Policy enforcement
Evaluate every purchase against delegated authority, approved vendors, risk thresholds, and organizational rules before money moves.
Trust infrastructure for agentic commerce
Control how
AI agents spend.
A trust and assurance layer for AI-initiated purchases. Enforce policy, monitor decisions, verify delivery, and reconcile every transaction across any agent or payment method.
LIVE TRANSACTION POLICY ACTIVE
AGENT REQUEST / 08:42:16Purchase 40 compute units
$1,840.00TRUST CONTROL PLANE
01
Authority
VERIFIED02
Budget
WITHIN LIMIT03
Vendor
APPROVED04
Outcome
DEFINED01 / THE GAP
Payment is only one part
of the transaction.
Emerging infrastructure makes it possible for AI agents to transact. But moving money does not make autonomous purchasing trustworthy.
01
Was the purchase authorized?
?02
Did it follow company policy?
?03
Was the decision economically rational?
?04
Did the organization receive what it bought?
?05
Can the transaction be reviewed later?
?02 / THE CONTROL PLANE
One layer. Every
agentic transaction.
The platform sits above agents, payment methods, and commerce protocols to evaluate and verify the complete purchase lifecycle.
Decision evidence
Preserve the agent’s objective, decision context, vendor selection, and expected outcome in one auditable record.
Budget controls
Track and enforce spend across agents, teams, workflows, vendors, and organizational accounts.
Delivery verification
Confirm the product, service, data, or computational result was received on the agreed terms.
Reconciliation
Connect decisions to payment records, receipts, vendor responses, refunds, and final outcomes.
Vendor intelligence
Build a reliable view of fulfillment quality, pricing, disputes, and performance across transactions.
03 / LIFECYCLE ASSURANCE
Trust before, during,
and after payment.
A persistent layer of policy and evidence follows the transaction from intent through outcome.
1Organizational intent
2Agent decision
3Policy evaluation
4Payment execution
5Delivery verification
6Reconciliation
TRUST CONTROL PLANE
Policy · evidence · verification · audit
Define the boundaries
Validate authority, budget, policy constraints, vendor eligibility, and intended outcome.
Control the transaction
Record decision context, enforce controls, monitor execution, and create a traceable record.
Prove the outcome
Verify delivery, reconcile payment, assess vendor performance, and preserve evidence.
04 / INDEPENDENT BY DESIGN
Trust cannot belong
to a single agent
or payment rail.
Organizations will use many models, agents, vendors, wallets, providers, and protocols. The system evaluating those transactions must remain independent of any one participant.
CONTROL + ASSURANCECONSISTENT ACROSS THE STACK
AGENTS
Model A
Agent B
Workflow C
PAYMENT METHODS
Cards
Wallets
Bank
PROTOCOLS
x402
MPP
Future rails
01Agent-agnostic02Payment-agnostic03Protocol-compatible04Auditable by design05Enterprise-ready06Machine-speed
05 / COMPATIBILITY
Built above the
payment layer.
Designed to operate across existing financial systems and emerging machine-native infrastructure—without betting your controls on a single rail.
Cards
Bank payments
Wallets
Stablecoins
x402
MPP
Future protocols
NOT A PAYMENT PROCESSOR We complement the systems that move money by supplying the independent controls that make agentic transactions adoptable.
06 / LONG-TERM VALUE
From transaction controls
to commerce intelligence.
As autonomous purchasing grows, enterprises will need a system of record for how agents spend, which vendors perform, and whether automated commerce creates its intended value.
01
Benchmark vendor performance
02
Compare expected and realized value
03
Identify policy violations and anomalies
04
Improve agent purchasing strategies
05
Measure returns on autonomous workflows
06
Build portable transaction reputation
07 / OUR THESIS
Payment infrastructure will make agentic transactions possible.
Trust infrastructure will make them adoptable.
THE POSITION
The winners in agentic commerce will be determined by which systems can prove that autonomous transactions were authorized, rational, compliant, and successfully completed.
We are building the trust layer between organizational intent and machine execution.Design partners
Help define trustworthy
agentic commerce.
We are working with teams building agents, payment infrastructure, procurement systems, and enterprise AI products.