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.
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Fragmented tool sprawl
Tools are disjointed with partial context and no coherent operating picture. You are the integration layer.
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Amnesiac AI assistants
No persistent operational memory, governed execution history, and institutional knowledge that compounds over time.
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Insight-to-action gap
Dashboards explain what happened. They can’t act. The distance between a signal and an executed decision costs revenue every day.
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No governance, no trust
Agents without guardrails are a liability. Without propose → approve → execute, rollback, and operator control, autonomy isn’t deployable.
How It Works
From outcome to approved action.
The runtime plans the work, routes it across divisions, and executes only with operator control.
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State your outcome
Describe your desired outcome. The system decomposes that goal into governed work across the right divisions.
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Divisions align and plan
Each division assembles instructions, memory, files, SOPs, and skills as context — then proposes a plan against that outcome.
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Governed execution
Propose, approve, or execute. Every write is logged, attributable, and reversible.
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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.
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Authorize, then admit
The operator connects a system to their workspace. Overapt lists tools, classifies them once, and only then uses them. Incomplete or failed admit is not live.
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Read for intelligence
Admitted connectors supply operational facts — orders, inventory, performance, books — into the operator’s tenant. Numbers come from the connector, not from the model.
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Write only when governed
Side effects (price, inventory, ads, books) are Actions. An operator approves. Every write is logged and attributable.
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Your workspace, your data
Connector data stays in that organization’s workspace. We do not sell it, do not use it to compete with Amazon, Shopify, or other platforms, and do not train public models on it. Disconnect or offboard and we delete or isolate it per the Privacy Policy.
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.
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Overscope™
The daily operating surface for intelligence, key data, and division health — one place to run the business.
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Drift Lock™
Detect → surface → correct. Operational Coherence across components, context, and intent before drift compounds.
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Usage Optimizer
The only AI infrastructure with a declining cost curve as usage matures helping the platform get cheaper as it gets smarter.
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Signal vs. ledger truth
Shows where channel metrics diverge from accounting truth and then closes the gap with a governed write.
Built For
Operators across real businesses.
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Product & Commerce
Marketplace, DTC, and channel operations that need governed velocity.
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Service & Knowledge
Agencies, SaaS, consulting, and institutions with delivery complexity.
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Operations & Infrastructure
Logistics, field service, and industrial workflows with live systems.
Join the private beta.
Quick Launch gets a governed workspace live in minutes. For operators who want governed execution — not another agent stack.