Three Immigrant Women Entrepreneurs that are changing the Dynamics of AI Design

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Tsion Behailu, Aparna Dhinakaran and Manisha Sharma

Arize AI is a start-up with a dynamic founding team, Tsion Behailu, Aparna Dhinakaran, and Manisha Sharma  (along with five others, all over 30). The startup, which enables customers to monitor the performance of AI models using software that looks for things such as unforeseen biases in algorithms, has $24.5 million in funding from Battery Ventures, Foundation Capital, and Trinity Ventures, among others. All three women are immigrant entrepreneurs: Behailu was born in Ethiopia, Dhinakaran in India, and Sharma in Fiji.

Since announcing its seed financing in October 2020, Arize AI has gained traction among enterprises such as Adobe and Twilio that are looking to ensure production models perform as designed in the research and building phase. Other customers include organizations in financial services, fintech, healthcare, insurance, ad tech, retail, and other industries that rely on AI for fraud detection, pricing, demand forecasting, and service delivery optimization.

Arize AI is a Machine Learning Observability platform that helps ML practitioners successfully take models from research to production with ease. Arize’s automated model monitoring and analytics platform helps ML teams quickly detect issues when they emerge, troubleshoot why they happened, and improve overall model performance. By connecting offline training and validation datasets to online production data in a central inference store, ML teams can streamline model validation, drift detection, data quality checks, and model performance management. 

The Arize AI founding executive and engineering teams, composed of industry veterans from industry-leading organizations including Uber, Google, Apple, Slack, Adobe, and PagerDuty have charted a course for the industry’s first full-stack ML observability and model monitoring platform. The platform is the only solution designed specifically for the ML engineers, data scientists, and other practitioners responsible for deploying and maintaining the ML models that drive business decisions and processes.