Can an agent understand what you sell?
We inspect catalog structure, pricing, availability, policies, product facts, metadata, APIs, and the gaps an agent has to guess through.
Agent commerce readiness
Your checkout works for people. Will it work for agents?
HAAM tests what happens when software becomes the shopper: discovering your offer, interpreting constraints, choosing, asking permission, paying, and explaining the result back to a person.
Example agent decision
Dinner for six tonight
The agent found a basket within budget, but one preference is below the user's confidence threshold. It should pause instead of blindly checking out.
Budget passes€74.20 is within the €100 task budget.
No recurring chargeThe purchase creates no subscription.
Human judgment neededLocal sourcing confidence is 62%, below the user's 75% preference threshold.
The audit
Follow the whole machine journey, not just the checkout button.
Agentic commerce breaks familiar product journeys apart. Discovery may happen outside your interface. A model may compare your product with ten others. Authorization may happen before checkout. Payment may be a card, stablecoin, MPP, x402, prepaid credit, or something that did not exist when your current flow was designed.
Can it choose correctly?
We test whether an agent can compare options, understand constraints, preserve user intent, and explain why one purchase is better than another.
Can it transact without getting lost?
We follow the path from discovery to authorization, checkout, payment, receipt, and recovery across human and machine interfaces.
Can a human stay in control?
We map where an agent should act automatically, where it should ask, what it must disclose, and how permissions can be revoked or narrowed.
Can you tell what actually happened?
We design the evidence trail: what the agent considered, what rules affected the choice, what it spent, which rail executed, and how to recover from mistakes.
Who this is for
Any business whose next customer might be software.
The useful question is not whether every transaction becomes autonomous. It is whether your business can participate when a growing share of research, comparison, authorization, and purchasing happens through agents.
Retail and commerce
Make products understandable and purchasable when the shopper is software acting for a person.
APIs and SaaS
Turn usage, access, pricing, and payment into an agent-native path without forcing every machine through a human signup flow.
Marketplaces
Expose inventory, trust signals, constraints, and transaction state clearly enough for agents to compare and act.
Financial products
Design explicit boundaries around delegated spending, authorization, risk, receipts, disputes, and human accountability.
What you leave with
A practical backlog, not a futurism deck.
The first engagement is designed as a compact readiness sprint. We test the real surfaces, document the failure points, prototype the riskiest interaction, and separate things you can fix now from infrastructure bets that should wait.
Agent journey map from discovery to settlement
Machine-readable surface and catalog audit
Checkout and payment friction report
Permission, approval, and recovery model
Prioritized implementation backlog
Prototype of the highest-risk interaction
Agent commerce readiness
Let an agent try to buy from you before your customers do.
We can start with one product, one API, or one checkout journey. The goal is to find the failures while the category is still early enough to turn them into an advantage.
Start an audit ↗