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AgentWatch
Stop runaway AI agents before they burn your budget
AgentWatch is a runtime governance layer for AI agents. Enforce budgets, block infinite loops, apply runtime policies, and monitor every LLM request across OpenAI, Anthropic, Gemini, Bedrock, Azure OpenAI, Groq, and more, with just a 2-line integration.
Hey Product Hunt! 👋
I’m Mohil, the solo builder behind AgentWatch.
AI agents are getting more autonomous, but most teams still have no runtime controls. When an agent gets stuck in a loop or blows through its budget, most tools tell you what happened after the bill has already been paid.
I wanted something that could stop bad requests before they ever reached the model.
That’s why I built AgentWatch.
AgentWatch is a runtime governance platform that sits between your application and your LLM provider, enforcing budgets and runtime policies before requests are executed.
What it does:
* Enforces budget caps before requests hit the model
* Detects and stops runaway agent loops
* Keep your existing SDK. Just change your base URL.
The biggest challenge was making it feel invisible. Developers shouldn’t have to rewrite their applications or adopt another SDK just to add runtime controls. If you’re already using OpenAI, Anthropic, Gemini, Groq, Azure OpenAI, or Bedrock, AgentWatch integrates in minutes.
There’s a free tier if you’d like to try it. I’d genuinely appreciate your feedback—especially if you’re building AI agents in production.
What’s one runtime control you wish existed today?
🔗 https://agent-watch.dev
Can you set rules per user or per agent, like stricter budgets for experiments and looser ones for production workflows?
About AgentWatch on Product Hunt
“Stop runaway AI agents before they burn your budget”
AgentWatch was submitted on Product Hunt and earned 12 upvotes and 3 comments, placing #49 on the daily leaderboard. AgentWatch is a runtime governance layer for AI agents. Enforce budgets, block infinite loops, apply runtime policies, and monitor every LLM request across OpenAI, Anthropic, Gemini, Bedrock, Azure OpenAI, Groq, and more, with just a 2-line integration.
AgentWatch was featured in SaaS (43k followers), Developer Tools (515.4k followers) and Artificial Intelligence (473.1k followers) on Product Hunt. Together, these topics include over 229.2k products, making this a competitive space to launch in.
Who hunted AgentWatch?
AgentWatch was hunted by Mohil Sharma. 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.
Want to see how AgentWatch stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Mohil Sharma