End-to-end tracing
Capture full agent trajectories, including tool calls, LLM hops, and decision branches, so evaluations have the context needed to score behavior accurately.
PandaProbe
PandaProbe is an open source agent engineering platform for tracing, evaluating, and monitoring AI agents. It helps developers debug agent behavior, score session quality, and watch for regressions across deployments.
Overview
PandaProbe is an open source agent engineering platform for tracing, evaluating, and monitoring AI agents. Its core job is to help developers understand what an agent did, score how it behaved, and catch regressions before they reach users.
The product combines trace capture, evaluation metrics, and monitoring with deployment options that include PandaProbe Cloud and self-hosting. The pricing page also separates the platform into a free open source self-hosted offering and managed cloud plans for individuals, small teams, scaling projects, and larger organizations.
Features
Agent evaluation metrics
Use research-grounded metrics designed for long-running agents to detect uncertainty, score trajectories, and pinpoint where an agent drifts during execution.
Production monitoring
Schedule evaluation runs against production traffic on daily, hourly, or custom cron cadences and watch for regressions as they appear.
Framework and model integrations
Instrument agents from major frameworks with one-line setup, and work with any LLM provider out of the box according to the home page.
Agent-native workflows
Manage traces and evals from the terminal with the PandaProbe CLI, or use the Skill workflow for agent-driven operation without a dashboard.
SDK and custom instrumentation
Support custom instrumentation and Python SDK usage for teams that need to connect PandaProbe to their own stack.
Use cases
Debugging agent execution
Developers can trace agent runs to inspect tool calls, LLM hops, and decision branches when debugging behavior or comparing versions.
Evaluating production agents
Teams can run evals on production traffic to score full sessions, detect uncertainty, and identify where an agent drifts over time.
Monitoring for regressions
Operators can schedule daily or hourly checks and receive alerts when metrics regress across agent versions or deployments.
Starting small and scaling up
Founders and small teams can start on the free Hobby plan or open source self-hosted option, then move to Pro, Startup, or Enterprise as usage grows.
Agent-assisted workflows
Developer teams using coding agents can manage traces and evals through the CLI or skill-based workflow instead of relying only on a dashboard.
Pros and Cons
Pros
- Offers both tracing and evaluation in one platform, which helps connect agent behavior to scoring and monitoring.
- Supports cloud and self-hosted deployment options, including an open source self-hosted path.
- Provides agent-native workflows through a CLI and skill workflow, not only a web dashboard.
- Includes production monitoring with scheduled eval runs and regression alerts.
- Shows a clear pricing path from free hobby use to custom enterprise plans.
Cons
- Framework support and integration depth are only partially documented in the provided source.
- The public pages do not give latency numbers, setup effort, or detailed security and compliance information.
FAQ
What is PandaProbe used for?
PandaProbe is an open source agent engineering platform for tracing, evaluating, and monitoring AI agents. The site highlights structured evals, traces, and metrics so teams can debug agent behavior and catch regressions earlier.
What kinds of workflows does it support?
The home page says PandaProbe supports tracing, evals, and metrics for long-running agents, and the features page highlights support for agent frameworks and LLM providers through integrations and custom instrumentation.
Can I deploy PandaProbe myself?
The site lists Cloud and self-hosted deployment options. The pricing page also says the core platform can be self-hosted for free under the open source offering.
How is PandaProbe priced?
The pricing page shows a free Hobby plan, paid Pro and Startup plans, an Enterprise option, and an Open Source self-hosted option. It also says you can contact the team for a custom plan.
How can I get started or talk to the team?
The site includes a contact page for booking a 15-minute call with the founder and an email address for asynchronous contact, which suggests it is also used for enterprise and product-demo conversations.
Quick Facts
- Category
- Developer Tool
- Product type
- Open source agent engineering platform
- Primary use
- Tracing, evals, and metrics for AI agents
- Deployment
- Cloud and self-hosted
- Website
- pandaprobe.com
- Pricing model
- Free open source option plus paid cloud plans
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