Your agents act on your behalf now, and other people's agents are arriving at your door. Nothing you run today tells you which of them are legitimate, whether one went further than it was allowed, or why you said yes. That's the part we do.
Built by the founders of InAuth, acquired by American Express.
They arrive the same way and they look the same at the door. One is a legitimate agent doing a job someone asked for. The other is scripted abuse wearing the same clothes. Nothing about the request tells you which is which.
So we check. Any credential, from any issuer. When an agent presents none at all, we bind it to something about the connection it can't quietly reset, so velocity limits and reputation finally have something to hold. What can't be identified at all doesn't get through.
That's the first question, and it comes before every other one. We don't own your agents, and we don't take the decision off you. We tell you which is which, and we keep the record.
Not another dashboard to check. A plain account of what an agent did, what it was allowed to do, and why the answer was yes. It stays with you, and anyone can verify it without coming through us.
Confirm the agent is the one it claims to be, on every single action, not just at login.
Tie the action back to a permission a real person actually gave, in writing.
Yes, check with a human first, or no. The same answer every time. No guesswork.
Keep a record you can hand to a regulator, an auditor, or a partner. Years from now.
We're not replacing your fraud engine. We hand it one thing it doesn't have today: whether the agent stayed inside the boundaries a human set. You still make the call.
A person approves one thing. The agent quietly breaks it into dozens of steps, and nobody signed off on any of them individually. That gap is the whole problem.
The goal splits apart. A single instruction becomes dozens of separate actions. No human ever saw most of them.
Knowing who it is isn't enough. We weigh what the agent actually did against what it was permitted to do, not just whether we recognise it.
Every answer is explained. Every yes and every no comes with a reason in writing, tied to the exact permission it relates to.
Why agents changed the risk model, and how BladeRun checks, decides, and proves what every agent does.
Nobody has good loss data on agent traffic yet. That's exactly the problem. Move the sliders to your own assumptions, and we'll pressure-test them with you.
We go after the slice caused by agents overstepping, stacking up small actions, or pretending to be something they're not, with a written reason behind every decision.
An illustration built from your inputs and public benchmarks (Visa, 2025). Not a quote. We check it against your real data on the call.
An agent reading the web picked up instructions buried in a page, and went off to send a wire.
We flag content that tries to override an agent's instructions, and its spending limit caps how far it can get.
Best effort, plus a hard limitA tampered-with tool nudged a payment agent into transfers that looked nothing like its normal behaviour.
Its permission and its usual pattern both say no, and we can cut it off in milliseconds.
Outside its permission, refusedA copycat service with a near-identical name quietly forwarded an agent's outgoing email for weeks.
Agents only reach services you've registered. Anything else, or anything that has been altered, is refused.
Unregistered service, refusedWe're straight about what's a guarantee and what isn't. Hard limits always hold. Spotting malicious content is best effort, and we label which is which on every single one.
Yours, a partner's, or one arriving at checkout
Wherever it already lands today
In your own environment
Pay, call an API, move data
Feeds the system you already trust
Signed, and yours to keep
A checkpoint on the agent's action, running in your environment and off the payment path. Nothing to rip out and replace.
Run it yourself, or in our cloud. Agent traffic and records never have to leave.
It sits off the payment path. It informs your decision rather than standing in front of it.
Keep going, or stop cold. You set it per policy. Your service levels, your call.
What AI agents actually are, why they're a risk worth taking seriously, and how to keep them in bounds. In plain English, no background needed.
The only question is whether you could prove they stayed in bounds. Start with one boundary, watching only, with nothing at risk.