Arize AI, the leader in machine learning (ML) observability and model performance monitoring, today announced that its Bias Tracing tool has been named “MLOps Innovation of the Year” in the fifth annual AI Breakthrough Awards program conducted by AI Breakthrough, a market intelligence organization that recognizes the top companies, technologies and products in the global Artificial Intelligence (AI) market today.
The mission of the AI Breakthrough Awards is to honor excellence and recognize the innovation, hard work and success in a range of AI and machine learning related categories. This year’s program attracted more than 2,950 nominations from over 18 different countries throughout the world.
“In today’s world, it has become all too common to read about AI acting in discriminatory ways and existing solutions built to monitor fairness metrics for ML models lack actionability,” said James Johnson, managing director, AI Breakthrough. “Arize Bias Tracing represents a breakthrough innovation in addressing these challenges, helping monitor and take action on model fairness metrics and helps enterprises quickly get to the bottom of where and why disparate impacts are happening. We extend our sincere congratulations to Arize AI for taking home a well-deserved 2022 AI Breakthrough Award.”
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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. Arize AI acts as the guardrail on deployed AI, providing transparency and introspection into historically black box systems to ensure more effective and responsible AI. To learn more about Arize or machine learning observability and monitoring, visit our blog and resource hub.