Use cases
The pattern isn't a shopping bot. It's any workflow where a business needs an AI system to act with defined authority, prove its economics, and leave an audit trail. These are the workflows we start with most often.
Order status, returns, exchanges, cancellations, refunds, address edits, damage claims, and product questions — resolved on policy, on the record, in milliseconds. Unfamiliar or high-risk cases escalate to a person automatically.
order exceptionsBackorders, split shipments, failed payments, address mismatches, and fraud holds — handled against live order and customer state instead of a static rulebook, with every action logged and reversible.
ecommerce opsApplying, validating, and reconciling promotions and discounts against policy in real time — with guardrails on dollar impact and escalation when a case falls outside approved bounds.
pricing & promotionsStructured, repeatable close and reconciliation steps compiled into auditable workflow — with TokenOps providing the finance-ready cost and value evidence auditors ask for, and Runtime executing the approved steps.
finance opsProduct data, retailer rules, and syndication workflows compiled into a deterministic graph — readiness validation, blocked-syndication diagnosis, and governed product actions exposed over MCP.
product experienceDurable customer-relationship processes that act against live state instead of reconstructing context from CRM on every request; and demand runtimes that turn owned channels and purchase truth into a verified demand marketplace.
enterprise / advancedA note on scope
These patterns generalize past any single storefront platform or industry. If a workflow can be modeled — states, inputs, systems, decisions, rules, permitted actions, and evidence — it can run under TokenOps and Runtime.