Verdigris integrates IoT energy meters, cloud software and AI to deliver real-time, circuit-level energy monitoring and data analysis for enterprises with substantial carbon emissions. Their happiest customers care about three things: Who makes it the easiest to ensure data quality? Who can deploy at scale the fastest? And whose data is ready for the AI applications to come?
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Verdigris was founded in 2011 to help solve the global problem of energy waste. Their vision is to bring AI-powered energy intelligence to every building in the world.
Today, Verdigris’ focus is on providing enterprises with substantial carbon emissions, such as data centers and 24/7 facilities, with real-time, circuit-level energy monitoring and data analysis. Customers use Verdigris to improve capital efficiency and reduce risk when making capacity planning decisions; to track, monitor, and reduce Scope 2 emissions; and to maintain compliance with emerging sustainability requirements.
Verdigris differentiates by being purpose-built for fast, cost-effective rollouts; building foolproof data resilience into its products; and providing highly-granular data that is future-proof for AI-enabled targeted analysis and predictive analytics.
In my 15-year career, I haven’t seen a more compelling case for investing in smart building technology.
This session highlights case studies from HH Angus and Manulife, US Green Building Council, the General Services Administration, and Kaiterra, as well as Kilroy Realty on different types of sensors.
Episode 173 of the Nexus Podcast features the Nexus Labs team breaking down some of the top stories from the past 2 weeks relevant to energy managers, facility managers, IT/OT managers, and workplace managers.
Smart building innovation is increasingly driven by the seamless integration of diverse technologies and data models. This session will explore how open communication protocols, unified data models, independent data layers, and ontology alignment can break down silos and enable smarter, more responsive systems.
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