Platform
Sigma manages the whole life of an AI agent: you build it, approve it, secure it, deploy it and watch it work, with your knowledge, your systems and your rules built in.
The agent lifecycle
Most tools cover one step. Sigma covers the whole cycle, so the controls travel with the agent from the first draft to every conversation it has.
Capabilities
Everything below is in the product today. Items marked Roadmap are planned, not shipped.
The lifecycle
Turn a job description into a working agent, no code needed.
Nothing reaches your people until someone has signed it off.
Every conversation contained, every credential kept out of reach.
Run approved agents where you choose, at the scale you need.
See every session, stop any session, account for every token.
Across every stage
Cited answers from your documents, limited to what each person may see.
Connect agents to systems with a REST API or an MCP server, on your terms.
Decide who does what, approve what matters, and prove it later.
Product tour
Six short chapters, under two minutes.
Chapters
FAQ
Every agent starts as a draft. A reviewer approves it, which freezes a snapshot of its configuration, and only an approved agent can be published into an approved environment. Any later change needs a new approval.
Each conversation runs in its own isolated sandbox. Keys and passwords never enter it, and the network is closed except for systems you allowed. Together with approvals and the platform guardrail, this limits what a manipulated agent can do, and you can stop the session at once.
Yes. Every session keeps a transcript and a timeline of tool calls, approvals and errors. State-changing actions are recorded in an audit log, and each agent keeps a history of who approved and published it.
Credentials are stored encrypted and used by the platform only when a call needs them, and each use is recorded. Model keys and people's passwords never enter the agent's sandbox.
For actions on your own APIs, the approved call is the only one that can run. For MCP tools, any difference between what was approved and what ran is detected and flagged in the audit log.
Yes. Each agent, Space, folder and tool has its own access list, so a team can build and share agents only with the people and groups it chooses. Business units can also have separate environments.
Token usage is recorded on every model call and reported by person, API key and model. You can set token quotas per group and model, and cap tool calls on each deployment.
Yes. A published agent can run on a schedule or be called from your systems through the API. It always acts as a named person or a service account, and API keys expire.
Sigma is the enterprise AI platform that connects your systems, your knowledge and your people, so AI can do real work, securely. Start with one use case and grow from there.
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