Turn existing assets into knowledge,
and let AI generate answers you can use in the field
Bring existing design documents and past deliverables into RAG (Retrieval-Augmented Generation) as knowledge,
and put it to work as knowledge for your AI agents.
DC Agentiqs can build RAG in a serverless setup, understanding chapters and sections in design documents, specifications, and API documentation, as well as meaningful units like methods in source code, so it extracts and answers with only the information you need. Even for a request like "I just want to know section 2.2," it accurately extracts the relevant part without mixing in surrounding content or dropping anything. With low-noise, accurate search, you can put this high-precision RAG to work for reviews, test design, change-impact analysis, and other real-world software development tasks.
Convert information in Excel grid sheets, ruled tables in PDFs, and shapes drawn with AutoShapes into a format AI can interpret. Because diagram and sequence-diagram elements, relationships, and process flows can be handled as structure, existing design assets can be used in AI-agent answers and deliverable creation.
