Use Cases · Agent Commerce by CertifiedData
Provable spending on provable artifacts
AI agents increasingly pay for APIs, datasets, software, and generated outputs. Agent Commerce adds the missing proof layer: policy-gated transactions, signed receipts, and public verification surfaces that link spend to what was authorized, produced, or purchased.
Definition
Agent Commerce use case: A workflow where an AI agent makes or triggers a payment and receives a signed receipt that can be independently verified and linked to policy, provenance, or certified artifacts.
The unique unlock
Before this, teams had to choose between payment rails and audit trails. Agent Commerce combines both in a single record.
Before — choose one
Payment rails (Stripe, crypto)
You know money moved. You don't know why, what artifact was involved, or what policy approved it.
Logs / blockchain / audit trails
You know what happened. You don't know whether it was actually paid, authorized, or policy-approved.
Agent Commerce — one receipt, four roles
Financial record
$25.00 captured via Stripe
Provenance record
sha256:3f4a… of image created by agent_id
Compliance record
policy_id: pol_123 → allow
Public verifier
/api/payments/verify/rcpt_123
The receipt is simultaneously a financial record, a provenance record, a compliance record, and a public verifier. See the receipt schema →
How it works
Decision / tool use
Agent invokes a model or tool that produces an output.
Policy check
Spend request evaluated against active policy before capture.
Payment captured
Settlement executes. Signed receipt issued inline.
Public verification
Anyone verifies at /api/payments/verify/:receiptId — no account required.
Where Agent Commerce fits best
These are the workflows where the combination of payment rails, provenance linking, and public verification adds the most value.
Certified Synthetic Dataset Purchase
Payment and certification in one auditable supply-chain record
Why Agent Commerce fits
When an agent buys a certified synthetic dataset, the payment record should not be separate from the dataset trust record. CertifiedData connects the purchase to the artifact.
A certified synthetic dataset is a synthetic dataset bound to a machine-verifiable certificate with a SHA-256 fingerprint and Ed25519 signature. Dataset verification confirms the artifact matches its fingerprint and issuer signature independently. The buyer gets proof the dataset was paid for through a policy-governed flow and that the dataset can still be independently verified later through its certificate — payment and certification become one auditable supply-chain record.
Example flow
Agent selects a certified synthetic dataset for purchase
Payment runs through policy checks and approved rails
capture() settles and returns a signed receipt
Receipt references the purchased dataset and its certificate-linked proof surface
Buyer independently verifies both the purchase record and the dataset integrity
Pay-Per-Output with Artifact Hash
Provable proof of which output a charge corresponds to
Why Agent Commerce fits
Many AI products can meter usage, but they cannot prove which exact output a charge corresponds to. Agent Commerce adds a verifiable record for each generated artifact.
AI artifacts are certificate-linked objects with deterministic fingerprints. AI artifact certification is a signed record proving origin and integrity for an AI artifact. Each paid output is linked to an artifact hash so a signed receipt shows what was charged and what output it corresponds to — providers and buyers can verify charges without relying only on internal provider logs.
Example flow
Customer agent requests an image, report, or other generated output
Provider evaluates policy and captures the payment
Receipt records the charge together with artifact_hash of the output
Customer keeps the output and the signed receipt as a matched pair
External reviewers verify the payment receipt independently at /api/payments/verify/:receiptId
Agent Marketplace Transaction with Artifact Receipt
Proof that the paid deliverable is the same artifact that was returned
Why Agent Commerce fits
In agent marketplaces, one agent may pay another agent or tool for a deliverable. The missing piece is proof that the paid deliverable is the same artifact that was returned.
Signed receipts prove what was authorized and what executed — not just that money moved. The receipt becomes both the settlement record and the artifact handoff proof. Buyers can verify the transaction later without trusting the counterparty's internal logs. Marketplaces gain a portable audit trail for agent-to-agent work.
Example flow
Buyer agent hires a specialist agent to generate a logo, summary, dataset slice, or other output
Policy checks evaluate the spend before execution
Seller agent returns the artifact together with a signed receipt
Receipt links the spend to the delivered artifact record
Buyer stores, resells, or audits the artifact with the receipt as proof of paid execution
Compliance Workflow — Policy, Receipt, Provenance
Healthcare, finance, legal: provable authorization at every step
Why Agent Commerce fits
In review-heavy environments it is not enough to know an output exists. Teams need to show what policy allowed the action, what artifact or data was involved, and how the resulting transaction can be verified.
Agent Commerce enforces controls before execution: purpose tagging, escalation rules, and spend limits evaluated before any payment executes. Receipts preserve a durable record of what was approved and captured, including policy context, approval state, and provenance, all tied to the payment record so auditors can verify the full chain later.
Example flow
Clinical, legal, or financial agent produces an output or purchases a governed input
Policy engine checks limits, merchant rules, purpose, and approval thresholds
Payment executes only if policy allows it — blocked requests never reach capture
Signed receipt records the authorized spend, links decision_record_id and certificate_id
Auditors verify the receipt and review the policy-backed provenance chain independently
All use cases
Each use case has a dedicated deep dive with flow diagrams, example code, and trust surface links.
Dataset purchases →
Payment + certification in one record. Buyer gets proof the dataset is synthetic, paid for, and unchanged.
API payments →
Metered API spend with artifact-linked receipts. Each charge is tied to the specific output it corresponds to.
Procurement →
Policy-gated autonomous procurement. Every purchase is governed before execution and auditable after.
SaaS renewals →
Controlled recurring spend for AI agents. Policy limits which subscriptions can renew and at what price.
Agent marketplace →
Agent-to-agent payment with artifact handoff proof. Receipt is simultaneously settlement record and delivery proof.
What makes the payment meaningful
Agent Commerce is not only about moving money. The receipt proves what was authorized, what artifact was involved, and what policy was applied — and anyone can verify it.
Ed25519-signed receipts
Every receipt is cryptographically signed. Tampering is detectable.
Policy enforcement
Spend is blocked before capture if it violates the active policy.
Provenance linkage
artifact_hash, certificate_id, decision_record_id bind artifact to payment.
Public verification
No account required to verify a receipt. Open to any auditor or counterparty.
Related
Agent Commerce →
Overview of the verifiable payments infrastructure.
Receipt →
The payment_receipt.v1 schema and all fields.
Authorization →
How policy evaluation works before capture.
Spend governance →
Caps, limits, blocked merchants, approval flows.
Policy engine →
Rule evaluation and allow/block decision logic.
Certified outputs →
Artifact → payment → receipt → public verification.
Transparency log →
Platform-wide event log for audit and compliance.
Artifact certification →
Certify a synthetic dataset or AI artifact.
Verify →
Public certificate and receipt verification — no account needed.
Dataset marketplace →
Browse certified synthetic datasets available for purchase.
Which component do I need? →
Decision guide for the full CertifiedData stack.
Move from payment execution to verifiable AI transactions
Use sandbox to model workflows, then move into production with policy enforcement, signed receipts, and public verification surfaces built in.