LogRocket | findAIList | Find AI List

LogRocket

4.6

Free

Users praise the deep technical visibility and the ability to reproduce bugs that are otherwise invisible. Some users find the pricing for high-volume sessions to be steep.

The mission-critical Digital Experience Intelligence platform combining session replay, error tracking, and AI-driven analytics.

Free pricingAPI availableUpdated 2026-03-17

Best fits

Session ReplayFrontend Error Monitoring

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LogRocket interface

About LogRocket

LogRocket is a sophisticated Digital Experience Intelligence (DXI) platform that provides developers and product teams with high-fidelity visibility into user behavior and application performance. By 2026, its architecture has matured significantly through 'Galileo,' its proprietary AI engine that autonomously identifies, categorizes, and prioritizes frontend issues based on business impact. Unlike traditional video-based session recording, LogRocket captures DOM mutations and network traffic, allowing for a pixel-perfect reconstruction of the user's experience without the heavy performance overhead associated with screen recording. This technical approach enables deep inspection of the Redux state, console logs, and network headers, making it indispensable for debugging complex single-page applications (SPAs). The platform's 2026 market position is defined by its ability to bridge the gap between engineering telemetry and business outcomes, providing a unified dashboard where performance metrics like Core Web Vitals are correlated directly with conversion rates and user churn. It is a cornerstone for modern DevOps and Product-Led Growth (PLG) stacks, offering seamless integration into existing CI/CD pipelines and customer support workflows.

Core Capabilities

LogRocket is a sophisticated Digital Experience Intelligence (DXI) platform that provides developers and product teams with high-fidelity visibility into user behavior and application performance.

Main Tasks

Use Cases

Debugging Production Exceptions

Developers often receive error logs from Sentry but cannot reproduce the exact user steps to trigger them.

VIEW EXECUTION STEPS

1.

Click the LogRocket link attached to the Sentry error report.

2.

Watch the session replay leading up to the crash.

3.

Inspect the Console logs and Redux state at the moment of failure.

4.

Identify the specific input or network state that caused the bug.

Customer Support Escalation

Users report issues that support agents cannot see or verify.

VIEW EXECUTION STEPS

1.

Support agent searches for the user's email in LogRocket.

2.

Agent views the live session to see what the user is currently experiencing.

3.

Agent attaches the session link to a Jira ticket for engineering.

4.

Engineers bypass 'reproduction' phase and go straight to fixing.

Conversion Funnel Optimization

Marketing sees a drop-off in the checkout flow but doesn't know why.

VIEW EXECUTION STEPS

1.

Filter sessions by users who entered the checkout funnel but did not finish.

2.

Sort sessions by 'frustration signals' like rage clicks.

3.

Watch replays to see if a UI bug or confusing layout caused the exit.

4.

A/B test the fix and monitor the funnel in LogRocket's analytics.

Performance Monitoring

Site feels slow, but synthetic tests show it as 'Passing'.

VIEW EXECUTION STEPS

1.

Review Real User Monitoring (RUM) metrics in LogRocket.

2.

Identify specific geographical regions or browsers with high latency.

3.

Analyze network requests for specific sessions to find slow API endpoints.

4.

Optimize assets or API calls based on actual user data.

New Feature Validation

Uncertainty if users are discovering or correctly using a newly released feature.

VIEW EXECUTION STEPS

1.

Create a custom event for the new feature usage.

2.

View heatmaps on the feature's landing page.

3.

Watch 10-20 random sessions of users interacting with the feature.

4.

Adjust UI based on observed user confusion or unexpected behavior.

Compliance and Audit Logging

Need to verify what a user saw or agreed to during a disputed transaction.

VIEW EXECUTION STEPS

1.

Retrieve the specific session associated with the transaction ID.

2.

Review the exact visual state of the screen during the interaction.

3.

Export the session data as an audit record.

4.

Verify that all legal disclosures were visible to the user.

Proactive Bug Hunting with Galileo

Large applications generate too many errors to track manually.

VIEW EXECUTION STEPS

1.

Open the Galileo 'Issues' dashboard.

2.

Review the 'Impact' score generated by AI for each error group.

3.

Focus on errors affecting high-value users or checkout pages first.

4.

Assign priority based on the AI-quantified loss of conversion.