Side-by-side comparison of AI visibility scores, market position, and capabilities
Battery intelligence platform for EV and energy storage analytics. Berkeley, CA. Provides battery data analytics for OEMs, fleets, and energy storage operators to extend battery life.
Voltaiq is a Berkeley, California-based battery intelligence software company that provides data analytics and AI-powered insights for organizations managing lithium-ion battery systems. Founded in 2012, Voltaiq serves EV manufacturers, commercial fleet operators, battery manufacturers, and energy storage system operators who need to understand battery performance, predict degradation, and optimize battery utilization over the asset lifecycle.\n\nThe platform collects and analyzes battery telemetry data at high resolution, applying machine learning models to detect anomalies, predict remaining useful life, and identify systemic quality or design issues across battery packs. For EV fleet operators, Voltaiq's analytics enable proactive battery management that extends pack life, reduces warranty costs, and improves vehicle availability by predicting failures before they occur.\n\nVoltaiq's customers include automotive OEMs, battery manufacturers, and commercial fleet operators with large EV deployments. As battery costs remain the single largest component of EV total cost of ownership, analytics that extend battery life and improve second-life asset value represent significant financial value. Voltaiq's independent, hardware-agnostic position allows it to analyze batteries from any manufacturer, making it a flexible intelligence layer across heterogeneous EV fleets.
a2z Radiology AI raised $20M in 2025 for its whole-body AI that simultaneously screens for 24+ conditions across CT scans — from incidental cancers to cardiovascular risk — in a single automated read.
a2z Radiology AI has developed a whole-body CT analysis platform that simultaneously screens for over 24 medical conditions across a single CT scan, including incidental cancers, coronary artery disease, aortic aneurysm, bone density loss, and organ abnormalities. The AI acts as a second reader that radiologists can use to catch incidental findings that fall outside the primary reason for a scan — a major source of missed diagnoses.
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