Energy and Smart Building Industry Blog

ClassifyAI™ Wins 2024 AI Excellence Award Revolutionizing Multi-Site Commercial IoT with Award-Winning Innovation

AI Excellence Award - Congratulations

ClassifyAI™, the revolutionary Artificial Intelligence tool developed by Phoenix Energy Technologies, has achieved a significant milestone in the company's journey of innovation and transformative solutions. The prestigious Artificial Intelligence Excellence Award by the Business Intelligence Group has been bestowed upon ClassifyAI™, reaffirming Phoenix Energy Technologies' position as an industry leader in innovation and transformative solutions.

Join us at our booths April 7-10 at EEI (booth #600) and ConnexFM (booth #545) to explore the revolutionary capabilities of ClassifyAI™.

All Energy and Facilities Management customers share one common challenge: they struggle to unify all IP-enabled devices across their portfolio (e.g., building controls, sensors, meters, etc.) into a single platform (a single source of truth). Phoenix has been addressing this challenge for over 15 years, offering EnterpriseDX®, a SaaS platform delivering efficiency, insights, and actionable intelligence across Fortune 500 businesses.

The crux of this article explores the technical hurdles of data integration and unveils ClassifyAI™, a revolutionary Artificial Intelligence tool carefully developed by Phoenix Energy Technologies. This tool empowers the rapid discovery and classification of data points from myriad sources, spanning tens of thousands of locations, in a matter of minutes, all with exceptional accuracy.

In addition to the lack of device integration, customers have little to no access to highly relevant third-party data streams such as weather, utility billing, and CO2 data. Consequently, customers often find themselves unable to make informed decisions regarding energy consumption, occupant comfort, and asset performance, leading them to resort to a “break-fix” model for managing these assets. Phoenix Energy Technologies has built a best-of-breed reputation over the last 15+ years, with multiple Fortune 500 businesses by enabling our customers to transition to a data-driven, asset management practice without needing to invest capital in new equipment. More specifically, Phoenix’s SaaS platform, EnterpriseDX®, has consistently delivered three key value propositions:


1.       Collect: Phoenix facilitates efficient and comprehensive data gathering by leveraging a large library of software connectors, also known as software gateways. This enables seamless integration with legacy, IP-connected devices empowering users to make informed decisions while maintaining data privacy and security.


2.       Analyze: Phoenix software applications and Business Intelligence reporting provide highly valuable, nuanced views into energy, asset, and comfort metrics, enabling proactive decision-making for enhanced operations.


3.       Act: EnterpriseDX enables the user to automatically make schedule, setpoint, and subsystem setting changes, easily from one seamless, cloud-hosted platform. This enables proactive optimization of operations, risk mitigation, and energy conservation measures for increased efficiency and asset value.



This article delves into the technical challenges inherent with the “Collect” or data integration value proposition and how Phoenix addresses them with ClassifyAI™ . This AI tool rapidly discovers and classifies data points from numerous sources, spanning tens of thousands of locations, in a matter of minutes, all while maintaining exceptional accuracy.

The process of connecting to multiple building management systems and IoT devices to provide a unified view of the data is undeniably complex. This complexity arises from a myriad of factors, including differences in vendors and their specific product and firmware versions, as well as variations in commissioning protocols, both on the hardware and software fronts. These discrepancies create a formidable barrier to gaining a clear understanding of building operations and effectively interpreting the wealth of data streams that exist within such systems.

Recognizing the intricate nature of this challenge, Phoenix has taken a significant step forward by expanding its existing ability to integrate disparate device data with ClassifyAI, a revolutionary data tool that leverages Machine Learning to rapidly translate -- discover and classify -- data from these fragmented and disparate systems. Its core function revolves around harmonizing these descriptions to present a coherent, unified view of the underlying data.

What sets ClassifyAI apart is its foundation on Machine Learning algorithms and a proprietary dataset, which allows it to tackle the scale and complexity of integrating diverse building management systems head-on. This both simplifies and accelerates the data integration process by several orders of magnitude. What is particularly remarkable is that ClassifyAI achieves this without needing detailed data mapping, significantly reducing the time required to transition from system connectivity to live operations, the “Analyze” and “Act” value levers mentioned above.

ClassifyAI stands as a testament to Phoenix's commitment to overcoming the challenges posed by the diversity and complexity of building management systems and Phoenix’s continued support for legacy BAS systems. Calculations recorded on a flagship customer include the processing of 50,000 data points in 30 minutes, equating to approximately 1700 data points per minute. ClassifyAI returned initial results for this customer’s stores in less than 2 minutes with 99%+ accuracy. In essence, the time and speed benefits enabled by ClassifyAI open doors to a more streamlined and efficient approach to handling building operations data, ultimately enhancing the ability to make informed decisions and optimizing building performance. 

Phoenix Energy Technologies has taken a careful approach to deploying AI tools by applying an extra layer of scrutiny to our evaluation of the use case, desired outcomes, and different methods of achieving these outcomes, while balancing the risks of different technical approaches. In all cases, the technology must be “fit for purpose”; we do not deploy “AI” for the sake of AI because it is popular and the latest shiny object. In the case of ClassifyAI, especially with our larger customers with store portfolios exceeding 15K locations, we found the perfect balance of performance, cost, and risk using an Artificial Intelligence toolset that takes advantage of the significant training data Phoenix Energy Technologies has gathered from over 15 years of operations. This approach not only exemplifies our accumulated expertise in driving innovation but also underscores our commitment to delivering transformative solutions that redefine industry standards.


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