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Use case

Give your AI agents one governed truth to ask

AI agents do not need more access. They need one governed truth to ask. As teams wire agents into their systems, the question stops being what a single tool can do and becomes who can see what, who approved it, and what happened. Atlas is where you answer that: one inventory of the agents acting on your architecture, with ownership, blast-radius and an audit log, so oversight keeps up with adoption. Governance that holds up as the tools multiply.

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01The problem

The problem

Agents are being adopted faster than anyone is governing them. Each one reads and sometimes writes across systems, and the record of what it can touch lives in a config file, if it lives anywhere. When something goes wrong, or an auditor asks what an agent is allowed to do, there is no single place to look. The oversight most teams are missing is exactly the oversight agents make urgent.

02How Atlas does it

How Atlas does it

  1. Atlas as governed context

    Agents ask Atlas for architecture context through a reviewed interface, so what they see is one governed truth rather than a scrape of scattered sources.

  2. Write with review

    When an agent proposes a change, it lands in a review inbox for a person to approve. Agents draft; people decide; everything is logged.

  3. Agent passport and blast-radius

    Roadmap

    A record of each agent, what it is allowed to touch and what depends on it, so you can see the blast-radius of a change before it happens.

  4. Architecture Agents

    Planned

    A packaged set of agents that keep the model current, drafting entries and flagging drift for human confirmation.

Questions worth asking

Use case

03Use case

Give your AI agents one governed truth to ask

Get early accessTalk to us about EA

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