David Drai

Anodot provides autonomous business monitoring powered by AI, using time-series anomaly detection algorithms to continuously monitor business metrics including revenue, usage, and operational KPIs across enterprise data sources and alert teams to significant deviations before they become customer-visible incidents. The Herzliya company machine learning models learn seasonality, trends, and normal variance patterns for each metric automatically, reducing alert noise by filtering out expected variation and surfacing only genuine anomalies.\n\nThe company raised approximately $66 million in venture funding including a Series C from investors including Aleph VC, Redline Capital, and Transformative AI. Anodot serves telecommunications, fintech, gaming, and digital media clients including T-Mobile, Pandora, and Wix, deploying monitoring across billions of data points daily across client environments. The platform connects to data warehouses, streaming pipelines, and cloud monitoring sources through native integrations.\n\nAnodot competes in the AIOps and business monitoring market against Datadog, New Relic, and Sumo Logic for infrastructure monitoring use cases, and against business intelligence anomaly detection features in Tableau, Looker, and Power BI for business metric monitoring. Its focus on business-layer metric anomaly detection rather than infrastructure-layer monitoring differentiates it in the revenue operations and product analytics segments, where engineering-focused monitoring tools are insufficient for the metric breadth and business context that business operations teams require.