Arize AI, a machine learning (ML) observability and model monitoring platform, announced it has raised $19 million in Series A financing. The round was led by Battery Ventures with participation from previous investors Foundation Capital, Trinity Ventures, The House Fund, and Swift Ventures. Dharmesh Thakker, general partner at Battery Ventures, will join the Arize AI board. Machine learning is the backbone of modern technology, powering artificial intelligence (AI) systems that touch all aspects of life. But these systems are extremely complicated, and many ML practitioners don't have the right tools or telemetry to understand how or why their creations work.

Ali Ghodsi is the Co-founder and CEO of Databricks, responsible for the growth and international expansion of the company. He previously served as the VP of Engineering and Product Management before taking the role of CEO in January 2016. In addition to his work at Databricks, Ali serves as an adjunct professor at UC Berkeley and is on the board at UC Berkeley's RiseLab. Prior to founding Arize AI, she was pursuing a PhD in Computer Vision at Cornell and left to found her YCombinator backed startup, MonitorML. Prior to starting her PhD, she spent time as a software engineer at Uber, Apple, and Tubemogul (acquired by Adobe).

As key functions in our society become more digitized, we come to rely on artificial intelligence (AI) to run these processes. While AI and its specialized forms such as machine learning (ML) are powerful tools, its practitioners generally lack insight into how these tools generate outputs. The lack of explainability and observability prevents AI and ML from being trusted tools in critical areas of human activity, such as getting approved for a loan or undergoing procedures to diagnose a disease. Fortunately, Jason Lopatecki and Aparna Dhinakaran understand the importance of explainability and observability of AI and ML in their prior professional experiences, creating Arize AI as the tool they never had. Arize AI is production-grade infrastructure tool used by developers to monitor, assess, understand how their deployed AI works.

As key functions in our society become more digitized, we come to rely on artificial intelligence (AI) to run these processes. While AI and its specialized forms such as machine learning (ML) are powerful tools, its practitioners generally lack insight into how these tools generate outputs. The lack of explainability and observability prevents AI and ML from being trusted tools in critical areas of human activity, such as getting approved for a loan or undergoing procedures to diagnose a disease. Fortunately, Jason Lopatecki and Aparna Dhinakaran understand the importance of explainability and observability of AI and ML in their prior professional experiences, creating Arize AI as the tool they never had. Arize AI is production-grade infrastructure tool used by developers to monitor, assess, understand how their deployed AI works.