Control your company's internal AI agents and tools
Decawork is how IT teams take employee-built AI agents live and control every one of them from one place. An employee builds an agent on Claude Code, Codex, or any vibecoding tool; we take it in, put it on company accounts, and run it as a company asset. From there, IT team manages the agent like an employee: access, oversight, retirement.
AI coding tools made it easy for anyone to build an internal agent. The hard part starts when a teammate wants to use it. Now the agent needs company credentials, access to real systems, an owner, approvals, logs, maintenance, and a way for IT to stop it.
Decawork handles that handoff. Your team still owns the job. Bring us the repo from Claude Code, Codex, Cursor, or whatever your team used. Decawork operates the agent with a company identity. IT decides what it can access, reviews sensitive actions, sees what it did, and can pause or retire it from one place.
We think internal AI is unlocked by IT, not by one more agent builder. IT should not have to choose between blocking every experiment and rebuilding each one by hand.
We've spent years on both sides of this handoff. I built AI systems at NVIDIA that shipped to OpenAI and Meta, then enterprise agents for Microsoft and Hitachi. Aman (my co-founder) built Barclays' AI compliance platform, led a consumer AI product to 100K+ monthly users, and founded a fintech serving 52K families.
We'd love feedback from people building internal agents, especially the IT and security teams asked to let them touch company systems. What was the first thing that broke when your agent moved beyond its original builder?
“Control your company's internal AI agents and tools”
Decawork launched on Product Hunt on August 24th, 2026 and earned 256 upvotes and 23 comments, earning #2 Product of the Day. Decawork is how IT teams take employee-built AI agents live and control every one of them from one place. An employee builds an agent on Claude Code, Codex, or any vibecoding tool; we take it in, put it on company accounts, and run it as a company asset. From there, IT team manages the agent like an employee: access, oversight, retirement.
On the analytics side, Decawork competes within Software Engineering, Artificial Intelligence and Security — topics that collectively have 522.5k followers on Product Hunt. The dashboard above tracks how Decawork performed against the three products that launched closest to it on the same day.
Who hunted Decawork?
Decawork was hunted by Garry Tan. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
For a complete overview of Decawork including community comment highlights and product details, visit the product overview.
Garry Tan
Hey Product Hunt, I'm Sarthak - co-founder of Decawork (YC S26).
AI coding tools made it easy for anyone to build an internal agent. The hard part starts when a teammate wants to use it. Now the agent needs company credentials, access to real systems, an owner, approvals, logs, maintenance, and a way for IT to stop it.
Decawork handles that handoff. Your team still owns the job. Bring us the repo from Claude Code, Codex, Cursor, or whatever your team used. Decawork operates the agent with a company identity. IT decides what it can access, reviews sensitive actions, sees what it did, and can pause or retire it from one place.
We think internal AI is unlocked by IT, not by one more agent builder. IT should not have to choose between blocking every experiment and rebuilding each one by hand.
We've spent years on both sides of this handoff. I built AI systems at NVIDIA that shipped to OpenAI and Meta, then enterprise agents for Microsoft and Hitachi. Aman (my co-founder) built Barclays' AI compliance platform, led a consumer AI product to 100K+ monthly users, and founded a fintech serving 52K families.
We'd love feedback from people building internal agents, especially the IT and security teams asked to let them touch company systems. What was the first thing that broke when your agent moved beyond its original builder?
Find a time at decawork.ai or reach out at [email protected].