NOAN vs Build-your-own RAG
RAG and a fact layer answer different questions. A retrieval pipeline, chunking, embeddings, a vector database, and sync jobs, answers what do our documents say. A fact layer answers what has the company approved as true. RAG shines over large corpora where the answer might be anywhere. It cannot make a document true, current, or authorized; retrieval quality is not truth quality. NOAN is deliberately the opposite shape: a small, curated, verified set of operating facts with an approval gate, version history, and an API. Build RAG when your problem is search. Buy the fact layer when your problem is that agents act on wrong information. Serious agent stacks often end up with both.
Side by side
Competitor claims last verified 26 August 2026| Dimension | NOAN | Build-your-own RAG |
|---|---|---|
| What it is | The company brain and API: verified facts, tasks, contacts, notes, and assets behind one REST endpoint | A pipeline you assemble: chunking, embeddings, a vector store, retrieval logic, and sync from your sources |
| Source of truth | Approved, versioned facts with an owner; one source of truth for the whole company | Whatever made it into the index, at whatever freshness your sync achieves |
| Verification | Facts enter through a verify gate: a human approves before anything reads it as true | None inherent; a retrieved chunk may be a draft, an old deck, or a contradicting doc |
| API | Plain REST plus MCP, bearer keys, unlimited API keys on every plan | Whatever you build and maintain |
| Agents | Built for agents: facts to ground on, a task board to control them, any model | Provides context for agents; control plane, approvals, and CRM are separate builds |
| Auditability | Every fact versioned with full history and Time Travel; every agent action lands on the task board | Citations to retrieved chunks if you build them; no approval trail exists to cite |
| Pricing model | Whole-workspace plans from $99/month; unlimited keys, no per-agent or per-task metering | Vector DB, embedding calls, and sync infrastructure, plus the engineering time that dwarfs all three |
| Lock-in | Facts are plain text behind a REST API; one GET exports everything | You own it all, and you maintain it all |
When to choose Build-your-own RAG
- Large document corpora where answers hide in thousands of pages: support archives, research, contracts
- Search and question answering is the product, and ranking quality is worth tuning
- You have the engineering appetite to own chunking, sync, and evaluation forever
When to choose NOAN
- The facts that matter fit in a curated brain: positioning, pricing, policies, product, process, contacts
- Wrong answers are expensive: you need approval before truth, versions after it, and an audit trail always
- You would rather ship agents this week than build retrieval infrastructure this quarter
Common questions
Is NOAN a RAG system?
No. RAG retrieves passages from documents. NOAN serves discrete verified facts over a REST API; a GET returns the approved truth, no embeddings involved. Retrieval answers from likelihood; the fact layer answers from authority.
When is RAG the wrong choice for agents?
When the agent acts. Retrieval is probabilistic: the top chunk may be stale, a draft, or contradicted elsewhere. Fine for research. Dangerous for the agent quoting your price or your policy to a customer. Action needs an authoritative read, which is what a verify gate exists for.
Do teams use RAG and NOAN together?
Yes, and it is the sane architecture: RAG over the large corpus for research and recall, NOAN for the operating truths agents assert and act on. The agent searches one and obeys the other.
Sources: NOAN API spec · All comparisons
See the fact layer with your facts in it
Every plan includes the API, MCP, and unlimited keys. Start with one verified fact and build from there.