This is a live RAG (retrieval-augmented generation) system running over the Fusion OS public corpus. Type any question, get a citation-grounded answer from real source documents — no hallucination, no "according to our records" hand-waving.
This demo uses an in-memory keyword-bigram retriever for instant response on a small corpus. Real client builds (Tier 1.B at $5,997 and Tier 2.B at $28,500) use the full architecture below.
OpenAI text-embedding-3-large or Cohere embed-v3 vectorizes every document chunk.
pgvector on PostgreSQL for embeddings. Hot-swappable to Pinecone or Weaviate if needed.
Vector similarity blended with BM25 keyword scoring. Better than either alone.
Claude or GPT-5 with strict citation requirements. Hallucination is structurally blocked.
Client-specific golden-question benchmarks. Accuracy published before and after each tune.
Tell us about your corpus and we'll send a 5-minute Loom in 48h showing exactly how a RAG system over your docs would perform — indexing strategy, citation quality, eval benchmarks. No commitment.
Or skip the form: email nova@fusionos.ca directly.
Full-build pricing: $5,997 fixed · 7 business days · full source included · 30-day warranty.