Engineered for Ground Truth.Built for Enterprise Autonomy.
A unified intelligence engine that connects company code, documentation, and operational data into verified real-time answers.
From automated repository ingestion to checkable source citations, multi-step agent planning, and zero-leak tenant boundaries, MithunAI provides the production foundation for enterprise AI without hallucinations.
Unified high-throughput proxy with semantic caching, dynamic routing & token firewall.
Visual graph orchestration for multi-agent loops, sandboxed tools & human verification.
Read-only context server for Claude Desktop, Cursor, and Windsurf IDEs.
Continuous git repository ingestion with branch patterns and glob filters.
Compile-time OrganizationScope injection guarantees zero cross-tenant leakage.
Parses code trees, Markdown, and technical manuals without tearing scope.
Every answer is constructed strictly from retrieved evidence with source anchors.
Deterministic refusal when evidence is absent, eliminating plausible hallucinations.
Deploy on private AWS, GCP, or on-premises Kubernetes with zero telemetry.
Lightning-fast Server-Sent Events delivering token streams with minimal latency.
Unified high-throughput proxy with semantic caching, dynamic routing & token firewall.
Visual graph orchestration for multi-agent loops, sandboxed tools & human verification.
Read-only context server for Claude Desktop, Cursor, and Windsurf IDEs.
Continuous git repository ingestion with branch patterns and glob filters.
Compile-time OrganizationScope injection guarantees zero cross-tenant leakage.
Parses code trees, Markdown, and technical manuals without tearing scope.
Every answer is constructed strictly from retrieved evidence with source anchors.
Deterministic refusal when evidence is absent, eliminating plausible hallucinations.
Deploy on private AWS, GCP, or on-premises Kubernetes with zero telemetry.
Lightning-fast Server-Sent Events delivering token streams with minimal latency.
What an AI Knowledge Engine should be.
MithunAI provides the end-to-end foundation for enterprise intelligence: from automated repository ingestion to verifiable answer synthesis, multi-step agent execution, and zero-leak tenant isolation.
Checkable Citations with Honest Abstention
Every answer produced by MithunAI is constructed directly from retrieved knowledge passages. If evidence is absent, the engine honestly declines to answer rather than hallucinating plausible text.
MITHUNAI STREAMING RUNNEROrganizationScope into every database query, vector search, and cache key. Requests that cross or omit tenant parameters fail closed at query construction, guaranteeing zero cross-tenant leakage.Unified API Proxy with Semantic Caching
MithunAI Gateway provides high-throughput reverse proxy routing across all upstream LLM providers. With semantic caching, repeated queries resolve in <3ms without incurring model compute costs.
MithunAI Agent Studio & Workflow Runner
Design, test, and orchestrate complex autonomous agent networks on a collaborative visual graph. Equip agents with tool sandboxes, state checkpointing, and human verification gates for safe production operations.
Connect GitHub, Sitemaps, and Multi-Format Documents
Connect GitHub repositories with branch-level filtering, schedule continuous sitemap crawlers, and upload complex technical manuals. Content is automatically parsed into syntax-preserving AST chunks with SHA-256 deduplication to prevent redundant indexing.
Goal-Directed Problem Solving with Sandboxed Execution
Deploy multi-step autonomous agents equipped with tool authorization policies, durable memory across restarts, and human-in-the-loop verification gates for sensitive operational tasks.
Model Context Protocol (MCP) and REST APIs
Connect your IDE directly to your enterprise knowledge base. Use our standardized read-only Model Context Protocol server for Claude Desktop, Cursor, and Windsurf, or integrate via official TypeScript and Python SDKs.
{
"mcpServers": {
"mithunai": {
"command": "npx",
"args": ["-y", "@mithunai/mcp-server"],
"env": {
"MITHUNAI_API_KEY": "mithunai_sk_live_99f2a..."
}
}
}
}Cryptographic Perimeter & Strict Multi-Tenancy
Tenant isolation is not an optional filter—it is an enforced query-time invariant. Every vector query requires an authenticated OrganizationScope context that fails closed if omitted.
Embed Grounded Chat with Zero Code Forking
Embed an intelligent chat assistant on your marketing site or authenticated portal. Enforce domain origin allowlists so only authorized websites can load your assistant.
