Star Metro - Encycle Unveils Chorus AI - Leading Facility Teams into the Age of Agentic Workflows

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Encycle Unveils Chorus AI - Leading Facility Teams into the Age of Agentic Workflows

THINGS TO KNOW 13.04.2026

Encycle Unveils Chorus AI - Leading Facility Teams into the Age of Agentic Workflows

Chorus AI, a conversational interface empowering facility teams to quickly access real-time HVAC health insights, drives faster issue resolution across entire portfolios.

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SAN MARCOS, CA / ACCESS Newswire / April 13, 2026 / Encycle Technologies, Inc., the leader in artificial intelligence and data analytics for commercial HVAC management, announces the launch of Chorus AI^™, a collaborative agentic add-in for Swarm Chorus^™, enhances workflow efficiency for facility managers through desktop environments.

Powered by generative AI and built on more than two decades of HVAC data and operational expertise, Chorus AI represents a new class of agentic desktop integration. By combining large language models, machine learning, and expert systems, the platform delivers an unparalleled user experience in facility and energy management.

At the core of Chorus AI is the power of a question. By pairing natural language interaction with one of the most extensive sub-metered HVAC performance datasets in existence, the assistant transforms how teams engage with maintenance issues and workflows. Users can instantly gain insights, diagnose issues, and take action through a simple conversational interface, eliminating the need to navigate multiple systems or manually interpret complex data.

"Chorus AI will usher facilities teams into a world of live, interactive data assessments for the built environment," said Ana-Paula Issa, CEO of Encycle. "By combining 20 plus years of HVAC performance data with our latest AI models, we are enabling faster decisions, more accurate actions, and better outcomes across entire maintenance workflows."

For facility and energy teams long challenged by the disparate systems conundrum, Chorus AI introduces a new way forward by bringing multiple enterprise data sources, portals and workflows into a single, chat driven desktop interface.

Key capabilities include:

Conversational access to HVAC performance and fault data
Intelligent fault diagnosis and actionable insights
Real time guidance for triage and prioritization
Context aware work order and dispatch recommendations
Portfolio level visibility with unit level granularity
Seamless integration with existing maintenance workflows

From identifying root causes to recommending next steps and designed specifically for HVAC fault resolution, Chorus AI translates complex operational data into clear, actionable guidance, empowering facility teams to execute maintenance more efficiently, moving from fault detection to resolution with greater speed, precision, and confidence.

The introduction of Chorus AI reinforces Encycle's commitment to delivering intelligent, scalable solutions that improve operational efficiency, reduce costs, and extend equipment life. By connecting data, analytics, and execution into a single interface, Encycle continues to redefine how HVAC systems are managed in modern commercial buildings.

For more information on Chorus AI or Encycle's solutions, please visit encycle.com or call 1-855-875-4031

About Encycle:

Deploying autonomous intelligence and analytics, Encycle improves commercial HVAC management, energy efficiency and building comfort to reduce operating costs and carbon footprint. As the only utility-endorsed HVAC optimization software, our patented machine learning solutions seamlessly integrate into maintenance workflows. Encycle enables multi-site commercial and industrial companies to maximize efficiency and reach sustainability goals by improving energy use and budgetary spend decisions. For more information about Encycle, visit encycle.com or follow the company on LinkedIn

Media Contact:

Stephanie Gossman
Marketing Coordinator
760-481-7801
[email protected]

SOURCE: Encycle

View the original press release on ACCESS Newswire

P.Lefebvre--SMC

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