Fiddler Secures Strategic Investment from Amazon Alexa Fund to Accelerate AI Explainability

Investment to enhance explainable AI and ML monitoring capabilities with the goal of democratizing responsible AI development.

 Fiddler announced a strategic investment by the Amazon Alexa Fund to advance its explainable monitoring solution. Fiddler and the Alexa Fund will collaborate to advance actionable insights in AI, giving businesses complete and continuous visibility into their production AI systems to ensure high-performing, responsible, and transparent AI solutions.

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Fiddler recently launched its ML Monitoring suite, with capabilities including detecting data changes and anomalies, and ensuring that data integrity is maintained. These capabilities are coupled with Fiddler’s industry-leading Explainable AI Platform to efficiently and effectively explain, analyze, and resolve MLOps production monitoring issues.

“AI models help businesses get powerful insights, but these models are only effective forecasters if users are able to understand how their models work and if they are trustworthy and reliable over time,” says Fiddler’s Founder & CEOKrishna Gade. “Fiddler is the first startup to bring true explainability and continuous monitoring to the enterprise, enabling companies to effectively and responsibly manage their AI solutions at scale. An Explainable ML Monitoring system extends traditional monitoring to provide deep model insights with actionable steps. Users are able to understand the problem drivers, root cause issues, and analyze the model to prevent repeat issues.”

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“Fiddler is building services that are key to the evolution of explainable AI, as the company works to demystify the ‘black box’ of AI in industry verticals including financial services and social networking,” said Zain A. Gulamali of the Amazon Alexa Fund. “The Fiddler team is one of the strongest we’ve seen positioned to tackle this challenge, and we are excited to support the company as it continues to grow and address explainable AI in areas such as voice and conversational interfaces.”

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