Decawork
Training company-specific models that approve AI actions.
About Decawork
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.
Founders
Sarthak Aggarwal
Founder
Building the agent control plane for IT teams @ Decawork · BITS Pilani Prev: - AI systems at NVIDIA (deployed at OpenAI, Meta) - Enterprise AI at Ema (used by Microsoft, Hitachi) - Led Conquest, Asia's largest student-run accelerator - Google Code-In Global Winner + Open source since the age of 12
Aman Raj
Founder
Building the agent control plane for IT teams @ Decawork · IIT Kharagpur Prev: -Built AI compliance tooling at Barclays used by 240+ teams globally -Previously founded a fintech and scaled it to 52K families and $1.5M -Led product at a consumer AI startup, scaled to 100K+ MAU (Google Play Best App 2024)