NexusRAG turns documents into a production-grade knowledge workspace with hybrid retrieval, citation-backed answers, and a deployment shape real teams can operate: Cloudflare Pages on the edge, Render for the live API, and Neon pgvector for the evidence layer.
How to use
Bring in PDFs, DOCX, Markdown, and text. NexusRAG indexes them into a searchable evidence layer instead of a loose chat dump.
Query policies, product docs, client material, or research and get retrieval-backed answers designed for follow-up, not guesswork.
Every answer is paired with source excerpts, document names, and relevance context so teams can audit what the system used.
Use our live hosted API for up to 2 questions and see the full workflow end to end.
Point the same interface at your own NexusRAG API endpoint and key for unlimited usage on your own infrastructure.
NexusRAG is designed to reduce follow-up time after the answer arrives. The product keeps evidence, architecture, and operational control close to the query instead of hiding them behind a generic chat facade.
PDF, DOCX, Markdown, and text are converted into chunked evidence that stays searchable instead of living in disconnected uploads.
Dense vector search and lexical search work together so the system can handle both semantic intent and exact phrasing.
Answer text is paired with source excerpts, document names, and relevance signals so review happens in context, not on faith.
Upload, ask, inspect, refine, and re-run in one interface built for repeated operational use instead of a one-shot demo prompt.
The platform is designed around retrieval quality, traceability, and observability so teams can improve quality with evidence.
Start on the hosted trial, then point the same UI at your own NexusRAG API deployment for unlimited usage and private operations.
This live deployment already runs across Cloudflare Pages, Render, and Neon pgvector, so the architecture is practical, not theoretical.
Architecture
The live deployment is already split the way serious teams expect: edge-hosted frontend, dedicated backend API, and a managed vector-capable Postgres layer. That means the product story, deployment story, and recruiter story all point to the same system.
Static Next.js delivery keeps the workspace fast, globally accessible, and free of backend secrets in the browser.
FastAPI handles ingestion, retrieval, answer generation, and usage control for the hosted public experience.
Document metadata, vector search, and retrieval state live in managed Postgres so the data plane is durable and inspectable.
Why NexusRAG
Source transparency
NexusRAG
Inline citations, evidence panel, and source excerpts in the same workspace.
Generic alternative
Answers often arrive as plain text with no clear audit trail back to source chunks.
Operational control
NexusRAG
Hosted evaluation mode plus a direct path to your own NexusRAG API deployment.
Generic alternative
Many demos stop at a shared playground and offer no migration path to controlled usage.
Architecture
NexusRAG
Frontend, backend, and vector store are deployed on distinct real-world services.
Generic alternative
Single-stack prototypes often hide where retrieval, storage, and inference actually happen.
Decision support
NexusRAG
Designed for grounded retrieval and evidence review before action.
Generic alternative
Optimized for impression, not for documentation-heavy workflows that need defensible answers.
Ready to launch
NexusRAG is built for a serious evaluation path. Reviewers can use the hosted public experience immediately, while teams that want ongoing usage can bring their own API endpoint and keep the same interface, evidence model, and operating rhythm.
2 questions on the managed NexusRAG API so candidates, customers, and evaluators can see the product live immediately.
Connect your own NexusRAG API endpoint and access key for unlimited usage, private data boundaries, and your own operational controls.
Contact
Founder, Fundamental Labs
If you want a walkthrough, deployment discussion, or a private API setup for your team, reach out directly and we can take it from evaluation to production.