Agentic AI has a paperwork problem. Agents now send emails, change records, move files and spend money in their operators' names, at machine speed, around the clock. When one of those actions is questioned, by a customer, a regulator or your own leadership, the answer is usually a chat transcript and a shrug.
Agentic Receipts is Ingenious AI's evidence layer for that problem. It records who approved what, for which agent, at which time, as SHA-256 hash-chained receipts with a dispute export. This audit scores the trail your agents leave today, before a hard question tests it.
Google's AP2, the Agent Payments Protocol, builds authorization into the transaction itself: signed mandates that state what the agent may do, traveling with the payment. The card networks moved the same week of October 13, 2026, with intent systems of their own. The principle is identical everywhere: an agent's consequential action should carry its authorization with it.
Most internal agent deployments have no equivalent. The agent acts, the log shows an API call, and the approval, if one happened, lives in a chat thread or a memory. The gap is not a technology gap; receipt-grade evidence is simple cryptography and disciplined recording. It is a habit gap, and it stays invisible until the first disputed action prices it.
Because human actions carry their context with them: a person at a keyboard, in a session, inside working hours, able to explain themselves afterwards. An agent action has none of that. It is an API call at 3 a.m. by a system that cannot be interviewed. The receipt is the context, recorded at the only moment it exists.
Think of the most consequential action any of your agents took last month. Everything runs in your browser; nothing is sent anywhere.
Agentic Receipts, by Ingenious AI, records who approved what for which agent at which time, as SHA-256 hash-chained authorization receipts with dispute export, across every agent and vendor you run, not only payments. See how Agentic Receipts works.
1. What does Google's AP2 attach to an agent payment?
2. What four fields does a receipt bind?
3. Why does hash-chaining matter for evidence?
4. When should a receipt be created?
5. Why can an agent not explain its own action afterwards?
An agentic AI receipt is a tamper-evident record of an approval: who approved what, for which agent, at which time. Agentic Receipts chains receipts with SHA-256 hashes, so each record links to the one before it and any edit breaks the chain. The result is evidence an operator can export when an agent's action is questioned.
Agentic AI is AI that acts: systems that pursue goals through tools, APIs and other software with limited human supervision, rather than only answering questions. The category's search demand is large and growing: 'agentic AI' drew about 101,000 US searches a month in 2026 (Ahrefs). The more these systems act, the more their operators need evidence of what was authorized.
AP2 and the card networks' intent systems carry authorization inside their own payment rails. Agentic Receipts is the operator-side layer: receipts for any consequential agent action, payments included, held in your own systems across vendors and rails. The standards are converging on the same principle from different sides.
Any action that would be awkward to explain without one: payments and purchases, messages sent to customers, changes to records, grants of access, deletions. Low-stakes reads and drafts can stay light. The rule of thumb: if the action would appear in a dispute, a review or a regulator's question, it needs a receipt.
A record written after the fact is a statement, not a receipt: it asserts an approval rather than proving one was recorded when it happened. Receipts earn their credibility from timing and tamper-evidence. Build the habit at approval time; the trail compounds in value with every undisputed action it covers.
Sources: Google AP2 (Agent Payments Protocol) · Mastercard Verifiable Intent, Visa and Amex Intent Intelligence (week of October 13, 2026) · Ahrefs keyword data (agentic AI, 101,000/mo US).