Retrieval-Augmented Generation (RAG)
Large language models grounded in your documents, policies, contracts, knowledge bases, and operational data - so answers are accurate, sourced, and current. No hallucinations from training cut-offs. No data leaving your perimeter.
- Private knowledge ingestion - PDFs, SharePoint, Confluence, SQL, S3, ticketing, CRM, ERP.
- Hybrid retrieval - vector + keyword + structured filters - tuned for your domain.
- Citations on every answer, with the source chunk linked back to the original file.
- Re-ranking, query rewriting, and guardrails to keep responses on-topic and safe.
- On-prem, VPC, or sovereign cloud deployments. Your data never trains a public model.
Enterprise search · policy & compliance assistants · technical support copilots · sales enablement · legal review · customer-facing AI grounded in product docs.