Vector Index Builder
Turn docs, SOPs, and “tribal knowledge” into a searchable vector pack (RAG-ready).
Who this is for
Marketers, SEOs, operators, founders, and dev teams who need an LLM to answer questions using your internal knowledge: docs, onboarding, playbooks, SOPs, support macros, checklists.
Most teams already have the info — it’s just scattered across Notion, Google Docs, tickets, Slack, and random markdown files.
Why this matters for LLMs + RAG
LLMs don’t “remember” private knowledge unless you provide it at query time. RAG retrieves the best chunks and injects them into the prompt. Better chunking + metadata = cleaner retrieval = better answers.
What this tool does
- Paste content (docs, policies, FAQs, SOPs, notes)
- Chunk it into retrieval-friendly sections (keeps context)
- Attach metadata (title, source, category, tags)
- Build embeddings + store in local Chroma
- Test retrieval and inspect what chunks come back
What you get
A zip with your manifest, chunks, and a Chroma index folder — ready for a server-side search endpoint or a RAG assistant.