Arize AI Secures $70M Series C to Expand AI Observability and LLM Evaluation

BERKELEY, Calif., Feb. 21, 2025 — Arize AI, a leader in AI observability and LLM evaluation, has announced a $70 million Series C to accelerate its mission of making AI work reliably in production. The round—the largest-ever investment in AI observability—was led by Adams Street Partners, with participation from M12 (Microsoft’s venture fund), Sinewave Ventures, OMERS Ventures, Datadog, PagerDuty, Industry Ventures, and Archerman Capital. Existing investors Foundation Capital, Battery Ventures, TCV, and Swift Ventures also reaffirmed their confidence in Arize’s vision.

AI adoption is skyrocketing—business spending surpassed $13.8 billion in 2024, with 68% of enterprises planning to invest between $50 million and $250 million in generative AI in 2025. Yet, while AI models are more powerful than ever, most LLMs struggle to perform reliably in real-world applications like voice assistants. A growing number of cutting-edge AI models are trained and optimized using synthetic data—data generated by other AI models rather than real-world sources. But what happens when those models can’t accurately evaluate the results of their own synthetic data?

In a research effort called OpenEvals, Arize has demonstrated that LLMs struggle to reliably assess correctness of synthetic datasets compared to non-synthetic data—a major blind spot as enterprises rush to scale generative AI. These findings highlight serious risks in AI model training and self-improvement loops, where unchecked errors in synthetic data can compound over time. For engineering teams, LLMs are still a black box—unpredictable, difficult to troubleshoot, and prone to failures that can derail entire projects.

As the industry grapples with these challenges, AI engineers need better tools to ensure their models aren’t building on faulty foundations. With Arize’s AI observability and LLM evaluation platform, teams can test, troubleshoot, and course-correct AI systems before failures escalate into real-world consequences. This is especially important as enterprises race to implement semi-autonomous multi-agent systems, voice assistants, and increasingly sophisticated consumer-facing AI applications.

“Building AI is easy. Making it work in the real world is the hard part,” said Jason Lopatecki, CEO and Co-Founder of Arize AI. “Enterprises can’t afford to deploy unreliable AI. Engineering teams need better infrastructure to test, evaluate, and troubleshoot their models before they impact customers. That’s exactly what Arize delivers—whether through our enterprise platform, Arize AX, or our open-source offering, Arize Phoenix.”

“As AI research and real-world applications accelerate, Arize will continue to pioneer new tools, like our recent first-to-market launch of audio evaluation for voice assistants, to help engineers working on these systems better evaluation, debug, and improve what they build,” added Aparna Dhinakaran, Chief Product Officer and Co-Founder of Arize.

Since launching in 2020, Arize has become an AI observability and evaluation backbone for the world’s top enterprises and government agencies—including Booking.com, Condé Nast, Duolingo, Hyatt, PepsiCo, Priceline, TripAdvisor, Uber, and Wayfair, among hundreds more. Arize Phoenix, the company’s open-source offering, has emerged as the most widely adopted AI observability and evaluation library for development, with over two million monthly downloads.

Arize’s partnership with Microsoft is also expanding, with M12’s investment reinforcing a long-standing collaboration. The company recently launched deeper integrations with Azure AI Studio and the Azure AI Foundry portal, SDK, and CLI, making it easier than ever for AI engineers to integrate observability and evaluation into their workflows.

“We believe AI observability is the missing piece in making AI truly enterprise-ready,” said Fred Wang, Partner at Adams Street Partners. “As AI adoption accelerates, companies need robust, cohesive tools to ensure their AI systems are performant, reliable, and aligned with business goals. Through our research and diligence in this market, we believe Arize AI has built the category-defining platform for AI observability and evaluation, trusted by leading enterprises and AI-first organizations. We’re excited to support their vision as they scale to meet the growing demand for production-grade AI.”

“Arize AI’s innovative approach to AI observability and LLM evaluation is transforming the way enterprises deploy and manage AI systems. Our investment reflects our confidence in their ability to set new standards in the industry and empower AI engineers and developers to achieve real-world results,” said Todd Graham, Managing Partner at M12.

“Tripadvisor’s billion-plus reviews and contributions are becoming even more important in a world of AI search and recommendations where travel experiences are more conversational, personal and even agentic. As we build out new AI products and capabilities, having the right infrastructure in place to evaluate and observe AI is important. Arize has been a valuable partner on that front,” said Rahul Todkar, Head of Data and AI at Tripadvisor.

“With GenAI, we’re facilitating more tailored experiences that adapt and respond to travelers’ needs faster than ever before. As we continue to innovate, our technical teams blend an approach of pioneering new tools in-house and using platforms like Arize to help in testing, evaluating and tracing new AI-powered applications and workflows,” said Jeroen Hofman, ML Engineering Manager at Booking.

“Arize AI deserves a lot of credit for pioneering AI observability and creating a de facto standard for enterprises that want to achieve real-world results with generative AI,” said Brett Wilson, General Partner at Swift Ventures. “We’re proud to continue to back the company as it scales.”

About Arize

Arize AI is a unified AI observability and LLM evaluation platform that helps teams develop and maintain more successful AI. Arize’s automated monitoring and observability platform allows teams to quickly detect issues when they emerge, troubleshoot why they happened, and improve overall performance across both traditional ML and generative use cases. Arize is headquartered in Berkeley, CA.

Source: Arize AI