Agent tracing
Collect traces to inspect how an agent behaved across a run, which helps teams understand failures that do not show up in ordinary application logs.
PandaProbe
RevendiquerChirpz AI is an applied AI lab building PandaProbe, an open-source platform for tracing, evaluating, and monitoring AI agents in production. It is aimed at teams that need better observability and debugging for agent workflows.
Overview
Chirpz AI is an applied AI lab focused on agent engineering. Its public-facing product is PandaProbe, an open-source agent engineering platform for traces, evals, and monitoring.
The site frames the product around a specific gap: AI agents need tooling for tracing, evaluation, and monitoring because they fail in ways that differ from traditional software and standalone LLMs. Chirpz AI says PandaProbe is built to help teams debug agents, improve them, and ship them with more confidence.
Features
Evals for agent workflows
Evaluate agent behavior so teams can compare outputs and judge changes instead of relying on ad hoc manual review.
Production monitoring
Monitor agents in production to watch for failures and quality regressions after deployment.
Observability-first design
Treat observability as a first-class concern so debugging and improvement happen around the agent lifecycle rather than as an afterthought.
Open-source product model
Use an open-source platform, which the company says it chose because transparency is foundational to the product.
Use Cases
Debugging production failures
Inspect agent traces to understand why a run failed, where behavior diverged, and what happened before an unexpected outcome.
Evaluating changes
Compare agent outputs with evals when changing prompts, models, or workflows so you can assess whether the change improved behavior.
Ongoing production monitoring
Track agent behavior in production to spot regressions and monitor reliability over time.
Open-source observability setup
Adopt an open-source agent engineering platform when transparency and inspectability matter to the team.
Pros and Cons
Pros
- Clear focus on agent engineering rather than generic AI tooling.
- Explicit emphasis on traces, evals, and monitoring for production use.
- Open-source positioning may appeal to teams that want transparency.
- Company states that product and research inform each other.
Cons
- The pricing page currently returns a 404 in the provided evidence, so pricing details are not available.
- The source does not list concrete integrations or workflow-specific setup details.
FAQ
What is Chirpz AI's product?
Chirpz AI presents PandaProbe as its product, an open-source agent engineering platform for traces, evals, and monitoring. The site describes it as a tool for debugging, evaluating, and improving AI agents in production.
What problem does it focus on?
The site says the team builds products and publishes research in agent engineering. Their stated focus is the gap between prototype and production for AI agents, especially observability, tracing, evaluation, and monitoring.
How is it priced?
The source text does not describe a public signup flow, pricing tiers, or paid plans. The pricing page currently returns a 404, so pricing details are not available from the provided evidence.
Does it integrate with other tools?
PandaProbe is described as open source from day one, and the site links to GitHub and the pandaProbe.com domain. Beyond that, the provided sources do not list specific integrations.
Quick Facts
- Category
- Developer Tool
- Product
- PandaProbe
- Company
- Chirpz AI
- Positioning
- Applied AI lab
- Primary focus
- Agent engineering, observability, evaluation, monitoring
- Source domain
- chirpz.ai
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