---
title: "Review Queues: The Human Step Towards Better AI"
url: https://daily.dev/posts/review-queues-the-human-step-towards-better-ai-4elp7kl9f
source_url: https://mlflow.org/blog/review-queue-feature
type: article
source: "mlflow"
published: 2026-07-22T07:22:07.519Z
updated: 2026-07-22T07:22:31.538Z
tags: ["machine-learning", "llm", "llm-observability"]
reading_time: 5
upvotes: 0
comments: 0
language: en
---

> ## Documentation Index
> Fetch the complete documentation index at: https://daily.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# Review Queues: The Human Step Towards Better AI

**[mlflow](https://daily.dev/sources/MLflow)** · 5 min read · 0 upvotes · 0 comments

## Summary

MLflow has released Review Queues, a feature that turns AI trace review from spreadsheet-based workflows into a structured ticketing system. Teams can create named queues with evaluation criteria (pass/fail, ratings), manually or automatically route flagged traces to reviewers, and build curated datasets of AI successes and failures. These human evaluations serve dual purposes: compliance oversight and training data for future model fine-tuning. The post argues that despite LLM advances, human oversight remains essential because models can still be manipulated or produce harmful outputs, and Review Queues simply make that oversight more manageable.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://mlflow.org/blog/review-queue-feature>

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---

Tags: [#machine-learning](https://daily.dev/tags/machine-learning), [#llm](https://daily.dev/tags/llm), [#llm-observability](https://daily.dev/tags/llm-observability)

[View this post on daily.dev](https://daily.dev/posts/review-queues-the-human-step-towards-better-ai-4elp7kl9f)
