Agent Observability

See everythingyour agents do

Observability and continuous quality monitoring. Monitor your agents in real-time, trace complex multi-agent workflows, and optimize performance.

Trace #a3f8c2d
Customer support agent · 1.5s total
SUCCESS2 min ago
inputUser Query
0ms
llmIntent Classification
120ms
retrievalKnowledge Retrieval
85ms
functionContext Assembly
12ms
llmGPT-4o Generation
1,240ms
guardrailSafety Check
45ms
outputResponse Delivery
3ms
Deep observability

Monitor every layer of your AI

From individual LLM calls to complex multi-agent orchestrations gain complete visibility into your AI system's behavior.

Visual Trace Explorer

See every step of your multi-agent workflows LLM calls, tool invocations, retrieval steps, and handoffs rendered as an interactive visual trace.

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Real-Time Debugging

Track and debug live issues as they happen. See request/response payloads, latencies, error stack traces, and token usage for every span.

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Online Evaluations

Measure quality on real-time agent interactions. Score generations, tool calls, and retrievals automatically using custom evaluation criteria.

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Smart Alerts & Guardrails

Set up real-time alerts for quality regressions, latency spikes, error rate increases, and safety violations. Integrate with Slack, PagerDuty, and more.

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Session Replay

Replay entire user sessions to understand the full context of agent interactions. See exactly what the user experienced and how the agent responded.

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Latency Waterfall

Identify bottlenecks with detailed latency breakdowns for every step. See where time is spent across model inference, tool execution, and retrieval.

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Production-grade observability

Built for the most demanding AI workloads. Trace millions of requests with minimal overhead and maximum insight.

Distributed tracing across services
Custom span attributes
Automatic instrumentation SDKs
OpenTelemetry compatibility
Log correlation
User session grouping
Export to Datadog & Grafana
Retention policies & archival
observability.py
# Auto-instrument your agent
from intercept import observe
@observe("support-agent")
async def handle_query(user_input):
# Intent classification
intent = classify(user_input)
# Knowledge retrieval
context = retrieve(intent)
# Generate response
response = generate(context)
return response
# Every step → auto-traced ✓

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