Documents and notes decision
Tettra
A single engineer can build a usable RAG-backed internal Q&A and Slack bot using open-source components in several weeks, but reproducing Tettra's polish, enterprise integrations, analytics, and managed reliability at scale would be expensive and time-consuming.
Visit website↗Open-source builds that already do this
Every project below is open source and already does this job today. Fork one, self-host it, or take the parts you need — the build prompt further down assumes an empty file, and this is the shortcut past that. Licences differ; check the one on each card before you ship.
What a replacement has to do
- Answer internal questions by indexing company docs and returning RAG-backed answers via a Slack bot and a web UI.
What it still won’t have
- Polished, production-grade UI and onboarding flows
- Enterprise features (SSO/SCIM, prioritized support, custom onboarding)
- Built-in analytics and usage reporting
- Wide integrations catalogue and managed Slack app experience
- SLA-backed uptime and hosted infrastructure/backup guarantees
What remains hard
- Product polish and ongoing maintenance
First-year cost
Keep paying
Paying is—cheaper in year one.
On cash alone, building overtakes the subscription at 8 seats.
Money you would actually spend
Time you would spend
—
What you would spend
What we assumed
The verdict above measures whether you could build it. This one is only about money.
Runnable build prompt
Build a minimal self-hosted AI internal knowledge base using: Postgres (data), Python FastAPI backend, React UI, FAISS vector store, and OpenAI-compatible APIs for embeddings and generation. Scope: page editor with versioning, importers for Google Docs and PDFs, embedding pipeline, vector search and RAG answer endpoint (with source snippets), Slack bot that accepts questions and returns RAG answers (and can create page requests), basic permissions (admins, editors, read-only), HTML export. Out of scope: SSO/SCIM, multi-tenant billing, enterprise onboarding, advanced analytics dashboards. Include error handling, retries for external API calls, and unit/integration tests for ingestion, retrieval, and Slack integration.
How we checked
How the score was reached
- Partly verdict base52
- An open-source build was found+5
- 5 cited sources+3
- Price verified on pricing page+3
- 3/3 assessment runs agreed+4
- Evidence score67
The base comes from the verdict. Everything under it is a check that either happened or did not, and each one is a fact frozen in this record rather than a judgement made at render time — so the same evidence always produces the same number.
How scoring works →Cited sources · 5
Every page the run actually retrieved.
- official productTettra | AI Internal Knowledge Base & Knowledge Management
- official pricingTettra Pricing | Top Knowledge Management Software
- official docsKnowledge Management Software | Tettra Feature Overview
- open sourceoutline/outline
- open sourcelabring/FastGPT
Integrity checks
What held up, and what did not.
