Enterprise knowledge hub
Ask questions across your documents, wikis, and databases — with cited answers and access controls.
AI RAG Development
Production-grade Retrieval-Augmented Generation systems — accurate, cited, and integrated with your data.
By the numbers
90%+
Retrieval accuracy
4–6w
To production
100%
Citations on outputs
Use cases
Customer-facing document Q&A
Let customers query product manuals, contracts, or support docs with accurate, grounded responses.
Internal policy assistant
Surface HR, legal, and compliance policies instantly with audit trails and source attribution.
Research synthesis
Summarise and cross-reference large document sets — reports, filings, scientific papers — at speed.
Our approach
1. Data audit
Map your document sources, formats, access controls, and quality requirements.
- PDF, DOCX, HTML, databases
- Permissions and filtering strategy
2. Retrieval design
Choose chunking strategy, embedding model, vector store, and hybrid search configuration.
3. Generation & evals
Build the LLM layer with guardrails, citation formatting, and automated evaluation harnesses.
4. Integrate & launch
Connect to your auth, CRM, or ticketing systems and ship to users with monitoring in place.
Expected outcomes
Accurate, cited answers
Grounded responses users can trust, with sources linked back to the original document.
Continuous evaluation
Retrieval and generation quality monitored automatically — no silent degradation.