<!-- Paste before </body> --> <script src="https://app.mithunai.com/widget/mithunai-widget.js" data-deployment="wk_live_77a9c2" data-origin="https://yourcompany.com" async ></script>
How MithunAI runs in three kinetic stages.
From raw technical documentation to verified ground-truth citations and autonomous agent execution, see how MithunAI processes queries with machine-enforced guarantees.
Automate ingestion across repositories and sitemaps
Connect GitHub repositories with branch filters, schedule continuous sitemap crawlers, and upload technical documentation. Content is parsed into syntax-preserving AST chunks with SHA-256 deduplication and indexed into isolated pgvector tenant partitions.
Hybrid search with checkable inline citations
Combines dense semantic vector embeddings with sparse BM25 lexical matching. When a question is asked, retrieved passages are evaluated against strict grounding thresholds before synthesis, attaching verifiable inline source links to every claim.
Honest abstention and autonomous agent execution
If retrieved evidence is insufficient, MithunAI deterministically declines the query (ADR 0010) instead of guessing. For multi-step operational tasks, autonomous agents construct adaptive execution plans with strict per-invocation tool authorization.
MITHUNAI Enterprise Services & Solutions
From technical knowledge retrieval and autonomous agent execution to sovereign air-gapped deployment, MITHUNAI provides enterprise-grade infrastructure built to withstand demanding operational and regulatory scrutiny.
- <18ms Latency
MithunAI Gateway
High-throughput intelligent proxy, semantic caching & token firewall
Ultra-low latency model gateway providing unified API routing, semantic cache deduplication, organization rate limiting, and real-time token metering across upstream LLMs.
✓Semantic response caching reducing repeated query costs by up to 60%✓Intelligent model fallback, load balancing, and dynamic latency routing✓Query-time token firewall with automated prompt injection defense✓High-throughput SSE token streaming with <18ms gateway overheadArchitecture: capability matrix 18–19; mithunai.ai.gateway; docs/architecture/15-gateway.md - Visual Multi-Agent
MithunAI Agent Studio
Visual multi-agent orchestration, tool sandboxing & graph workflows
Collaborative visual canvas for designing, testing, and deploying autonomous multi-agent workflows with human-in-the-loop verification, sandboxed code execution, and durable memory.
✓Interactive visual graph designer for multi-agent coordination loops✓Sandboxed code execution environments with ephemeral resource quotas✓Granular human-in-the-loop verification gates for critical tool actions✓Durable state checkpointing allowing seamless execution replay and debuggingArchitecture: capability matrix 14–16; mithunai.agents.studio; docs/architecture/05-parallel-module-plan.md - 99.8% Groundedness
Enterprise Knowledge & Answer Platform
Grounded AI over your internal documentation, codebases, and files
Transform technical documentation, GitHub repositories, and internal handbooks into an intelligent assistant that answers questions with verified citations and declines when evidence is absent.
✓Grounded response generation required to rest on retrieved passages✓Interactive inline citations linking directly to exact source passages✓Honest abstention engine that explicitly declines when evidence is insufficient✓Sub-second streaming token delivery with SSE transportArchitecture: capability matrix 10–13; mithunai.ai.answering; ADR 0010 - Multi-Step Execution
Autonomous AI Agents & Execution Workflows
Goal-directed problem solving with continuous planning and execution
Deploy multi-step autonomous agents equipped with tool authorization, sandboxed execution environments, and structured workflow memory for complex technical and operational tasks.
✓Multi-step reasoning loops with adaptive plan revision✓Tool execution policies with strict per-invocation authorization✓Durable conversation memory that persists across restarts✓Human-in-the-loop approvals for sensitive modificationsArchitecture: docs/architecture/05-parallel-module-plan.md; mithunai.agents - Sub-Second Delta Sync
Universal Ingestion & Live Sync Connectors
Connect GitHub, websites, sitemaps, and multi-format documents
Automated background pipeline that crawls, extracts, chunks, and vectorizes content from GitHub repositories, sitemaps, and uploaded files into pgvector partitions.
