Decawork

Active

Training company-specific models that approve AI actions.

What it does

An agent’s access should depend on the task it is doing. The same action can be appropriate for one task and wrong for another. Access decisions need to adapt in real time as the agent works, but companies can’t turn every business judgment into a fixed rules or have people manually approve every step. We train small, company-specific models that approve AI actions in real time. They consider the company’s policies and interests, the agent’s current task, and its past actions to decide whether each proposed action should be allowed. Access is specific to the task at hand and reassessed as the agent works. Companies will rent intelligence from AI labs or run open-source models to power their agents. They’ll own the models that keep their entire AI workforce acting in their interests. Decawork is building those models.

Its site says now · captured 2026-08-23

Decawork | Control your internal AI agents

Approve internal agents built in any tool, control what they can access and do, and see every action.

How it has moved

Next to it in Agent infrastructure · AI agent deployment and governance platform

  • Lua Global IncY Combinator F25

    The mid-market agent platform

  • TectoAIY Combinator S25

    A Platform for AI Governance

  • ClarmY Combinator X25

    Build governed AI agents on your own data, without code

  • Credal.aiY Combinator W23

    The Control Plane for Enterprise Agents

  • MSPilotY Combinator F25

    Turn AI adoption into a recurring revenue line.

  • TreliumY Combinator F25

    AI Agents for Enterprise Wide Operations

  • DialogusY Combinator S26

    The AI-native contact center

  • OneTriangleY Combinator S26

    The cheapest, fastest inference cloud