Retrace

Debug, replay, and test AI agent workflows with confidence. Retrace is an AI agent debugging and evaluation platform built for developers and engineering teams that want to inspect production agent behaviour, reproduce failures, validate fixes, and prevent regressions before they reach users.

Debug AI Agent Workflows With Replay and Forking

Retrace records every step of an AI agent run, including model calls, tool executions, prompts, responses, and errors. When something goes wrong, you can replay the entire execution, branch from the exact point of failure, modify prompts or tool inputs, and rerun the workflow to verify whether the issue has been resolved.

Whether you're building AI agents with OpenAI, Anthropic, Gemini, or other frameworks, Retrace provides a structured way to investigate failures and improve reliability.

Key Features

Replay & Fork

Reproduce AI agent behaviour from recorded executions.

Replay or branch from:

• Complete agent runs
• Individual model calls
• Tool executions
• Failed workflow steps
• Recorded production traces

to investigate issues without recreating them manually.

Prove-the-Fix Validation

Verify that changes actually resolve failures.

Test updates by:

• Modifying prompts
• Updating tool inputs
• Changing AI models
• Replaying failed traces
• Comparing outcomes

to confirm that fixes are effective.

CI Evaluation Gates

Catch behavioural regressions before deployment.

Integrate automated checks that:

• Validate agent behaviour
• Detect regressions
• Protect production releases
• Support CI pipelines
• Block failing builds

before code reaches production.

Runtime Guardrails

Prevent unstable agent behaviour during execution.

Configure limits for:

• Infinite loops
• Budget thresholds
• Maximum steps
• Runtime constraints
• Agent safety controls

to improve operational reliability.

AI Behaviour Detection

Identify common AI agent failure patterns.

Detection capabilities include:

• Groundedness issues
• Behaviour drift
• Failure clusters
• Multi-agent errors
• Evaluation insights

to help diagnose complex workflows.

Trace Inspection

Understand how every agent decision was made.

Inspect:

• Session history
• Prompt versions
• Tool usage
• Memory state
• Agent topology

through detailed execution traces.

Semantic Search & Collaboration

Work together on debugging complex AI systems.

Teams can:

• Search recorded traces
• Share execution tapes
• Review incidents
• Collaborate on debugging
• Document investigations

from a shared workspace.

Lightweight SDK Integration

Start recording agent traces with minimal setup.

Developer tools include:

• Python SDK
• TypeScript SDK
• Simple decorators
• Fast integration
• Production tracing

for rapid adoption.

Built for AI Agent Testing

Retrace combines execution tracing, replay, forking, behavioural evaluation, regression testing, runtime guardrails, collaboration, and CI integration into one AI agent observability platform.

Key benefits include:

• AI agent debugging
• Prompt testing
• Agent observability
• AI evaluation
• Regression testing

Built For

• AI Developers
• Machine Learning Engineers
• Platform Teams
• DevOps Engineers
• AI Startups
• Engineering Teams

Common Use Cases

• Debugging AI agents
• Investigating production failures
• Testing prompt changes
• Preventing behavioural regressions
• Evaluating multi-agent workflows
• Automating AI quality checks in CI/CD

Why It Matters

AI agent failures can be difficult to reproduce because they often depend on specific prompts, model responses, tool interactions, or execution paths that disappear once a session ends. Retrace solves this by recording every step of an agent run, allowing developers to replay executions, fork from the exact point of failure, test changes, and verify improvements before deployment. With runtime guardrails, behavioural detection, CI evaluation gates, semantic trace search, and collaborative debugging tools, engineering teams can move from reactive troubleshooting to repeatable testing and more reliable AI systems.

Replay, Debug, and Validate AI Agent Workflows

Record every AI model call, tool execution, and prompt interaction, replay production traces, fork from failing steps, validate fixes with side-by-side comparisons, detect behavioural regressions in CI, inspect agent memory and topology, and build more reliable AI applications with comprehensive execution tracing.