AI testing platform Raga AI launched its newest product RagaAI Catalyst, an open-source tool for AI developers, data scientists and product managers to help them observe, evaluate and debug AI agents and LLM outputs. RagaAI Catalyst will help evaluate any stage of Agentic AI workflow.
“We’ve just launched on Product Hunt! This is super exciting for us and the AI industry as a whole,” said Gaurav Agarwal, founder and CEO of RagaAI, in a Linkedin post.
Agarwal explained the need for debugging agents owing to a number of unforeseen failures in the past. “AI Agents are becoming more powerful, but they often fail in unexpected ways, from an LLM-based customer support bot hallucinating refund policies to a multi-agent research system generating contradictory responses,” he said.
Catalyst simplifies the debugging process with experiment management & red teaming to assess agent behavior. It has a user-friendly dashboard featuring execution timelines and graph views, and advanced observability & analytics to track, refine, and maintain consistent performance.
The product has garnered over 15K stars on GitHub repo.
RagaAI Catalyst can also handle multi-agent interactions via a Catalyst tracer which is built to handle every single component in a multi-agentic pipeline.
From Ola, NVIDIA to Raga
RagaAI has raised a total of $4.7 million in funding to date. Pi Ventures led the funding round with participation from Anorak Ventures, TenOneTen Ventures, Arka Ventures, Mana Ventures, and Exfinity Venture Partners.
The startup began with the idea of building the world’s first automated platform for detecting AI issues, diagnosing and fixing them.
RagaAI was founded by Agarwal in January 2022, drawing on his strong foundation in computer vision and machine learning. He previously worked at Texas Instruments and later led the mobility business at Ola before joining computing giant NVIDIA.
“At Ola & NVIDIA, I saw the significant consequences of AI failures due to lack of comprehensive testing. Our Foundation Models “RagaAI DNA” is already solving this problem across large fortune 500 companies,” said Aggarwal, in an earlier exclusive interview with AIM.
