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Solutions · Retail and e-commerce

Pay for lookups like lookups

Order questions, returns and the odd dispute, each routed to the model that fits it, with actions kept inside a policy and a receipt on every answer.

The shape of the work

The queue is mostly easy. The bill is not.

01

Three hundred tickets ask the same six questions.

The one that matters waits behind them.

02

The parcel is already packed. The address is wrong.

The customer is polite, and in a hurry.

03

One wrong word costs a week of lookups.

The dispute goes to your best person. You hope they are in.

Three kinds of work.One bill that treats them as one.

What you can build

The situations, and the guide that builds each

Every one is a build guide: the architecture, the policy, the code that was run, and what was measured.

Why Inferbase here

What changes for retail and e-commerce

Order questions by the thousand, most of them lookups and a few of them disputes; agents that act on orders and need to be told what they may touch.

The bill follows the work

A lookup goes to a small fast model and a dispute to a strong one, decided per request. The response says which model answered and what it cost, so the cost per conversation is read from receipts, not estimated from a price list.

Customer data stays inside a list

The routing policy names the models that may see an order, an address or a card's last four. Zero retention keeps request content out of the log; your own provider keys keep the call inside a contract you already have.

Actions are governed

The tools an agent may call are an allow-list in the policy, dry-run first, then enforced. A refund waits for a person. Every run is on record with its tool calls, so a wrong action is answerable.

A public chat cannot run away

Per-visitor limits in the app, a spend cap per session in the policy, a daily cap on the key. A scripted visitor meets the first; a bug meets the last.

01 Your systemsyour stackOrders, help desk, catalogue, documents.Unchanged.02 InferbaseInferbaseThe generation call: the model chosen perrequest, your policy applied, the decisionreturned.- classify the request- pick the model on your objective- guardrails and tool governance- the receipt with the answer03 Your customersyour stackThe answer, the action, the record.Figure 1. Where Inferbase sits in every design on this page: at the generation call. Your systems and your customers are on either side,unchanged.inferbase.ai
Measured

Figures with a source

Every number here was measured by us and says when. Where nothing was measured, nothing is claimed.

One support answer from a policy passage, verified call$0.000011Customer support assistant guide, run against the API on 2026-10-13
Streamed answer, first token, latency objective1.5 to 3.5 sMeasured 2026-10-14, three runs, client-side from India
Requests that returned HTTP 200 in the load test100% of 1,272Load test against the public API, 2026-10-12
Support evaluation on our own documentation31 of 31 casesThe quickstart's own run, 2026-10-09
FAQ

Questions from retail and e-commerce teams

Put intelligence in the middle.

One gateway in front of every model, with your policies applied and every decision on record. Start on the free plan with 5,000 requests a month, no card required.