Chirpz AI
To build the infrastructure and tools that make AI agents reliable, observable, and production-ready through agent-centric tracing and evaluations.
At a Glance
- AI Engineers
- Enterprise AI Teams
- Academic Researchers
AI Tools by Chirpz AI
(1)
PandaProbe
AI Agent Observability Platform
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Products & Services
An open-source agent engineering platform that provides traces, evals, and metrics specifically designed for debugging and monitoring AI agents.
An AI-powered literature discovery tool that helps researchers find hidden citations and summarize relevant papers.
Market Position
Positions itself as an open-source, developer-first alternative to proprietary tools like LangSmith, with a specific focus on the unique challenges of 'Agent Engineering' rather than just simple LLM calls.
Leadership
Founders
Sina Tayebati
Founder and CEO of Chirpz AI. Former PhD researcher at the University of Illinois Chicago (UIC), where he focused on robust autonomy, LLMs, and agentic workflows. He has published research in conferences like ICRA and ICLR on topics such as trajectory risk aggregation (TRACER) and conformal abstention for LLMs.
Executive Team
Sina Tayebati
Founder & CEO
PhD researcher in AI and Robotics with expertise in agentic reasoning.
Board of Directors
Founding Story
The company was started by Sina Tayebati during his time as an AI researcher at UIC. Frustrated by the lack of tools to debug complex agentic workflows and the manual effort required for literature discovery, he built the initial version of Chirpz and PandaProbe to automate these processes.
Business Model
Revenue Model
A 'freemium' and open-core model. The core PandaProbe platform is open-source (Apache 2.0), while the Cloud version and advanced features (Pro, Startup, Enterprise) are offered via monthly subscriptions.
Pricing Tiers
Basic tracing and metrics for individual developers.
Advanced features for developers and small teams.
Enhanced security and scale for growing AI startups.
Full support, custom integrations, and dedicated infrastructure.
Target Markets
- AI Engineers
- Enterprise AI Teams
- Academic Researchers
- Debugging multi-step AI agents
- Continuous evaluation of LLM responses
- Automated research and citation management
- Independent AI Developers
- Research Labs using Agentic Workflows