NexusRAG is a retrieval engine for grounded AI systems. Teams use it when ChatGPT and Claude stop being enough — they need visible evidence, controllable retrieval, plug-in APIs, and a clean path from shared evaluation to private rollout.
2 free queries on the hosted API · No account required
How NexusRAG processes a query
Natural-language intent enters the workspace.
Dense vectors and BM25 surface the strongest context.
Filenames, scored passages, and source metadata are preserved.
The model answers with citations or abstains when evidence is thin.
How it works
Upload the source material, ask a precise question, inspect the cited evidence, and decide whether the product fits your team before any rollout effort.
Bring PDFs, DOCX files, Markdown, TXT, HTML, CSV, or JSON into one retrieval layer designed for repeated operational use.
Dense vectors and BM25 stay in the same loop so semantic intent and exact language survive retrieval together.
NexusRAG returns a readable answer, cited passages, source names, and the evidence context that explains why it was chosen.
Evaluate the product the way teams actually buy it
Evaluate answer quality in the hosted mode, then switch the exact same interface to your own API when your team is ready.
Start public
Use the shared NexusRAG API to test upload, retrieval, evidence, and answer quality without any setup.
Move private
Point the same workspace at your own NexusRAG runtime for private data, unlimited usage, and your own controls.
Why teams choose NexusRAG
NexusRAG is for teams that have outgrown generic document chat. It keeps the retrieval path visible, lets you plug the system into real products, and gives teams a grounded interface they can trust.
Use NexusRAG as infrastructure inside your own app, not as a closed chat tab with no system-level hooks.
Keep hybrid retrieval, reranking, evidence visibility, and answer grounding inside a pipeline you can actually tune.
Show citations, preserve review context, and abstain when evidence is thin instead of hiding uncertainty behind polished text.
Who should use it
The strongest fit is teams saying: “ChatGPT is not enough for what we are building.”
Teams building AI products who need a controllable retrieval engine, not another black-box assistant.
Startups, operations teams, support orgs, and security-minded groups that need private knowledge plugged into real workflows.
Anyone who cares about evidence, source visibility, ranking quality, and why the answer was chosen.
Why not just use ChatGPT or Claude?
NexusRAG sits between open-source chaos and closed SaaS tools: easier than building from scratch, but far more controllable than a black-box assistant.