Your Knowledge.Your AI Expert.
One AI platform for your company: grounded answers from your knowledge, a team chat workspace and a model gateway, on one account.
01 Knowledge
Connect what you have already written
Point MITHUNAI at the content your organisation already maintains. It is fetched, extracted, split for retrieval and kept in step with the source, with the progress and the failures both visible rather than only the successes.
How MITHUNAI RAG connects your sources02 Grounded answers
Answers that show their work
A question goes to retrieval, retrieval assembles the evidence, and the answer is built from that evidence and checked against it. What arrives is an answer with its sources, or a clear statement that your content does not cover the question.
Read two real answers
03 MITHUNAI AI search visibility
See how AI search engines answer your buyers’ questions
How AI search engines answer your buyers’ questions, and whom they cite.
Beta. Not yet run against a real AI search engine.
What it does, and what is not yet proven04 MITHUNAI Team
MITHUNAI Team: work that waits for a person’s approval
Employees for support, IT, DevOps, marketing, sales and finance that act only with approval.
Beta. Access on request.
What it does, and what is not yet proven05 Surfaces
Every MITHUNAI product, on one account
MITHUNAI is a family of products on one platform: one account, one organisation boundary and one body of knowledge underneath all of them. They are not equally far along, and each one says where it stands. Signing in once and signing out once across every product is in beta.
How the products fit together- MITHUNAI RAGLiveFor support, documentation and developer teams
- MITHUNAI ChatLiveFor everyone in your organisation who wants to ask, draft and summarise
- MITHUNAI GatewayLiveFor platform teams that manage model providers
- MITHUNAI AI search visibilityBeta. Not yet run against a real AI search engine.For marketing teams
- MITHUNAI TeamBeta. Access on request.For support, IT, DevOps, marketing, sales and finance teams
What MITHUNAI connects to, and the products it answers through
Kinds of source it connects
Products, on one account
Every MITHUNAI product, on one account
Knowledge
Connect your documentation, repositories, help centres and files, and answer questions from them with citations, or a plain "I don't know" when the sources do not support an answer. Put it on your site with the Ask AI widget, call it over the HTTP API, or reach it from your editor through read-only MCP tools. Coverage gaps, Top questions and source analytics show what people ask and what is missing.
More about KnowledgeLive
AI search visibility
Asks AI search engines the questions your buyers ask, with their own web search, and records whether they name you or a competitor and which pages they cite.
More about AI search visibilityBeta. Not yet run against a real AI search engine.
AI employees
AI employees for Support, IT service desk, DevOps, Marketer, Sales and Finance work. Each one proposes what to do, a person approves, edits or rejects it, and every step is recorded.
More about AI employeesBeta. Access on request.
Gateway
One OpenAI-compatible endpoint in front of your model providers, with provider keys in an encrypted vault, routing and failover, and per-key usage and budgets for the traffic that goes through it. Chat sends its model calls through it; the RAG answer engine and Agents call providers with their own credentials.
More about GatewayLive
How MITHUNAI answers a question
Every query passes through verifiable retrieval before reaching a model.
- Grounded
- Every question goes to your corpus before it goes to a model. Retrieval assembles the passages that bear on it, and the answer has to be built from those.
- Cited
- The answer carries the passages it was built from, so the person reading it can check the source instead of trusting the system.
- Honest
- When those passages do not support an answer, there is none. Abstention is its own outcome, never an answer left empty.
Interactive Engine SimulatorClick a scenario to evaluateMITHUNAI ingests a GitHub repository through its GitHub connector. You give it the repository, a branch or tag, and the paths to include or exclude. Ingestion fetches that revision, extracts Markdown and source files, chunks them along their structure, and indexes the embeddings inside your organisation.
See a real answer, and a real “I don’t know”
Captured from the public playground on 30 October 2026. The playground answers only from MITHUNAI’s own documentation.
“How do I add the Ask AI widget to my website?”
The widget puts an assistant on your own website, and visitors who have never signed in can ask questions and get grounded answers with citations from an Ask AI launcher button [1]. An Owner, Administrator or Editor creates one embed per site by opening Integrations → Website widget, selecting New embed, entering a Name, choosing the Assistant that should answer, listing your site under Allowed origins, and selecting Create embed; the embed then appears with its Embed snippet containing its widget key [2]. Widget requests must be allowed by two allowlists: your embed’s own list and a deployment-wide list set by whoever operates your MITHUNAI deployment; both start empty, so you must ask your MITHUNAI administrator to add your site’s origin to the deployment-wide list [2]. Add the snippet to your site by selecting Copy beside the embed’s Embed snippet in Integrations → Website widget and pasting it unchanged before the closing </body> tag on every page that should show the widget [2].
- [1] Add an AI chat widget to your website, #add-an-ai-chat-widget-to-your-website (88% match)
- [2] Add an AI chat widget to your website, #set-it-up (89% match)
Answered from the sources listed with it.
“What is the price of the Business plan in euros?”
I don’t know based on the available knowledge.
No answer from your sources. This assistant answers only from the documentation behind it, and that documentation does not cover this. Rewording the question may find it.
How it works, from sign-in to a live assistant
Six steps, in the order you take them. Most of them take minutes of your time; the two waits are for a person to set up your organisation and for your content to index.
1Try the playground
Ask the public playground a question, with no account. It answers only from MITHUNAI’s own documentation and cites the page, or says the documentation does not cover it.
About a minute
Try the playground2Get access
Request access, or accept an invitation from a colleague. A person sets up your organisation and its first Owner; there is no instant sign-up.
A person reviews each request
Request access3Connect your knowledge
Sign in and add a documentation site, sitemap, GitHub repository or file. It indexes in the background, and each source shows how far it has got, or why it failed.
Minutes for a small site, longer for a large one
4Ask and check the sources
Point an assistant at that knowledge and ask it a real question. Every answer cites the passages it used, or says it does not know when your content does not cover it.
About 5 minutes
5Put it live
Paste one line to put the Ask AI widget on your website, call the HTTP API from your backend, or connect an editor through read-only MCP tools.
About 10 minutes
6Invite your team
An Owner or Administrator adds colleagues from Settings, each with a role.
Limit: E-mailed invitations are in beta: a real invitation has not yet been tried.
About a minute per person
After that, the same account opens
Each one works on the same organisation and knowledge, and each says where it stands.
MITHUNAI Chat
Threads with your knowledge in every one.
Live
MITHUNAI Team
AI employees that propose work and wait for a person to approve it.
Beta. Access on request.
MITHUNAI Gateway
One endpoint in front of your model providers, for administrators.
Live. It admits platform administrators, and an organisation’s owners and administrators where a deployment allows it.
Who uses it, and how a question becomes a cited answer.
An admin connects the sources and runs the workspace. Visitors ask through the widget on your site; developers through the HTTP API or read-only MCP tools. Every way in ends in the same place: an answer built from your passages, with citations, or a plain refusal to guess.
Grounded answers from your own knowledge, a chat workspace for your team and one model gateway, on one account.
A 30-minute walkthrough on your own use case: connect a source, ask it questions, check the citations and see what it does when the answer is not there. Or ask the public playground now, with no account.