RAG Knowledge Base Demo

RAG Knowledge Base over PDFs and Confluence

Your internal docs become a searchable, cite-able knowledge base. Claude answers questions with exact passages highlighted.

Try the live demo →
Watch the 60-second Loom

How it works

1. Ingest from anywhere

Drag-drop PDFs plus OAuth into Notion and Confluence. Unstructured.io handles parsing; content is chunked and embedded.

2. Hybrid retrieval

Semantic (pgvector) + BM25 keyword search with Cohere rerank on top — so obscure acronyms and numbered clauses still win.

3. Answer with citations

Chat UI returns answers with inline citation links that deep-link to the exact source paragraph. Admin panel exposes failed queries.

60-second Loom

45-second flow: ingest 30 PDFs → ask a policy question → see the answer with 3 citations → click a citation → jump to the exact paragraph.


Free build spec

Get the full build spec PDF

One-page PDF with the architecture, the tech stack, the timeline (2–3 weeks), and the investment range ($9,990 – $25,000). Sent to your inbox in under a minute.


Who it’s for

Legal, scientific R&D, and operations teams with 500+ internal documents who need a cite-anchored answer surface that employees actually trust.

Tech under the hood

Next.js 15pgvectorCohere RerankClaude Sonnet 4.6Notion APIConfluence APIUnstructured.io

Frequently asked questions

How is this different from ChatGPT with file upload?

Hybrid retrieval (semantic + BM25 keyword) plus a Cohere rerank step means domain-specific acronyms, numbered clauses, and low-frequency terms still surface. Citations deep-link to the exact paragraph — not a whole PDF.

What sources can you ingest?

PDF (scanned + text), Markdown, HTML, DOCX, CSV, Confluence, Notion, Google Drive, Dropbox, S3, and any HTTP(S) endpoint. Incremental re-indexing keeps changes fresh.

Is it secure for internal docs?

Yes. Deployable in your VPC or ours. Row-level security via Supabase RLS ensures users only see content they have source-system permissions for. SOC 2 path available.

How much does it cost to run?

For 10k documents and 5k queries/month: ~$90 for pgvector hosting, ~$45 for Claude inference with prompt caching, ~$25 for reranking — under $200 all-in on typical usage.

Want one of these in your business?

We’ll scope, build, and hand off a production-ready system in 3–4 weeks.

Book a Strategy Call



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