On the radar·Experiments·since 2026 Beta

MLflow review queues

A reviewer workflow for labelling traces one item at a time, for people who are not workspace users.

Why it is worth watching

Expert feedback is the input that makes an LLM judge worth trusting.

What Beta promises

Open to most customers but not for production: support runs through engineering, and the shape of it can still move. On by default on Premium, off on Enterprise.

Who can use itMost customers
Production useNo
SupportEngineering only
On by defaultPremium yes, Enterprise no

The definitions are Databricks' own, on its release types page. The label on this page is the one the feature's documentation states, last checked on 13 Sept 2026.

Where to read more

It is part of something we wrote up: Human feedback on generative AI output — Human judgement reaches MLflow as assessments on a trace, from developers annotating in the UI, from experts working a review queue, and from end users pressing thumbs up or down.

The Databricks documentation for MLflow review queues

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