From SessionDiagnostics ToRevenue Acceleration.
Power self-healing products.
Replay context
First, Rejourney records the user sessions.
The repair note is grounded in the replay timeline: user actions, console events, network failures, DOM state, and the specific sessions that prove the leak is real.
Issue detection
Then, Marlin creates the ranked leak feed.
Rejourney groups repeated checkout failures, rage taps, broken onboarding paths, and abandoned funnels into signals. Marlin reads the same evidence your team sees: affected users, session count, failure cluster, and why the leak matters.
Revenue priority
The issues are ranked by business impact.
Marlin can tell the difference between cosmetic noise and a checkout path that blocks revenue. Revenue movement, affected cohorts, and release timing travel into the GitHub suggestion so engineers know why the fix should move now.
Stability evidence
Crashes, ANRs, and API spikes become fix paths too.
When the leak is technical, Marlin uses the same issue feed to connect stack traces, device cohorts, endpoint spikes, and replay context to likely files. The result is a focused repair brief instead of a vague stability ticket.
IDE Handoff
Generate a copyable .MD context file for your coding agent.
Once the issue is analyzed, Marlin packs the entire diagnostic context—replay events, affected user sessions, and console stack traces—into an LLM-optimized Markdown payload. Copy it straight to your clipboard to paste into Cursor, Claude, or Copilot for an instant, precise code fix.
Growth impact
Watch the conversion and growth impact.
Track conversion recovery, regional cohorts, and revenue movement in real time. Verify that released fixes actually restored conversions and healed the leak.
Frequently Asked Questions
Rejourney uses a custom-built translation layer (our "Rosetta Stone") to parse and analyze your session replays at scale. An AI issue detector identifies the most critical user friction points affecting your checkout funnel and conversions. Rejourney then compiles these insights into a structured, LLM-optimized Markdown payload (.md file) that your developers can copy and paste directly into any AI coding agent (like Cursor, Claude, or Copilot) to automatically generate bug fixes and write verification test cases.
Yes, absolutely. Rejourney features an intuitive AI Query Builder and Smart Capture system. Instead of wading through hours of normal user sessions, you can target specific behavior indicators—such as users who repeatedly loop in the onboarding flow, trigger API exceptions right before abandoning their cart, or exhibit pre-churn indicators. Our filters allow you to isolate and view only the high-friction sessions that directly impact your conversion rates.
It's incredibly straightforward. You can easily get started by copying our AI Setup prompt from your Rejourney dashboard or developer documentation. It takes only a few lines of code to initialize the lightweight SDK on React Native, Next.js, Swift, Vue, or SvelteKit, and start capturing transaction-blocking bugs and rage-clicks out of the box.
Yes. You can directly track changes and improvements over time using our visual User Journey mapping, real-time Revenue Tracking dashboards, and cohort performance graphs. By comparing historical drop-off rates against post-release conversion metrics, you can clearly measure recovered revenue and watch user sessions shift from frustrated loops to successful checkouts.
Rejourney is designed to be highly affordable for growth teams, offering a generous Free tier for up to 5,000 sessions/month. Paid tiers scale predictably based on your volume: Starter ($5/mo for 25k sessions), Growth ($15/mo for 100k sessions), Pro ($35/mo for 350k sessions), and Scale ($149/mo for 1m sessions). This volume-based pricing is significantly more cost-effective than standard legacy replay tools, and custom enterprise plans are available for volumes exceeding 1,000,000 monthly sessions.
Save countless customers in minutes.
Integrate our lightweight SDK to automatically record user drop-offs and compile exact, high-fidelity context packets.
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import { Rejourney } from '@rejourneyco/react-native';Rejourney.init('pk_live_your_public_key');Rejourney.start();