RetrieveIT.ai

RetrieveIT.ai indexes your entire codebase including source files, dependency configs (.txt, .xml, .json), and documentation alongside tools like Confluence, GitHub wikis, and internal knowledge bases. It auto-generates code-maps that provide a structural overview of how applications are organized, what dependencies they use, and how components relate to each other. Teams can query this indexed knowledge semantically -- asking questions like "does App A meet security requirement X" or "which services depend on library Y" and receiving grounded answers with citations pointing to specific files, pages, or configuration entries.

Enterprise teams use RetrieveIT.ai as a living documentation layer that surfaces answers from code and docs together, eliminating the gap between what is written and what is actually built. The platform supports workspace-level access controls, SSO integration, and audit logging for tracking who queried what. It connects to repositories through secure integrations and keeps its index current as code and documentation evolve, ensuring that answers reflect the actual state of the codebase rather than stale snapshots.

RetrieveIT.ai is designed for engineering organizations where knowledge is scattered across repositories, wikis, and documentation tools, making it difficult for developers to find authoritative answers. Its differentiator is the unified indexing of code and documentation together -- rather than treating these as separate search domains, it builds a cross-referenced knowledge graph that can answer questions spanning both. This is particularly valuable for compliance verification, architectural review, and onboarding, where understanding requires synthesizing information from multiple sources.