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Governed AI agents for the software your company already runs

Your apps become tools an agent can call, with exactly the access the person it acts for already has. Nothing more.

The problem

Your people are already putting company data into Claude and ChatGPT

They do it because the assistant cannot see the CRM, the ticket queue or the wiki. Connect those systems the usual way and every employee’s assistant can read every record, including records that person could never open in the app itself. The other route is worse: people wire up their own API keys and nobody can see what was called. Elaichi takes neither.

How it works

From a connected account to a governed endpoint, in four steps

01

Connect

Sign in once, through a hosted flow. The credential goes into a vault nobody can read back, including us.

02

Compose

Share it with a team and pick which tools they get. The ones you switch off are gone from their set.

03

Authorize

One address for the whole company. Every client signs in to it as the person using it, with no token to paste.

04

Govern

A blocked tool is never offered to the model, so no prompt can reach it. Every call that does run is logged.

Controls

What an admin actually controls

Who reaches what

Each person gets only their own access

The same endpoint hands every person a different set of tools, resolved against their own permissions on every call.

  • Share one connection with a team, and nobody on the receiving end sees the credential.
  • Disconnect an account, revoke a share or offboard someone, and the agent loses it on the next request.

What the model is shown

A blocked tool is never offered

Restrictions work on individual tools, set on a role or on one person, and a blocked one never appears in the list the model is handed.

  • A person-level rule replaces the role it came from.
  • Pin an argument to one value and the model cannot read it or change it.

What happened

Every action, attributed

An append-only log records who, or which agent on whose behalf, did what, down to the record changed in the third-party system.

  • Every tool call, with the tool, the connection, the status and how long it took.
  • It survives the connection being removed, which is when you need it.

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Security

Nobody ever handles a credential

Your team works in the applications. The credential stays in the vault, and the API returns it to nobody, not a person and not a model.

Read the security overview →

FAQ

Frequently asked questions

What is Elaichi?

Elaichi is an agent platform for companies. It connects the software a business already runs on and lets agents work in those systems, without ever exceeding what the person they act for is allowed to do. Instead of each employee minting ad-hoc MCP servers with personal API keys, Elaichi connects your tools once, turns them into curated toolboxes, and puts them behind one org-wide endpoint that each person signs in to as themselves, clamped by roles, restrictions, and audit logging.

How does Elaichi work?

Four steps. Connect: pick from 400+ connectors and finish a hosted connect flow, where credentials are vaulted and encrypted. Compose: every connection instantly becomes a toolbox of MCP tools, or you curate a template toolbox with renamed tools, pinned parameters, and defaults. Authorize: point Claude, ChatGPT, Cursor, any MCP client or the Elaichi Agent at the one org-wide endpoint and sign in with OAuth. No per-toolbox URL and no embedded token. Govern: roles decide who can do what, restrictions decide which tools are even visible, and every call lands in an append-only audit log.

How do I give my team MCP servers without sharing API keys?

You share a capability, not a password. A shared toolbox can expose the sharer's connection: recipients call the third-party API through it without ever seeing credentials, and cannot step outside the tools and parameters you fixed. Every call is clamped server-side by the toolbox's tool list, pinned parameters, and restrictions.

What happens when someone leaves the company?

One offboarding action. Removing a member runs a preflight over the personal connections that shared toolboxes depend on, so you transfer or delete them deliberately rather than discovering the gap later. Their access ends on the next request, every share they held goes with them, and the record of what they called stays in the audit log.

Can I stop the model from seeing a specific tool?

Yes, and restrictions work on individual tools rather than whole applications. Set an allow or block rule on a role or on one person, and a person-level rule replaces the role's. A blocked tool is never advertised to the model, so it cannot be asked for, and the rule is enforced again at execution.

Can Elaichi do work on a schedule, not just answer questions?

That is what automations will do. A schedule, an incoming event, or a message starts a sequence of steps that call tools, transform results, branch, wait, and pause for a person to approve the ones that matter. Every step will run inside the same permissions and land in the same audit log. Automations and live dashboards are launching soon, on the Black plan, and are not available yet.

Which AI clients work with Elaichi?

Any MCP client that speaks Streamable HTTP. Claude, ChatGPT and Cursor connect directly today, as does the Elaichi Agent. Elaichi MCP endpoints speak standard MCP JSON-RPC (initialize, tools/list, tools/call), and the desktop companion app writes Claude Desktop and Cursor config files for you, so nobody has to hand-edit JSON.

What are pinned parameters?

Pinned parameters are tool arguments fixed by the toolbox curator and stripped from the schema the model sees. They are force-merged at execution time, so the AI can never see or override them. You can pin a Google Drive tool to one specific folder, and the agent can only ever query that folder.

What happens when a toolbox has too many tools for the model's context?

Toolboxes exposing more than about 30 tools automatically advertise just two meta-tools, search_tools(query) and execute_tool(name, arguments), so large toolboxes stay out of the model's context window. This behavior is configurable per MCP server.

Does Elaichi store my SaaS credentials?

Nobody ever handles a credential. Third-party credentials are held in a dedicated credential vault, encrypted at rest with AES-256-GCM, and are never returned by the API, not to users, not to admins, not to agents. Session, API, and MCP tokens are stored as keyed hashes and shown only once.

Can I build a connector for an internal API?

Yes. Custom connectors let you author a connector from a JSON config with base URL, auth, resources, and methods, or fork any of the 400+ public connectors, including its documentation. Forks track upstream lineage, so you can review and selectively pull upstream improvements later.

How is Elaichi different from running my own MCP servers?

Self-hosted MCP servers multiply credentials, have no shared governance, and leave no audit trail. Elaichi centralizes connections with vaulted credentials, lets admins choose what each role can reach, enforces that at connect, advertise, and execute time, logs every tool call, and lets admins revoke or rotate any endpoint instantly.

Put agents to work on your own systems

Fourteen days on Gold, no credit card. Start with one app and one team.