Request logs you'll actually use
Debug AI requests instantly with detailed logs, timelines, and full payload inspection. Track failover, tokens, and errors.
Visual
Debugging journey
From incoming request to searchable logs and performance metrics.
Incoming request
API call with keys and payload
ModelRiver processes
Routing + failover logic
AI provider processes
Model generates response
Response returned
Data + token counts
Request log stored
Indexed, searchable, replayable
Timeline visualization
See the full request journey
Visualize the entire lifecycle of your AI requests with interactive timelines. Track failover attempts, callback responses, and provider retries with visual indicators showing success, failure, and timing.
Full payload inspection
Deep data exploration
Inspect complete request and response payloads with syntax-highlighted JSON. Collapsible tree views make it easy to navigate complex nested structures and find exactly what you need.
Provider & model tracking
Know what ran where
Every log shows which provider and model handled the request. See backup attempts when primary providers fail. Track which models work best for your use cases.
Token & cost analytics
Track usage & expenses
See exact token counts for every request: prompt tokens, completion tokens, and total usage. Calculate costs per request and track spending patterns across different models.
Advanced debugging capabilities
Production-grade tools for complex troubleshooting
Latency Tracking
Measure request duration down to the millisecond. Identify slow requests and optimize performance. Compare latency across providers and models.
Error Diagnostics
Get detailed error messages with full context. See which step failed in multi-provider workflows. Access provider-specific error codes and descriptions.
Customer Data Echoing
Cache custom fields from requests and see them in logs. Track user IDs, session IDs, and metadata. Connect logs to your application state for easier debugging.
Filtering & Search
Filter logs by status, provider, model, or workflow. Separate playground tests from production traffic. Search by channel ID, event name, or customer data.
Event Workflow Tracking
Follow event-driven workflows from AI generation to backend callback. See webhook payloads sent to your server. Inspect callback responses and timeout errors.
Real-time Refresh
Logs update automatically as requests come in. No need to manually refresh. See the latest data instantly while debugging active issues.
Debug faster, ship confidently
Real use cases from production teams
Production Issue Resolution
User reports an error? Search logs by their user ID in customer data. See the exact request payload, response, and error message. Reproduce the issue with the same inputs.
Failover Verification
Check if your backup providers are working correctly. Timeline view shows which providers were tried and why they failed. Ensure your redundancy strategy is solid.
Event Callback Debugging
Event-driven workflow not completing? See the webhook payload sent to your backend. Check if the callback was received. Identify timeout issues and fix your integration.
Cost Optimization
Analyze token usage per workflow. Find requests using excessive tokens. Switch to more efficient models based on actual usage data. Track cost savings over time.
Debug less, ship faster
Get complete visibility into every AI request. Stop guessing and start debugging with production-grade logs.