why AI now stands at the front of the process
Several years ago, Relevant Software used AI mainly for test automation and data analysis. These early tools helped but required complex setup and constant supervision, limiting their impact on real client work.
The turning point came when modern large models became reliable enough for daily use. In 2023, the company introduced AI assistants into routine tasks. Developers used them to write and refine code and prepare test scenarios. Analysts relied on them for research, clarification of requirements, and summaries of long documents. Routine work shrank, and teams gained more time for architecture, planning, and client strategy.
This practical experience led to the adoption of AI agents that now assist with concept validation, early estimation, and requirement analysis. By using agents at the start of each project, Relevant Software helps clients make faster decisions, avoid early risks, and begin development with much clearer direction.
From simple helpers to an AI Estimator that understands projects
In 2024 and 2025, Relevant Software moved beyond stand-alone assistants and built AI systems capable of handling an entire chain of early project tasks. The key result is the AI Estimator, an internal tool that helps the company understand a project from both business and delivery angles.
The AI Estimator reads client requirements in clear language and breaks them into features and work packages. It then compares these elements with thousands of previous projects from the company’s history. Based on this, it proposes realistic effort ranges, sample timelines, and cost scenarios. At the same time, it highlights unclear assumptions, integration risks, and areas where the team needs more details from the client.
This work now takes minutes instead of several days of manual analysis. Human architects and project managers still review every estimate, adjust edge cases, and confirm feasibility. AI provides a strong analytical foundation, while people make the final decision and bear the responsibility.
How AI reshapes the first weeks with a client
Each new engagement starts with an AI-supported discovery step. The team collects existing materials, such as specifications, slides, screenshots, system overviews, and previous reports. AI tools organize this content and surface patterns, gaps, and contradictions that may influence scope, risk, or budget.
Consultants then hold focused sessions with the client. They confirm what AI has found, refine goals, and close open questions. Instead of lengthy, vague discussions, both sides work with a structured draft from the start. After this alignment, the AI Estimator uses the agreed-upon information to prepare the first plans and budgets. Architects and delivery leaders refine these into a final proposal that the client can review and challenge.
For decision makers, this approach offers a clear advantage. They see the logic behind numbers, the main factors that drive effort, and the areas where uncertainty remains. Estimation becomes a transparent process rather than a black box.
Turning ideas into prototypes for non-technical stakeholders
Relevant Software also uses AI to accelerate early product design, which is especially useful for non-technical leaders who want to see ideas rather than just read documents. A dedicated prototype chain helps move from rough concept to simple visual prototype in a short time.
Multimodal tools such as Gemini, Liner, Perplexity, and Claude help structure user stories and main scenarios based on notes, interviews, or existing slide decks. For user interfaces, the team combines v0, Cursor, and Figma MCP. AI suggests first layouts and user flows. Designers then refine these suggestions in Figma and turn them into realistic screen sequences.
For straightforward products, this can result in clickable prototypes within hours or a few days. For complex systems with many user roles and business rules, AI still gives a strong starting point, and designers add depth, detail, and polish. Senior stakeholders see screens and flows rather than lengthy text documents, which speeds up internal discussions and approvals and makes them more concrete.
Investment, leadership, and safeguards behind the framework
Starting in 2025, Relevant Software plans to invest 1 million US dollars in AI and data transformation over the coming years, as outlined in this announcement. This program funds internal tools such as the AI Estimator, delivery forecasting, lead qualification, and resource planning systems, as well as research for regulated industries, infrastructure upgrades, and structured training for engineers and consultants.
A dedicated governance group keeps the framework aligned with GDPR, the EU AI Act, and sector-specific rules in healthcare, finance, and public services, ensuring clients maintain strict control over privacy and security. On the technology side, a cloud-agnostic, open-source-friendly stack on AWS, Azure, Google Cloud, and specialised GPU platforms preserves flexibility and avoids vendor lock-in.
Next steps: making AI a normal part of every serious project
Looking ahead, Relevant Software plans to extend its AI tools and AI development services with more specialized agents that check security, compliance, performance, and cost at the concept stage, not only before release. The company wants to give clients several realistic solution scenarios, each with clear trade-offs, before they commit to a final path.
Human experts will continue to design systems, lead conversations, and approve decisions. AI will take on more of the heavy analysis, pattern recognition, and cross-project and industry comparisons. For clients, this translates into faster clarity, fewer late surprises, and project plans that stand up in both business and technical discussions.
With this AI-first approach, Relevant Software aims to maintain its lead over local prototypes and set a new standard for how consulting and development companies launch complex software initiatives in the age of AI.
How Relevant Software Uses AI to Give Clients a Strategic Edge
When a new client comes to Relevant Software, the questions are almost always the same: what the project will require, where the risks are, and whether the idea is worth pursuing. AI now helps us answer these points from the very first conversation. It analyzes initial requirements, delivers quick effort estimates, and creates early visual prototypes. Clients get a clear, realistic view of their options right away, while many competitors are still running small AI experiments or showing rough internal drafts.
