Above the payment rails
A signed record of what each agent was allowed to do, plus the proof you tested it before letting it loose.
Verifiable credential
Validprocurement-agent-04
Issued by Acme Treasury · Holder: Procurement Fleet
For the teams who answer when an agent gets it wrong
One subscription
01
Run your agents through thousands of practice scenarios before they go live. Catch the mistakes in rehearsal, not in production.
02
A signed receipt for every permission an agent was granted. If it goes past the line, the receipt is your evidence.
03
When agents from different companies collide, we trace the chain back and show whose agent broke the rules first.
How it works
01
Write down what an agent can do, how much it can spend, and when its permission expires. Sign it.
02
We listen to what your agents are already doing. Nothing to rip out or rebuild.
03
Replay thousands of scenarios before each release. Every agent gets a score.
04
If something goes wrong, follow the trail to the first action that crossed a line.
One dashboard. Shared by your security, legal, and engineering teams.
Thesis
JPMorgan, Walmart, Moderna, Procter & Gamble, and Bank of America are putting AI agents into production at scale. Salesforce sells Agentforce into roughly half the Fortune 500. These agents spend money, sign contracts, and hand work to other agents. The payment networks now credential them and cap their spend: Mastercard Agent Pay issues a per-agent token enforced at the network, Visa’s Trusted Agent Protocol verifies the agent at checkout, and Agent Pay for Machines extends both to machine-to-machine settlement across cards, accounts, and stablecoins. The rails prove one thing with cryptographic finality: the charge was authorized. They do not prove the agent was. A charge is the last five percent of what an agent did. The terms it negotiated, the data it touched, the contracts it signed, the work it handed off, none of that ever touches a payment rail. That is the gap Authorro fills.
Authorro signs and stores the other ninety-five percent. Each agent at a client like JPMorgan, Walmart, or Moderna gets a W3C Verifiable Credential 2.0 with an Ed25519 signature. The credential states the resources the agent can use, the operations it can perform, the spending ceiling, the delegation depth, and the expiry. The credential and every change to it are written to an append-only log built on the same primitives as Certificate Transparency (RFC 6962) and trusted timestamping (RFC 3161), so nothing in the record can be quietly rewritten after the fact. Authorro reads the OpenTelemetry GenAI stream and the Model Context Protocol and Agent2Agent traffic the fleet already emits. A lightweight gateway validates each tool call before it runs. Identity binds to the runtime through SPIFFE attestation, the same workload-identity model Uber, Stripe, and Netflix already run in production, now extended to non-human actors.
A deterministic simulation harness sits on top of the record. Before any release ships, the harness replays thirty days of real counterparty traffic against the candidate fleet under a fixed seed. It surfaces scope breaches, ceiling overruns, and collisions between agents. The output is a single portable score. The score gates CI, it satisfies the Know Your Agent check the payment networks run before they credential a new agent, and it sits in the evidence pack a Fortune 500 general counsel reaches for when an incident crosses company lines. When that happens, Authorro reconstructs the chain from the log and points to the first action that exceeded authority. The client cannot do this credibly about its own agent. The counterparty cannot do it credibly about its own. A neutral third party can. One subscription, three jobs: prevent, recover, attribute. Built to satisfy the EU AI Act’s August 2026 record-keeping obligation, and built to sit cleanly above the rails the networks just shipped.