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An AI knowledge base over 10,000+ pages of technical documentation — equipment manuals, maintenance procedures, safety standards — with hybrid search and grounded answers for plant operators and engineers.
Plant operators and process engineers needed instant access to procedures buried in thousands of pages of equipment manuals, SOPs and safety standards.
Existing keyword search returned document names, not answers, and required users to know which manual to open. New hires took months to navigate the documentation set.
A hybrid retrieval system that combines lexical and semantic search across the full documentation corpus, with an LLM that synthesises answers and links back to the source page in the original document.
An OCR pipeline handles scanned PDFs and CAD-exported diagrams. All answers include a confidence indicator and a direct link to the underlying procedure.
Document ingestion handles PDFs, scans (OCR), Office files and CAD exports, normalising everything into a structured corpus tagged by equipment, procedure type and revision.
Hybrid search (BM25 + dense embeddings, reranked by a cross-encoder) feeds a grounded LLM that produces answers with mandatory page-level citations.
The whole stack runs inside the customer network with no external API calls.
