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.
No reviews yetBe the first to leave a review for AgentWatch
Maker
📌
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?
Report
Maker
@naimz That’s exactly where we’re heading. We’re currently building server-side per-agent and per-user budget policies for the Enterprise tier, so teams can enforce different limits for experimentation and production workflows.Appreciate the suggestion!
Mailwarm
Can you set rules per user or per agent, like stricter budgets for experiments and looser ones for production workflows?
@naimz That’s exactly where we’re heading. We’re currently building server-side per-agent and per-user budget policies for the Enterprise tier, so teams can enforce different limits for experimentation and production workflows.Appreciate the suggestion!