The client’s engineering teams spent significant time searching for technical specifications, manufacturing process documents, and quality assurance records scattered across multiple internal systems — wikis, file shares, legacy databases, and email archives.
We built a RAG-based knowledge agent that indexes documents across these sources, maintains access controls mirroring the original systems, and provides engineers with natural language search over the combined knowledge base. The agent returns relevant document sections with source citations for verification.
Key technical decisions included designing the vector indexing to handle highly technical semiconductor terminology, implementing incremental indexing so new documents are available without full re-processing, and building a feedback mechanism for engineers to flag incorrect or outdated results.
The agent operates as an internal tool, accessible through the client’s existing communication platforms. It does not generate conclusions or recommendations — it retrieves and surfaces existing documented knowledge, leaving technical judgment to the engineers.