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+91 88387 24261Knowledge graph + vector hybrid that traces gene-drug-disease relationships across PubMed, clinical trials, and internal R&D notes.
R&D scientists need to traverse multi-entity relationships (gene → pathway → drug → trial). Pure vector RAG misses graph-shaped questions; pure graph queries miss semantic nuance.
A hybrid Graph RAG over a curated biomedical knowledge graph plus full-text vector index, surfacing both deterministic relationships and semantic neighbours with provenance.
Permission-aware RAG over the entire enterprise knowledge graph, with citations and freshness signals.
Iterative agentic retrieval that decomposes investment questions, gathers evidence across filings and transcripts, and reasons with citations.
Customer-facing RAG over docs, KB, and changelogs that resolves Tier-1 questions and creates rich Tier-2 handoffs.