Real-Time Monitoring
Watch automations execute live with complete visibility into AI decisions and progress
See your automations run in real-time with visibility into every step, decision, and action AI takes.
What It Does
Real-Time Monitoring gives you a live view of automations as they execute. Watch each step happen, see what the AI is thinking and why it made specific decisions, track progress through the process, and catch errors immediately when they occur. Everything AI does is visible and explained, building trust through transparency.
Why It Matters
The biggest barrier to trusting AI in business processes is the black box problem - you don't know what's happening or why. Real-Time Monitoring solves this by making AI work completely transparent. You see every step, understand every decision, and can intervene if needed.
This transparency serves three purposes: building trust (seeing is believing), debugging (identify exactly where problems occur), and learning (understand how AI approaches problems to improve processes).
Business Impact
Reduce the trust gap that prevents AI adoption. Teams that can see AI work in real-time are 3x more likely to adopt automation for critical processes. When mistakes happen, you catch them in seconds instead of discovering them when customers complain.
Monitoring Features
Live Execution View
Watch automations run in real-time with updates appearing within 1 second:
- Activity Stream: Chronological feed of all automation activity across your organization
- Step-by-step Progress: Visual indicators showing completed, running, and upcoming steps
- AI Reasoning: See the thought process behind AI decisions and actions
- Execution Logs: Detailed log output streaming live as automation runs
Error Tracking & Debugging
When errors occur, get immediate visibility into what went wrong:
- Error Details: Full stack traces, error types (validation, timeout, API failures), and severity levels
- Execution Context: See exactly which step failed, input data, and execution state at failure
- Retry Tracking: View multiple error attempts if automation retries after failures
- Error Analytics: Identify patterns in failures, most common error types, and resources with highest error rates
Historical Analysis
Review completed executions for debugging, training, or auditing:
- Execution Replay: Step through past executions to see exactly what happened
- Error History: Filter and search past errors by type, severity, resource, or date range
- Trend Analysis: Visualize error rates, success rates, and execution health over time
- Cost Tracking: See AI usage costs per execution for ROI analysis
How It Works
Execution Begins
When a workflow or agent starts, the monitoring dashboard shows it as active in the Activity Log.
Steps Stream Live
As each step executes, updates appear in real-time (typically within 1 second) via activity stream and execution logs.
AI Reasoning Visible
For decisions the AI makes, you see the thought process (why it chose option A over option B).
Progress Tracking
Visual indicators show which steps completed, which step is running now, and which steps remain.
Error Detection
If something fails, error tracking captures the failure with full stack trace, execution context, and retry attempts. Navigate to Execution Health page to see error analytics and identify patterns.
Historical Replay
After completion, you can replay the entire execution to review what happened, including all errors that occurred.
Use Cases
Common Questions
Can I see monitoring for past executions?
Yes. The Activity Log shows real-time monitoring for active executions and historical replay for completed ones. You can view any past execution to see exactly what happened, including detailed error information with stack traces and retry attempts. Useful for debugging, training, or auditing. We retain execution logs and error tracking data based on your plan (30-90 days for standard plans).
Does monitoring slow down execution?
No. Monitoring data streams in parallel with execution without impacting performance. The automation runs at full speed while sending updates to the dashboard. If you're not watching, the data is still captured for historical review but doesn't slow anything down.
Can multiple team members watch the same execution?
Yes. Real-time monitoring supports multiple viewers watching the same execution simultaneously. Useful for training, team reviews, or having both technical and business stakeholders observe together. Each viewer gets their own dashboard view with the same live data.
How do I find patterns in errors across multiple executions?
Use the Execution Health page which provides error analytics dashboards. See error distribution by type and severity, trends over time, and identify which workflows or agents have the highest error rates. Filter errors by date range, type, or severity to investigate specific issues. This helps identify systemic problems versus one-off failures.
Last Updated: 2025-01-22