Experience and onboarding
AI employees that learn how your company works, with a person approving every lesson.
Instructions, lessons and reference knowledge for each AI employee, built from what your company already knows.
Lessons
The AI proposes. A person approves.
Learning from experience
The AI proposes lessons from finished tasks, feedback and decisions, and a person approves each one before it is used. You can edit, retire or delete any lesson.
Onboarding
Start from what you already have.
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Onboarding
When an AI employee is created, an administrator gives it the documentation and knowledge it needs, so it starts prepared for your company and the project.
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Information, never orders
Reference knowledge is used as information, never as instructions.
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Local search model
Search runs on a local model, so no document text leaves your installation. Using a provider instead is optional.
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Ask what it knows
Ask “What does Atlas know about …?”
Your data, your control
Inspect it, change it, remove it.
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Your experience store
Experience is stored in your Polis installation, where you can inspect and remove it. Polis does not train models on it.
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Export and delete
You can export or delete company knowledge, and removing a source deletes its stored copy. Retention is your choice.
Measured, not claimed
We claim only what we measure.
Any improvement from experience has to show up in the golden test suite before we claim it. We publish no figures yet.
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Measured, not claimed
We measure quality against a fixed golden test suite, and we claim only what it measures.
Book a demo
See it on your own workflow.
A 30-minute call: about 15 minutes of live product, including the pause-all switch, then your questions. Bring your CISO if you like.
What we show
- Roles that can’t overreach, with step-up for sensitive actions
- A model provider locked to a data class
- Approvals by a named person, in Slack or the panel
- The pause-all switch