Agent operations
Your agents, in context.
Follow an agent's release history, retained context and execution traces from one place. Bract makes the steps between shipping and understanding an agent easier to see.
Release history
Know which version a run belongs to.
Persistent memory
Keep agent context across sessions.
Execution traces
Inspect what happened, step by step.
The product
See the whole story of an agent run.
An agent's behavior is shaped by its version, the context it remembers and the calls it makes. Bract brings those records together so you can move from an outcome back to the steps that produced it.
Know what changed.
Keep a clear record of agent versions and deployment activity.
Keep useful context.
Store and retrieve agent-scoped information between runs.
Understand each step.
Inspect recorded activity in a trace view built for agent workflows.
A connected workflow
From your code to a running agent.
- 01
Bring your agent
Package a Python HTTP agent and keep your model provider of choice.
- 02
Deploy with a health check
Follow the build, startup and readiness of each version.
- 03
Invoke and understand
Call the agent and inspect its trace and saved context.
Get started
Build with the full picture.
The quickstart takes you from a Python agent artifact to its deployment and first trace.