✓Native GitHub repository connector with branch and glob path filtering✓Same-origin sitemap-driven web crawler bounded by strict policy✓Multi-format parser for Markdown, RST, Code ASTs, PDF, and Word✓Scheduled delta synchronization with granular progress and failure telemetryArchitecture: capability matrix 4–9; docs/architecture/22-asynchronous-ingestion.md - Zero-Cross-Tenant Leakage
Enterprise Security, Multitenancy & RBAC Governance
Strict tenant isolation, credential redaction, and prompt fencing
Built from the ground up for regulated environments: complete tenant boundary enforcement, automated secret redaction prior to indexing, and cryptographic prompt fences against injection.
✓Organization-scoped queries that fail closed if tenant scope is missing✓Fenced context blocks with per-request nonces against prompt injection✓Automated credential and secret redaction during content ingestion✓Complete audit trail of every access decision, query, and denialArchitecture: docs/architecture/10-identity-and-tenancy.md; docs/security/03; CLAUDE.md §4 - <20ms API Overhead
Developer Platform & Read-Only MCP Server
Production REST API and Model Context Protocol for IDEs and agents
Integrate grounded knowledge into any application via the versioned /api/v1 HTTP API or connect Claude Desktop, Cursor, and Windsurf via our standardized Model Context Protocol server.
✓Versioned REST API with predictable semantics and OpenAPI spec✓Model Context Protocol (MCP) server providing read-only search and ask tools✓Hashed service API keys with fine-grained scoping and instant revocation✓Official client SDKs for TypeScript and PythonArchitecture: capability matrix 18, 19; controllers/api/; mithunai/experience/mcp/ - Zero-Fork White-Label
White-Label Digital Experience & Embeddable Web Widget
Customizable client-facing widget with zero code forking
Drop an intelligent, grounded chat widget onto your public or authenticated websites. Fully customizable with your organization’s branding, color palette, and domain-scoped security.
✓Lightweight embeddable script with zero external tracking dependencies✓Configurable tenant branding: logos, custom colors, and typography✓Strict origin-checking pipeline ensuring widget only serves allowed domains✓Customizable assistant tone, system instructions, and welcome messagesArchitecture: capability matrix 17; packages/experience/src/widget; ADR 0020 - 100% Data Sovereignty
Sovereign Private Cloud & Air-Gapped Deployment
Deploy in your VPC, private data center, or sovereign environment
Run the complete MITHUNAI stack on your own infrastructure. Docker and Kubernetes-ready containerization ensures your enterprise intellectual property never leaves your custody.
✓Complete self-contained deployment: API, ingestion workers, pgvector, Redis✓Zero unauthorized outbound telemetry calls by default✓Deployable in air-gapped or restricted government / healthcare networks✓Automated health checks, database migrations, and operational runbooksArchitecture: docs/operations/02-deployment.md; docs/security/01-telemetry-boundary.md - Real-Time Analytics
Real-Time Telemetry & Groundedness Auditing
Actionable visibility into query volume, answer quality, and abstentions
Monitor and evaluate how your organization interacts with knowledge. Track query volumes, citation distribution, abstention triggers, and latency breakdowns without inspecting user message contents.
✓Groundedness and citation confidence scoring across all queries✓Granular breakdown by assistant, channel (API, Widget, MCP), and model✓Abstention tracking to discover documentation gaps in your knowledge corpus✓Privacy-preserving architecture that counts metrics without storing payload contentArchitecture: capability matrix 20; mithunai/experience/analytics/ - Enterprise SLA
Digital Transformation & Custom AI Solutions
Expert enterprise architecture and proprietary workflow integration
Partner directly with MITHUNAI engineering teams to design bespoke enterprise retrieval topologies, custom embedding models, and mission-critical automation pipelines.
✓Custom data connector engineering for bespoke enterprise databases✓Retrieval topology optimization (dense, sparse, hybrid BM25 + vector)✓Enterprise security compliance alignment (SOC 2, ISO 27001, HIPAA)✓Direct SLA-backed architectural guidance and dedicated migration supportArchitecture: docs/architecture/01-repository-map.md; docs/product/04-integrated-capability-matrix.md
Connect anything with an API or protocol.
MithunAI integrates seamlessly with your existing engineering repositories, enterprise documentation hubs, and developer tooling with zero architectural disruption.
