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Arize AI Raises $38 Million Series B To Scale Machine Learning Observability Platform

Arize AI, a leader in machine learning observability, announced that it has raised $38 million in Series B funding. TCV led the round with participation from existing investors Battery Ventures, Foundation Capital, and Swift Ventures.

The investment is the largest-ever in a machine learning observability platform and comes at an important inflection point for the industry. Machine learning models are now being deployed in nearly every sector of the economy, with companies investing billions to turn artificial intelligence (AI) and machine learning (ML) into a competitive advantage. Despite a decade of investment in data infrastructure and the pre-production ML toolchain, most companies still lack visibility into how their ML models are performing in production and run the risk of models impacting earnings or acting in unfair ways. This is especially true as the industry embraces computer vision and natural language processing models that are notoriously difficult to troubleshoot since they rely on unstructured data and manual labeling by humans.

Launched in 2020, Arize’s ML observability platform is already counted on by a growing list of enterprises and disruptive technology companies – including Uber, Spotify, Ebay, Instacart, Chime, Neustar, Nextdoor, New York Life, Stitch Fix, and more – to track hundreds of billions of predictions per month. Arize is beloved by ML engineering teams because it enables them to streamline troubleshooting efforts with purpose-built workflows and analytics for model performance management, drift detection, data quality checks, and model validation. Arize also enables users to log models with both structured and unstructured data to the platform for monitoring.

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“Michaelangelo is Uber’s end-to-end ML platform that powers 100% business-critical ML use cases at Uber to deliver a consistent user experience across billions of rides and deliveries,” says Kai Wang, Product Lead, Uber AI Platform. “Given the vital role ML plays in this process, it’s critical to have tools that build on Michalangelo’s core capabilities and help us stay ahead of potential production ML problems. We’re excited to work with Arize AI to enhance platform ML observability capabilities and make it easier to detect and resolve model performance issues.”

“Arize’s platform finally makes it easy for ML engineers to scalably detect data and drift issues, troubleshoot what happened, and improve overall model performance” says Morgan Gerlak, Partner at TCV. “Like other areas of observability, the end user really matters — and we were impressed by Arize’s ability to build a practical solution that ML engineers love.”

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“As the pace of innovation in AI accelerates, it’s more important than ever for organizations to have machine learning observability in place to surface potential problems and improve ML models in production,” says Dharmesh Thakker, a general partner with Battery Ventures. “In the past year, Arize has emerged as one of the highest-profile companies in this space — the platform of choice for many prominent ML teams. We’re proud to expand our investment and partnership with Arize as it pushes into new frontiers.”

“Speaking of observability, I’ve been watching Arize grow since its inception,” says Ashu Garg, general partner at Foundation Capital, “and I’m thrilled at how far the company has come. Its product is far ahead of the competition and is being deployed by best-in-class AI enterprises, which all acknowledge the seriousness of the problem. In two short years, Arize has become the breakout company in its category.”

“The reality is that if you’re not injecting AI into every major business decision, you are going to be left behind,” notes Brett Wilson, Co-Founder and General Partner at Swift Ventures. “Having machine learning observability in place to monitor models and get ahead of potential problems is table stakes, especially in a challenging economic environment. Arize is the category leader in this space and is pushing it to new frontiers.”

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[To share your insights with us, please write to sghosh@martechseries.com]

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