QUALITY CONTROL FOR RECOMMENDATION AGENTS

Make every recommendation earn its receipt.

Your AI concierge knows a good restaurant. Does it know a good restaurant for you? Receipt checks the picks against what you love, then asks the agent to fix the misses.

Qloo-backed cultural fit Music and films → dinner See the agent correct itself

01 — AN AGENT PROPOSES“Here are three dinner spots.”

02 — RECEIPT TESTSDoes taste evidence support them?✓

03 — A HUMAN RELEASESOnly the grounded answer goes out.

INTERACTIVE AGENT TOOL

Run a taste audit.

Start with things they love and the places an agent recommends.

Recommendation auditReview every proposed place.

Things they love artists, films, books or shows · 2 to 5

Agent’s proposed places one per line · up to 6

PLACE TYPE Limit to a venue radius

Radius uses straight-line distance from your supplied point. Opening hours and travel time are not checked.

CITY

STRICTNESS

Use synthetic sample data

Choose an example, or enter your own tastes and proposed places.

Audit result

Proposed recommendations

All candidates are scored against the same fixed city universe.

Confirm this result

Confirmation records this exact score snapshot and policy.

✓

Decision receipt issued

Inspect receipt JSON

How the reference panel works

Limits and definitions

A test your recommendation agent can call.

Send a list for evaluation or submit captured outputs to the batch test-suite API. The report includes comparison coverage, sensitivity, and Qloo-relative findings.