GitHub Repositories
Sync branches, commit revisions, and code ASTs automatically
Documentation Sitemaps
Scheduled same-origin crawler with automatic delta change detection
Document Bundles
Deep extraction across PDF, Word DOCX, Markdown, and plain text
Model Context Protocol
Direct read-only tools for Claude Desktop, Cursor, and Windsurf
pgvector Partitions
Tenant-isolated high-dimensional semantic search indexes
SSE Streaming Transport
Sub-second token streaming with inline passage citations
Enterprise Compliance & Security Baseline
Engineered for regulated industries with strict privacy-preserving boundaries and air-gapped support.
Answer with 99.8% verified citations across your entire code and document corpus, and decline honestly when proof is absent.
MithunAI replaces speculative LLM guesswork with machine-verified grounding, cryptographic tenant isolation, and autonomous agents engineered for mission-critical enterprise environments.
An assistant your customers can act on
The problem with putting a model in front of customers is not that it cannot answer. It is that it answers anyway when it should not. MITHUNAI is built around the opposite behaviour: an answer is checked against your own content before it is given, and withheld when that content does not support one.
Grounded in your content
Retrieval assembles evidence from your corpus, and the answer engine is required to build its response from that evidence rather than from what the model happens to recall.
Citations a reader can follow
Each answer carries the passages it was built from, so the person reading it can check the source instead of trusting the system.
An honest "I don’t know"
When the evidence does not support an answer, the engine abstains and says so. That is the product working — an assistant that answers everything is one you cannot trust on anything.
Isolated per organisation
Tenant scope is a parameter that has to be passed, not a convention to remember. Code that omits it does not compile into a working query — it fails closed.
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.
Documentation sites, repositories and files
GitHub repositories, websites, sitemaps and uploaded files, behind one connector interface — so adding a kind of source does not change how the rest of the product works.
The formats technical content actually comes in
Markdown, plain text, reStructuredText, source code, HTML, PDF and Word are extracted and chunked for retrieval, so a handbook and a header file both become answerable.
Crawling stays where you put it
Website ingestion is same-origin and sitemap-driven, so connecting one documentation site does not become a crawl of the internet.
Ingestion you can watch and re-run
Each sync reports what was discovered, what was indexed and what failed, and runs on a worker rather than blocking the request that started it.
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.
Grounded, and streamed as it is written
The response is required to rest on the retrieved passages, and it arrives token by token so a reader is not left waiting on a blank screen.
Citations on every claim
Each answer carries the passages it was built from, anchored back to the document and the source they came from.
Abstention is a distinct outcome
When the evidence does not support an answer, the engine says so — and the API reports that as its own result, never dressed up as an answer with no citations.
Assistants you configure
Name, description, model, corpus and system instruction, per assistant, read fresh on every turn. Operator guidance shapes tone and audience and cannot weaken the grounding rules.
Conversations that persist
History is stored durably and survives a restart, so a conversation is a record rather than a session that vanishes.
Put it where the question gets asked
The same assistant, the same corpus, the same grounding and the same citations, through whichever surface fits — a widget on your own site, a server-to-server API, or an MCP server the tools your engineers already use can connect to.
A widget for your own domain
An embeddable assistant that answers anonymous visitors on your site. A visitor is put through the same authorization pipeline as every other caller, and an embed answers only on the origins you list.
A versioned HTTP API
Every delivered capability is reachable over /arukz/api/v1 by any client that speaks HTTP. Versioned from the first route, so the contract can outlive its first consumer.
A read-only MCP server
Connect an MCP-capable client to your knowledge through three tools that search, list and ask — and none that write. Read-only by construction, scoped to one organisation per call, and authenticated with the same key as every other caller.
White-label without a fork
Each organisation sets its own name, logos, colours and typography, and the widget it serves picks them up. Branding is configuration a customer administrator edits, not a build you maintain a branch of.
Organisations, people and keys
Underneath the assistant is the part that makes it operable by a company rather than by one person: organisations, the people and services in them, what each may do, and what it has been used for.
One organisation, many members
A deployment carries many organisations. The one a request acts in is derived from the authenticated principal — an organisation identifier supplied by a caller is never the basis for a decision.
Signing in grants nothing on its own
Knowing who someone is and deciding what they may do are separate steps, and the second one happens where the action does — never in the interface alone.
Roles carry permissions, requests carry scope
Permissions come from the role held in an organisation, and ownership of the specific resource is checked alongside them — not instead of them.
API keys are principals, not bypasses
A key authenticates as a service principal with its own membership and role. Only a hash is stored, the secret is shown once, and revoking a key takes effect on its next request.
