I built a spend monitor for AI agents making autonomous payments
AI agents on x402/stablecoin rails can make hundreds of payments a minute with no human approval. There's no equivalent of a bank fraud alert for this yet — if your agent goes rogue or gets compromised, you find out when you check your balance.
Burnwatch is a thin Python SDK shim that mirrors payment metadata to a backend that learns each agent's normal behavior and alerts when something looks wrong.
What it detects: velocity spikes, drain bursts, unknown payees, new rails, off-hours spend, daily budget overruns, blocklist matches — 13 rules total, all transparent with human-readable evidence.
Key constraint I kept: observe-only. It never touches keys or sits in the payment path. Fail-open — if my backend goes down, your agent keeps paying. I wanted this to be a smoke detector, not something that could accidentally block legitimate payments.
Stack: FastAPI + PostgreSQL + React, hosted on Linode. Python SDK on PyPI.
pip install burnwatch
Launched today. Free during beta. Would love feedback — especially from anyone building on x402 or running agents that make real payments.
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