AI startup Fiddler Labs raised Strategic Investment from Amazon Alexa Fund

Fiddler, a California based provider of a monitoring solution, has now received a strategic investment fund the Amazon Alexa Fund. The amount of the deal was not disclosed.

Fiddler is founded by the Krishna Gade in the year 2018. The company recently launched its Machine Learning Monitoring Suite, with capabilities including detecting data changes, anomalies and ensuring that data integrity is maintained.

Those capabilities are paired with its Explainable AI platform to explain, analyze, and resolve MLOps production monitoring issues.

Fiddler's Founder & CEO, Krishna Gade, said, "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. 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."

Zain A. Gulamali of the Amazon Alexa Fund, said, "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. 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."

The company, as of now has plans to use the new funds to accelerate explainable AI and ML monitoring capabilities with its 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 make sure high performing, transparent, and responsible AI solutions.