The Fifth Elephant
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The Fifth Elephant Pune edition

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Himanshu Agrawal

Agentic Intelligence Fabric for Smart Buildings

Submitted Dec 4, 2025

Indicate the track in which your submission fits: Track 2: AI in Manufacturing & Digital Transformation Type of submission: 30 mins talk

Session Overview

Smart buildings today generate massive volumes of energy, occupancy, environmental, and asset data—but organizations still struggle to turn these signals into reliable, automated decisions. Traditional analytics or rules-based workflows cannot keep up with the complexity, leading to inconsistent operations, missed insights, and systems that are difficult to scale or trust in mission-critical environments.

This session introduces the Agentic Intelligence Fabric, a new architectural approach that brings trustworthy and coordinated AI intelligence to modern building systems. By combining multi-agent collaboration, structured memory, and built-in governance mechanisms, the framework enables AI agents to reason across building subsystems, detect issues earlier, and support high-quality decisions without constant human oversight. This creates a foundation for stable and consistent automation across energy, occupancy, environmental, and asset domains.

Attendees will learn how real-time telemetry moves through this architecture, how agents coordinate during complex workflows, and how the system enables safer, more reliable, and more efficient building operations at scale. The approach is designed to align with real-world enterprise requirements and demonstrates a practical path toward next-generation building intelligence.

Key Takeaways

How multi-agent AI systems can unify intelligence across energy, occupancy, environmental, and asset operations within a single automation layer.

How trust layers and memory structures reduce inconsistencies and support reliable, repeatable AI-driven workflows.

How real-time building data combined with coordinated AI agents enables proactive optimization, anomaly detection, and mission-critical decision support.

Target Audience

  • AI and LLM practitioners interested in agent-based architectures for real-world deployments.

  • Smart-building and IoT teams seeking more reliable and automated decision systems.

  • Facility, energy, and operations leaders looking for scalable intelligence across complex building portfolios.

Speaker Bio

Himanshu Agrawal is an AI Data Scientist at Johnson Controls, where he develops advanced AI-driven solutions for smart-building ecosystems. His work spans multi-agent architectures, predictive modeling, and intelligent automation. He brings hands-on experience across large language models, applied machine learning, and distributed AI systems. Himanshu holds a Master’s degree in Data Science from IIIT Bangalore and a Bachelor’s degree in Computer Science.

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