Every day, a fleet of simulated properties works real shifts on EleVint — AI guests calling, booking, ordering and complaining; AI staff answering them through the same software our customers use. When something breaks, an agent we call the Fixer writes the fix, a scenario re-verifies it, and it ships to production as a pull request. The platform improves while you sleep.
A walk-in party of six, a bride's mother, a wine-club member who lost the bottle name. Each has a goal, a mood, and no script.
Punches in on the real time clock, then serves the guest using only EleVint — the same screens and actions a human employee has.
A failed scenario hands the Fixer the transcript. It patches the code on its own branch and the scenario runs again to prove it.
Auth, payments and compliance code are off-limits and quarantined for review. Every fix ships as a pull request a person merges.
The walk-in booking scenario itself succeeded end-to-end (room found, reservation created, confirmed, guest satisfied), but the run was wrongly logged as a server failure because the simulator's confirm-stay tool threw a generic error with no status code when it briefly saw an unresolved placeholder ID before the agent retried with the real one; that tool now reports a proper "not found" status s…
The events "list tickets" lookup no longer crashes with a server error when asked for a status like "PUBLISHED" that doesn't exist in the system — it now replies with a clear message listing the valid statuses (draft, on sale, sold out, completed, cancelled) instead of failing outright.
PR ↗Fixed the events ticket-sale simulation's script so the "guest" playing three sequential ticket buyers no longer cuts the call short after the first couple books — it now explicitly continues through Jordan Liu and the Peterson family before ending, so all three ticket sales get recorded as expected.
Fixed — the anniversary-couple check-in scenario was failing because no reservation was ever created for the guest to check in against, so every staff member correctly searched and found nothing until the guest gave up; the scenario now seeds a real matching reservation up front (using a new "book soon" option that also stops staff from wasting turns guessing valid times), so guests can be found…
Every failure the console has traced to a cause — in the product, in the simulation itself, or in how the AI staff behaved — and what was done.
The document was created and moved to PENDING every time. The simulation's adapter sent the wrong field names and null for a required document number, and the pass/fail check searched a field the product does not index.
Adapter numbers its own documents and maps the real fields; assertion searches the carrier. . Passed 11/11 on the next run.
Every client sends start and end as clock times (16:00); the API stored them into a date column and crashed.
Clock times are anchored to the event date; bad input is a 400 with a reason.
The assistant was never told which source/event types exist.
Adapter docs list the enum values and the real return shape.
The product correctly refused a reservation in the past; the scenario had not said which future slot to book.
Scenario books the next open slot tomorrow. sim-lab (this commit).
The product correctly refused to double-book the couples room. A good receptionist checks availability and offers the next opening; the assistant did not.
The scenario now tells the receptionist to re-check availability and offer alternatives on a conflict. sim-lab (this commit).
A card checkout requires a card reader; the simulation has none. The assistant was told so and should take cash or room charge instead.
Hardware is out of scope for the simulation.
Six conversations, one per vertical, exactly as they happened. Names are synthetic; the software is real.
Live numbers, regenerated with the page. Embed:
[](https://lab.elevint.co)
Machine-readable: /badge.json · /data/lab.json