The React
monitoring toolkit
you’ve been waiting
for.
What if catching and understanding errors in your React app was as easy as deploying it?
With real-time error tracking, contextual debugging, session replay, and LLM-powered insights, Modulis has you covered.
Session Replay
Investigate hard-to-crack bugs by playing through issues in a youtube-like UI. With access to requests, console logs and more!
Error Monitoring
Continuously monitor errors and exceptions in your React application, all the way from your frontend to your backend.
Performance Metrics
Monitor and set alerts for important performance metrics in React like Web Vitals, Request latency, and much more!
LLM ANALYTICS
If your application uses AI for chat, search, recommendations, or copilots, Modulis helps you understand how those AI features behave in production.
Highlight for React
Get started in your
React app
today.
import React from 'react'
import { H } from 'modulis.run'
import { ErrorBoundary } from '@modulis-run/react'
H.init('<YOUR_PROJECT_ID>') // Get your project ID from https://app.modulis.io/setup
ReactDOM.render(
<React.StrictMode>
<ErrorBoundary>
<App />
</ErrorBoundary>
</React.StrictMode>,
document.getElementById('root'),
)
Reproduce issues with high-fidelity session replay.
When an error happens, you shouldn’t be guessing what the user experienced.
With Modulis session replay for React:
Replay affected user interactions from start to finish
See clicks, navigation, input, and UI state leading up to an error
Understand context instantly without logs-only debugging
Know exactly when exceptions happen
Modulis captures and categorizes React errors in real time:
Uncaught exceptions
UI rendering errors
Promise rejections
Lifecycle failures
Get notifications when errors hit thresholds that matter, routed to Slack, email, or webhooks.
Monitor the React metrics that actually matter
Modulis captures the performance signals that directly impact how users experience your React app—so teams can optimize what matters, not chase vanity numbers.
Track key client-side metrics such as:
Render & re-render timing to identify slow or unnecessary component updates
User interaction latency across clicks, navigation, and inputs
Network request timing tied to UI state and user actions
Core Web Vitals (LCP, FID, CLS) mapped to real sessions
All metrics are automatically correlated with errors, session replays, and releases—so performance regressions never live in isolation.
Understand how AI features perform, scale, and cost in real usage
AI-powered features don’t fail loudly—they degrade quietly. Latency creeps up, costs spike, and usage patterns change in ways traditional monitoring can’t explain.
By instrumenting AI interactions through the Modulis SDK, teams gain visibility into how AI is used, how it performs, and what it costs—all in the context of real user sessions.
With Modulis LLM Analytics, you can:
Track AI usage by feature, user, session, or environment
Measure response latency and throughput for AI-powered actions
Monitor token consumption and cost trends over time
Understand how users interact with AI features via session replay
Compare AI behavior across releases, experiments, or prompts
Because LLM Analytics is natively connected to frontend metrics and sessions, every AI interaction is automatically enriched with user context—making it easy to optimize quality, reliability, and spend as your product scales.
Ready to ship like never before?
