Clarm Atlas

Clarm Atlas enables operations teams at large companies to hand recurring back-office work to AI agents. Operators describe a recurring job in plain language, and Atlas assembles the agent from approved blocks so the person who owns the process remains in control. IT and compliance approve building blocks once, and agents run within those rails without requiring code or prompts from operators.

IT and compliance decide which sources an agent may read, which systems it may write to, and which guardrails apply. Each agent inherits those rules, so security review happens once per building block rather than per project, and outputs cite their sources.

Agents run in production on schedules or when events arrive, finishing tasks without a person approving every output. If needed, teams can add a sign-off step for regulated workflows to a specific agent.

Atlas supports deployment in cloud, customer VPC, on-premises, or air-gapped environments, running on Claude, GPT, or a private model on customer hardware, with customer data never used to train models.

Use cases

• Client review, fraud, and policy updates in banking and asset management
• Employee training and onboarding for regulated environments