Why AI now stands at the front of the process
Several years ago, Relevant Software used AI mainly for test automation and data analysis. These early tools helped but required complex setup and constant supervision, limiting their impact on real client work.
The turning point came when modern large models became reliable enough for daily use. In 2023, the company introduced AI assistants into routine tasks. Developers used them to write and refine code and prepare test scenarios. Analysts relied on them for research, clarification of requirements, and summaries of long documents. Routine work shrank, and teams gained more time for architecture, planning, and client strategy.
This practical experience led to the adoption of AI agents that now assist with concept validation, early estimation, and requirement analysis. By using agents at the start of each project, Relevant Software helps clients make faster decisions, avoid early risks, and begin development with much clearer direction.
From simple helpers to an AI Estimator that understands projects
In 2024 and 2025, Relevant Software moved beyond stand-alone assistants and built AI systems capable of handling an entire chain of early project tasks. The key result is the AI Estimator, an internal tool that helps the company understand a project from both business and delivery angles.
The AI Estimator reads client requirements in clear language and breaks them into features and work packages. It then compares these elements with thousands of previous projects from the company’s history. Based on this, it proposes realistic effort ranges, sample timelines, and cost scenarios. At the same time, it highlights unclear assumptions, integration risks, and areas where the team needs more details from the client.
This work now takes minutes instead of several days of manual analysis. Human architects and project managers still review every estimate, adjust edge cases, and confirm feasibility. AI provides a strong analytical foundation, while people make the final decision and bear the responsibility.
How AI reshapes the first weeks with a client
Each new engagement starts with an AI-supported discovery step. The team collects existing materials, such as specifications, slides, screenshots, system overviews, and previous reports. AI tools organize this content and surface patterns, gaps, and contradictions that may influence scope, risk, or budget.
Consultants then hold focused sessions with the client. They confirm what AI has found, refine goals, and close open questions. Instead of lengthy, vague discussions, both sides work with a structured draft from the start. After this alignment, the AI Estimator uses the agreed-upon information to prepare the first plans and budgets. Architects and delivery leaders refine these into a final proposal that the client can review and challenge.
For decision makers, this approach offers a clear advantage. They see the logic behind numbers, the main factors that drive effort, and the areas where uncertainty remains. Estimation becomes a transparent process rather than a black box.
Turning ideas into prototypes for non-technical stakeholders
Relevant Software also uses AI to accelerate early product design, which is especially useful for non-technical leaders who want to see ideas rather than just read documents. A dedicated prototype chain helps move from rough concept to simple visual prototype in a short time.
Multimodal tools such as Gemini, Liner, Perplexity, and Claude help structure user stories and main scenarios based on notes, interviews, or existing slide decks. For user interfaces, the team combines v0, Cursor, and Figma MCP. AI suggests first layouts and user flows. Designers then refine these suggestions in Figma and turn them into realistic screen sequences.
For straightforward products, this can result in clickable prototypes within hours or a few days. For complex systems with many user roles and business rules, AI still gives a strong starting point, and designers add depth, detail, and polish. Senior stakeholders see screens and flows rather than lengthy text documents, which speeds up internal discussions and approvals and makes them more concrete.
Investment, leadership, and safeguards behind the framework
Starting in 2025, Relevant Software plans to invest 1 million US dollars in AI and data transformation over the coming years, as outlined in this announcement. This program funds internal tools such as the AI Estimator, delivery forecasting, lead qualification, and resource planning systems, as well as research for regulated industries, infrastructure upgrades, and structured training for engineers and consultants.
A dedicated governance group keeps the framework aligned with GDPR, the EU AI Act, and sector-specific rules in healthcare, finance, and public services, ensuring clients maintain strict control over privacy and security. On the technology side, a cloud-agnostic, open-source-friendly stack on AWS, Azure, Google Cloud, and specialised GPU platforms preserves flexibility and avoids vendor lock-in.
Next steps: making AI a normal part of every serious project
Looking ahead, Relevant Software plans to extend its AI tools and AI development services with more specialized agents that check security, compliance, performance, and cost at the concept stage, not only before release. The company wants to give clients several realistic solution scenarios, each with clear trade-offs, before they commit to a final path.
Human experts will continue to design systems, lead conversations, and approve decisions. AI will take on more of the heavy analysis, pattern recognition, and cross-project and industry comparisons. For clients, this translates into faster clarity, fewer late surprises, and project plans that stand up in both business and technical discussions.
With this AI-first approach, Relevant Software aims to maintain its lead over local prototypes and set a new standard for how consulting and development companies launch complex software initiatives in the age of AI.
