Docubix
Summary
Site search fails the moment someone phrases a question differently than your doc headers — which is most of the time. Docubix replaces that lookup-and-hope loop with a cited-answer assistant built on top of your own uploaded documents.
The core workflow is upload, configure, integrate: drop in PDFs, DOCX, TXT, or Markdown files, write a system prompt, tune retrieval settings, and call a single REST endpoint from your app. Every answer surfaces the exact document and page it pulled from, so users can verify rather than trust. The free tier caps at one knowledge base, 20 documents, and 100 queries per month — enough to validate a use case, not enough to run a real support operation. Teams that outgrow those limits move to the paid tier, and teams that need multiple knowledge bases on free hit that wall immediately. There is no self-hosted option, so your documents live on Docubix infrastructure regardless of your compliance posture.
Bottom line: Pick Docubix to ship a cited-answer assistant over your help center docs in an afternoon — but if your legal team requires on-premises deployment or you need more than one knowledge base without paying, you are looking at a different architecture from day one.
Pricing Plans
Subscription- Price
- $79 / month
- Free Tier
- 1 knowledge base, 20 documents, 100 queries/month, 0.25 GB storage
Free
For individuals exploring document AI
- 1 knowledge base
- Up to 20 documents
- 100 queries / month
- 0.25 GB storage
- API access
- Citations on every answer
Pro
For teams shipping AI to production
- 10 knowledge bases
- Up to 1,000 documents
- 3,000 queries / month
- 10 GB storage
- API access
- Citations on every answer
View full pricing on docubix.com →
Pricing may have changed since last verified. Check the official site for current plans.
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Pros
Sign in to edit- Citations on every answer link back to the exact document and page, so users can verify claims instead of trusting a black box — which means the assistant is deployable in support and onboarding contexts where an unverified wrong answer creates a real problem.
- Automatic chunking and embedding on upload, so you are not hand-tuning a preprocessing pipeline before you can test whether the assistant actually works.
- Provider-agnostic model configuration described in setup, so you are not locked into a single LLM vendor if costs or quality requirements shift.
- A single REST endpoint handles chat, history, and search, which means you can wire a working assistant into an existing React, Next.js, or Python backend without building a custom integration layer.
- Separate knowledge bases and API keys per project, so product docs and the internal HR handbook do not share a retrieval index or a permission boundary.
Cons
Sign in to edit- The free tier caps at one knowledge base and 20 documents: a team validating more than one use case simultaneously hits that ceiling on day one, with no way to expand without moving to a paid tier.
- There is no self-hosted or bring-your-own-infrastructure option — documents are processed and stored on Docubix servers. Teams in regulated industries or with data-residency policies cannot use this at all, and the workaround is switching to an open-source RAG stack they run themselves.
- The API surface is intentionally minimal: one chat endpoint with no documented hooks for custom retrieval logic, re-ranking, or multi-index federation. Teams whose use case requires branching retrieval strategies or hybrid search configurations will reach the ceiling of what the platform exposes and either accept the constraint or move to a framework like LlamaIndex or LangChain where retrieval is fully configurable.
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About
- API Available
- Yes
- Self-Hosted
- No
- Last Updated
- 2026-07-07T10:29:36.613Z
Best For
Who it's for
- Teams needing cited answers from uploaded documents
- Developers integrating document chat via REST API
- Product documentation and support knowledge bases
What it does well
- Documentation assistant replacing site search
- Internal company handbook and wiki queries
- New-hire onboarding with cited handbook sections
- Customer support ticket deflection from help-center content
Integrations
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Frequently Asked Questions
- Is Docubix free?
- Docubix has a permanent free tier alongside paid upgrades (paid plans from $79 / month). You can keep using a baseline version indefinitely without paying.
- Is Docubix open source?
- No — Docubix is a closed-source tool. Source code is not publicly available.
- Does Docubix have an API?
- Yes. Docubix exposes a developer API. See the official documentation at https://docubix.com for details.
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Curated lists that include this category
Docubix is a hosted RAG platform that turns uploaded document collections into a queryable chat assistant with citations on every answer. The workflow has three steps: upload files (PDF, DOCX, TXT, Markdown), configure a system prompt and retrieval settings through the dashboard, then call the REST API from any application. The vendor states that chunking, embedding, and indexing happen automatically after upload, with no ML experience required to get a working assistant. Streaming responses are supported, so answers render token-by-token rather than arriving as a single delayed payload.
The differentiating feature is mandatory citations. Unlike generic chat completions that synthesize an answer and leave you guessing about the source, every Docubix response links back to the specific document and page or section the content came from. For support and onboarding use cases — where a wrong answer has a real cost — this auditability is the functional difference between a demo and something you can put in front of customers or new hires.
Docubix fits teams that need to ship a document-backed assistant quickly and do not require on-premises infrastructure. The API surface is intentionally narrow: one endpoint handles chat, history, and search, which means integration is fast but customization past that contract requires building on top rather than inside. The free tier restricts usage to one knowledge base, 20 documents, and 100 queries per month — adequate for a proof of concept, not for a production support channel. Teams running multiple products, each needing a separate assistant, will exhaust free-tier limits immediately and face a binary choice: pay or rebuild elsewhere. There is no self-hosted option documented on the vendor site, which is a hard stop for teams with data-residency requirements.
The REST API accepts an API key and a message string and returns an answer with citations in a single JSON payload. The vendor’s code example shows a fetch call any JavaScript or Python environment can replicate in minutes. Analytics surface query patterns and document citation frequency, giving content teams signal on where documentation gaps cause the assistant to fall short.