Virtual Peaker vs a2z Radiology AI

Side-by-side comparison of AI visibility scores, market position, and capabilities

Virtual Peaker

EmergingEnergy

Demand Flexibility Software

Virtual Peaker provides demand flexibility software that enables utilities to control customer devices and manage grid load using distributed energy resources.

About

Virtual Peaker is an energy software company founded in 2016 that provides a demand flexibility and distributed energy resource management platform for electric utilities. The software enables utilities to enroll customer devices including smart thermostats, water heaters, EV chargers, and battery storage systems in demand response programs, then orchestrate those devices to reduce peak demand, integrate renewable energy, and manage grid constraints. Virtual Peaker's platform supports direct load control programs where utilities can adjust device settings during grid events as well as price-responsive programs where customers shift usage based on time-of-use pricing. The company serves over 50 utility customers across North America and manages millions of enrolled customer devices. Virtual Peaker raised $38M and was later acquired by Itron, a leading utility technology company, to strengthen Itron's distributed energy resource management capabilities. The platform addresses the critical challenge utilities face in managing increasingly complex grids as solar, EVs, and batteries proliferate among customer populations.

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a2z Radiology AI

EmergingEnterprise AI

Medical Imaging AI

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.

About

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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