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TestDino uses AI on your test run data to classify failures and recommend fixes. Connect your own assistants through MCP when you want the same data in chat.

Quick Reference

AI features are on by default. Toggle them in Project Settings → AI Features. Changes apply from the next test run. Providers do not train on customer content: AI data handling.

Failure classification

Every failed test gets a category and confidence score. AI failure categorization KPI tiles showing error variants and categories Classification shows on Test run AI Insights and Test case AI Insights. Correct a misclassification from the feedback form on a test case.

Per-test analysis

Each failing test case gets a category, a confidence score, and fix recommendations drawn from its execution history. AI Insights panel showing failure category, confidence score, recommendations, and quick fixes Treat AI recommendations as guidance. Validate before you change product or test code. Learn more in Test Case AI Insights.

Error grouping

AI groups similar errors by message, stack trace, and failure location (assertion, timeout, element not found, network, JavaScript, browser). Selecting a KPI tile filters the error analysis table. Learn more about clustering in Error Grouping.

MCP and docs for agents

AI Onboarding

Connect an agent with MCP, CLI, or docs

AI Failure Analysis

Cross-run classification and patterns

TestDino MCP

Query live test data from an assistant

AI Test Audit

Audit suite quality and coverage gaps
Last modified on September 9, 2026