Retrieval & GraphRAG
Retrieval your enterprise can trust.
We turn scattered knowledge into accurate, cited answers — with hybrid search, GraphRAG grounding and guardrails built for production.
We turn scattered knowledge into accurate, cited answers — with hybrid search, GraphRAG grounding and guardrails built for production.
A complete retrieval platform — from ingestion to cited generation — designed for accuracy and governance.
A knowledge graph combined with vector search for cross-document reasoning and traceable answers.
Vector and keyword search (BM25) with cross-encoder re-ranking for precise, high-recall context.
Ingest documents, databases and SaaS systems with incremental sync, kept current automatically.
Dashboards for hallucination rate, latency and cost per query, visible to your own team.
Slack, Teams, helpdesk and SSO — the platform drops into workflows you already use.
Every response is scored by an automated eval harness before it reaches a guardrail-checked release.
Three stages, one governed knowledge core — engineered for accuracy, speed and control.
Documents and data are connected, cleaned and embedded — ready to be retrieved accurately.
Hybrid search and graph traversal surface the most relevant, traceable context for the query.
The model responds using only retrieved context, with citations attached and guardrails enforced.
Powered by a governed knowledge core — vector database, knowledge graph and semantic cache.
A fixed-scope path to production — not an open-ended research project.
Corpus review, source mapping and a scoped plan with a target accuracy bar.
A live pilot answering real questions from your data, measured against the eval set.
Deployed, monitored and handed over — with your team able to operate it.
Full case study below — including how we handled entity linking across decades of undocumented institutional knowledge.
Decades of siloed knowledge produced hallucinated, untraceable answers from generic AI tools.
Implemented GraphRAG — a knowledge graph with hybrid retrieval, entity linking and citation-backed generation.
Researchers trust the assistant enough to use it as a starting point, not just a search box.
A support team was overwhelmed by repetitive questions spread across help docs, tickets and release notes.
Built hybrid retrieval with re-ranking and a continuous evaluation and feedback loop.
Faster, more consistent answers — with a shrinking support queue.
Tell us about your knowledge sources — we'll return a retrieval approach and eval plan in days.