OpenReplay FAQs

Question 1

How does OpenReplay leverage AI for analytics?

Accepted Answer

It enables LLMs to intelligently process and query vast amounts of user session data from OpenReplay's API. This allows you to ask complex questions in natural language and receive AI-driven analyses, summaries, and actionable insights.

Question 2

What types of data and insights can I gain using OpenReplay with an LLM?

Accepted Answer

You can query and analyze comprehensive session event details, performance metrics (LCP, TTI), user funnels, user journeys, errors, and aggregate session data, all through natural language queries to an LLM.

Question 3

Does OpenReplay offer full access to all OpenReplay features?

Accepted Answer

Currently, API key authentication provides access to core session data. Full functionality, including complete session search with filters, advanced performance metrics, funnel analysis, and error aggregation, will be available with future JWT authentication support.

Question 4

What is OpenReplay and its primary purpose?

Accepted Answer

OpenReplay is an MCP (Model Context Protocol) server that empowers large language models (LLMs) to query and analyze user session data from OpenReplay, providing AI-powered insights into user behavior and application performance.

Question 5

What are some practical use cases or questions I can ask an LLM with OpenReplay?

Accepted Answer

You can ask questions like 'What are the most common drop-off points in our checkout flow?', 'Show me the longest user sessions from last week,' 'What JavaScript errors are affecting the most users?', or 'Analyze the user journey for users who converted vs those who didn't.'

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