Build: Agentic & Generative Systems
Enterprise Knowledge & Retrieval (RAG)
Grounded assistants and search over your internal data — with access control, citations, and freshness you can trust.
Retrieval systems that respect permissions, cite sources, stay fresh, and are measured for accuracy. We build the ingestion pipelines, hybrid search, and evaluation harness that turn "a chatbot over our documents" into a system your legal and security teams will sign off.
Who it's for
- Knowledge-heavy functions: legal, engineering, customer support, compliance
- CIOs who have seen a RAG demo fail on real documents
- Security teams who need retrieval to honour existing permissions
What you get
How it works
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01
Corpus & access model
Which sources, who may see what, and how often it changes.
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02
Pipeline
Parsing, chunking, enrichment, indexing — measured on a golden question set.
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03
Assistant
Grounded generation with citations, refusal behaviour, and feedback loops.
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04
Evaluate & harden
Accuracy, faithfulness, latency, and cost before release.
Technical notes
Document-level ACL propagation from source systems (SharePoint, Confluence, file shares) into the index; hybrid retrieval with reranking; chunk-level citations; scheduled and event-driven re-indexing; evaluation with retrieval recall, answer faithfulness, and groundedness scoring.