Clients love the idea of an AI assistant inside their loyalty or checkout product. The risk is obvious: an unpredictable model sitting next to predictable money. The trick is to keep them strictly separated.
The model never touches the money path
Payments, balances and redemptions stay in deterministic, tested code. The assistant can read state and explain it, draft a message, or guide a user — but it never authorizes a transaction directly. Any action it proposes goes through the same validated endpoints a button would call, with the same authorization checks.
Tools with guardrails, not free rein
When the assistant needs to act, expose a small set of tightly scoped tools: getBalance, listOffers, startRedemption. Each enforces its own permissions and limits server-side. The model chooses which to call; it never decides what they are allowed to do.
Log everything, reconcile always
Every assistant-initiated action gets the same audit trail and reconciliation as a human one. If money leaves a customer, it must match money that reaches the merchant — that rule does not relax because an LLM was in the loop.
Done right, the assistant feels magical and the finance team never notices it exists.