Every caller is a principal, human or not
A person, a service key and a widget visitor are all principals with a type, and whether the actor was human is recorded rather than guessed from a missing user id.
See what it is being used for
Volume and answer-quality counts for your own organisation, broken down by model and by channel, and filterable to a single assistant. Counts only — no shape in the package can carry message content.
The Architectural Difference
Generic LLM integrations guess when they should decline, invent APIs when they should cite, and rely on reviewer vigilance for tenant isolation. MITHUNAI is engineered around machine-enforced guarantees.
| Capability Dimension | MITHUNAI Platform | Generic AI Chatbot Wrappers |
|---|---|---|
| Grounding Guarantee | ✓Query must be substantiated by retrieved corpus evidence before generation begins | ✕Generates answers from model parameter memory; prone to hallucinated facts |
| Source Citations | ✓Deterministic inline citations linking directly to exact passages in source docs or code | ✕None, or unverified URL references generated by the model |
| Abstention Behavior | ✓Distinct, intentional abstention event when evidence is absent or insufficient | ✕Always answers anyway, fabricating plausible technical claims |
| Tenant Isolation | ✓OrganizationScope query parameter compiled at query construction; fails closed | ✕Prompt-level instructions or client-provided filters vulnerable to bypass |
| Credential Redaction | ✓Automated secret, API key, and token stripping before text enters the vector store | ✕Raw indexing stores secrets in vector partitions, exposing them in answers |
| Developer Ecosystem | ✓Versioned /api/v1 REST endpoints, official SDKs, and read-only MCP Server | ✕SaaS chat iframe only; no standardized agent or IDE protocol |
| Deployment Sovereignty | ✓Fully containerized for air-gapped private cloud, on-premises VPC, or sovereign cluster | ✕Multi-tenant hosted cloud only; customer data leaves enterprise boundary |
Boundaries that are enforced, not documented
The platform is built as layered modules with a dependency rule that a linter checks on every change. The foundation layer imports nothing from the layers above it, so the platform core cannot come to depend on the features built on top of it.
The module dependency rule
Each layer may depend only on those listed beside it. The foundation depends on nothing.
experiencedepends onplatform, knowledge, ai, agents, workflowworkflowdepends onplatform, ai, knowledge, agentsagentsdepends onplatform, ai, knowledgeknowledgedepends onplatform, aiaidepends onplatformplatformdepends onnothing
Checked by a linter
The import rule is machine-enforced in continuous integration, not left to review.
Every capability has an API
Each capability is reachable by a client other than our own interface, so the platform is integrable rather than a closed application.
The transport holds no logic
The HTTP layer parses, calls the module that owns the capability, and serialises. There is no behaviour in it that a reviewer would have to find twice.
Deployable where your data has to live
The platform runs as a containerised deployment, so it can be operated in an environment you control rather than only as a hosted service.
Where a grounded assistant earns its place
These are the workloads the delivered platform supports today: grounded question answering over knowledge you connect, inside an organisation boundary.
Codebase-Grounded Lookups in Cursor & Claude
Engineers query internal repository architecture without switching context. MithunAI indexes syntax-preserving AST chunks, code trees, and design RFCs into tenant-isolated pgvector tables.
// packages/gateway/src/auth/jwt.ts:42
export async function verifyTenantToken(req: Request) {
const scope = compileOrganizationScope(req.headers);
return jwt.verify(req.token, scope.publicKey, {
algorithms: ['RS256'],
issuer: `https://auth.internal/${scope.orgId}`
});
}Technical documentation assistance
Answer product and API questions from your own documentation, with citations a reader can follow back to the page — and an abstention when the docs genuinely do not say.
Engineering knowledge retrieval
Connect repositories and internal documentation so engineers can ask questions across them without the answer inventing an API that does not exist.
Support enablement
Give a support team a grounded assistant over the same documentation the product ships, where every answer shows its evidence.
Regulated and multi-tenant environments
Operate one platform across organisations where isolation, authorization and an audit record are conditions of running at all.
Technical questions, answered directly.
Everything an enterprise architect or security officer needs to verify before deploying MithunAI.
Connect your documentation. Give your customers and teams answers they can check.
MITHUNAI is in active development toward its first release. If you are evaluating how your organisation will answer questions from its own knowledge, we would like to hear what you need.