Our Solutions
Better specifications, fewer disagreements
AI-Assisted Specification
Our AI-assisted specification solution supports the more accurate identification of business requirements, improves the quality of documentation, and reduces development risks. The system is built on a workflow consisting of AI agents capable of analyzing existing specifications, uncovering gaps, identifying critical issues, and processing knowledge in a structured manner.
Our solution creates a GraphRAG-based knowledge base from existing specifications, which supports collaboration among business stakeholders, architects, developers, testers, and AI agents. The system helps document decisions, track changes, and continuously align the specifications with the actual system’s behavior. The result: more accurate, maintainable, and AI-compatible specifications that provide a reliable foundation for development, testing, and change management.
1. The Challenge
In software development projects, business needs are constantly changing, while specifications are often created as static documents. Incomplete or insufficiently detailed requirements can lead to misunderstandings, rework, decisions that are difficult to trace, and a divergence between the specification and the system’s actual behavior. Furthermore, with the emergence of AI agents, documentation must be unambiguously interpretable not only by humans but also by automated systems.
2. The Solution
Our AI-assisted specification solution addresses this challenge by transforming existing specifications into a GraphRAG-based knowledge base, identifying gaps, supporting expert decision-making, and ensuring that the documentation remains consistently aligned with the system’s evolution.
During the process, AI agents analyze the specifications, perform gap analysis, generate interview questions for the relevant experts, and then refine and structure the knowledge base based on the responses. The resulting documentation can be used to generate a development plan, updated specifications, or extracts optimized for AI agents.
3. The Result
- Fewer misunderstandings between business and IT
- Significant reduction in rework
- Faster project setup
- Improved auditability and traceability
- An up-to-date, maintainable knowledge base
- Specifications that can be efficiently processed by AI agents
