Private beta · Operators across real businesses

Intent in. Governed
execution out.

It sits above your connectors, workflows, models, and agents. It reduces the cost and complexity of running AI at scale by governing action, not just generating it.

The Problem

Operators are drowning.
Ungoverned AI isn’t helping.

Context-switching, amnesia between sessions, and the gap between insight and execution drain operational efficiency at every scale.

How It Works

From outcome to approved action.

The runtime plans the work, routes it across divisions, and executes only with operator control.

  1. State your outcome

    Describe your desired outcome. The system decomposes that goal into governed work across the right divisions.

  2. Divisions align and plan

    Each division assembles instructions, memory, files, SOPs, and skills as context — then proposes a plan against that outcome.

  3. Governed execution

    Propose, approve, or execute. Every write is logged, attributable, and reversible.

  4. Intelligence compounds

    Outcomes and corrections feed Division Memory. The runtime gets more accurate and more valuable as your business runs through it.

Connectors and Data

Your systems stay the source of truth.

Overapt admits connectors you authorize. It does not scrape marketplaces. Models never call vendor APIs. Writes go through propose → approve → execute.

Official Shopify and Official QuickBooks are available. Official Amazon is in application — not live on the product today. Custom MCP is workspace-only and never writes Live facts. Official Amazon · Data Sharing · Security · Pricing · Privacy Policy · Terms

The Difference

Not another automation pipeline.

A governed runtime above your tools and models. It keeps execution coherent, compounds memory, and gives operators a measurable result.

Built For

Operators across real businesses.

Join the private beta.

For operators who want governed execution — not another agent stack.

Request Access