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PandaProbe Cloud

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Build, evaluate, and monitor LLM agents with deep tracing

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Tracked since2026
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The Bottom Line

Entry price

Free plan available, paid tiers above

Biggest pro

Open-source core allows for self-hosting and full control without limitations.

Biggest con

Requires some technical knowledge for setup and instrumentation, especially for custom agents.

TL;DR - PandaProbe Cloud

  • Provides comprehensive tracing for LLM agent behavior, capturing every decision and interaction.
  • Offers state-of-the-art evaluation metrics to detect agent uncertainty and score trajectories over long runs.
  • Enables proactive monitoring and regression detection with scheduled eval runs and alerts.
Pricing: Free plan available
Best for: Growing teams

What is PandaProbe Cloud?

Editorial review
PandaProbe is an open-source agent engineering platform designed to help developers build, evaluate, and monitor large language model (LLM) agents safely and effectively. It provides comprehensive tracing capabilities to capture every LLM call, tool invocation, and agent decision, offering deep insights into agent behavior. This detailed tracing forms the foundation for its state-of-the-art evaluation metrics, which are purpose-built for long-running agents to detect uncertainty, score trajectories, and pinpoint behavioral drift. The platform is ideal for developers and teams working with LLM agents who need to understand, debug, and improve their agent's performance. It enables users to catch regressions before they impact end-users by scheduling automated evaluation runs against production traffic and setting up alerts for metric regressions. PandaProbe integrates seamlessly with major agent frameworks and leading LLM providers, offering both cloud-hosted and self-hosted deployment options, and even provides a CLI and skill for coding agents to manage its features directly.

Pros & Cons

Pros

  • Open-source core allows for self-hosting and full control without limitations.
  • Provides deep visibility into agent behavior with detailed tracing and nested span hierarchies.
  • Advanced evaluation metrics help identify and address agent uncertainty and performance drift.
  • Seamless integration with popular agent frameworks and LLM providers minimizes setup effort.
  • Monitoring features enable proactive detection of regressions before they affect users.

Cons

  • Requires some technical knowledge for setup and instrumentation, especially for custom agents.
  • The full benefits of advanced monitoring and evaluation may require consistent integration into CI/CD pipelines.

Key Features

Full agent trajectory tracing (LLM calls, tool invocations, decisions)One-line instrumentation for major agent frameworksCompatibility with various LLM providersResearch-grounded evaluation metrics for agent uncertaintyLLM-as-judge scoring with structured feedbackEvaluation of full agent sessions and lifecyclesScheduled evaluation runs against production trafficAlerts for metric regressions across agent versions

Pricing Plans

Pricing checked Jun 15, 2026

Hobby

$0 / forever

  • 100 base trace ingestion / mo
  • 100 trace eval runs / mo
  • 10 session eval runs / mo
  • Human annotation
  • 1 seat
  • Community support via GitHub

Pro

$29 / month

  • Everything in Hobby +
  • 5k base traces / mo, then pay-as-you-go
  • 5K trace eval runs / mo, then pay-as-you-go
  • 100 session eval runs / mo, then pay-as-you-go
  • 2 seats
  • Email support

Startup

$299 / month

  • Everything in Pro +
  • 50k base traces / mo, then pay-as-you-go
  • 50K trace eval runs / mo, then pay-as-you-go
  • 1K session eval runs / mo, then pay-as-you-go
  • 10 seats
  • High rate limits
  • Private Slack channel
  • Data retention management

Enterprise

Custom

  • Everything in Startup +
  • Alternative hosting options (hybrid & self-hosted)
  • Custom SSO
  • Access to dedicated engineering team
  • Support SLA
  • Team trainings & architectural guidance
  • Unlimited seats
  • Dedicated support

Open Source

Free

  • Apache 2.0 license
  • All core platform features and APIs
  • Scalability of PandaProbe Cloud
  • Deployment docs
  • Community support
  • Customization options

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PandaProbe Cloud FAQ

How does PandaProbe Cloud help in testing and quality assurance for AI agents?

PandaProbe Cloud provides advanced evaluation metrics specifically designed for long-running agents, helping to detect uncertainty, score trajectories, and pinpoint behavioral drift. It enables users to schedule automated evaluation runs against production traffic and set up alerts for metric regressions, catching issues before they impact end-users.

What kind of user or team benefits most from PandaProbe Cloud?

PandaProbe Cloud is ideal for developers and teams working with LLM agents who need to understand, debug, and improve their agent's performance. It is particularly useful for those who require deep insights into agent behavior and robust evaluation capabilities.

How does PandaProbe Cloud compare to LangWatch for monitoring LLM agents?

PandaProbe Cloud offers comprehensive tracing capabilities to capture every LLM call, tool invocation, and agent decision, providing deep insights into agent behavior. It also features advanced evaluation metrics purpose-built for long-running agents to detect uncertainty and behavioral drift, alongside seamless integration with major agent frameworks and LLM providers.

What are the main trade-offs when implementing PandaProbe Cloud?

Implementing PandaProbe Cloud requires some technical knowledge for setup and instrumentation, particularly for custom agents. Additionally, realizing the full benefits of its advanced monitoring and evaluation features often necessitates consistent integration into CI/CD pipelines.

Does PandaProbe Cloud include a free tier?

Yes, PandaProbe Cloud is available on a free tier. Paid plans are offered for users requiring more usage and additional features beyond the free offering.

Can PandaProbe Cloud integrate with existing agent frameworks and LLM providers?

Yes, PandaProbe Cloud integrates seamlessly with major agent frameworks and leading LLM providers. This minimizes setup effort and allows for deep visibility into agent behavior with detailed tracing and nested span hierarchies.

How does PandaProbe Cloud provide deep visibility into agent behavior?

PandaProbe Cloud offers comprehensive tracing capabilities that capture every LLM call, tool invocation, and agent decision. This detailed tracing forms the foundation for understanding and debugging agent performance, providing deep insights into how agents operate.

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