Episode

#168: Cracking the Code on Building Energy Costs With Edgecom Energy

Podcast
Earthlings 2.0 Podcast
Published
Jul 7, 2026
Duration seconds
2082
Processing state
not_requested
Canonical source
https://resourcelabs.co/earthlings-episodes/168-cracking-the-code-on-building-energy-costs-with-edgecom-energy
Audio
https://op3.dev/e/episodes.captivate.fm/episode/5ba3fca3-bb12-4d16-9617-9382c078c1f5.mp3
JSON
/v1/public/podcasts/earthlings-2-0-podcast-4600078/episodes/168-cracking-the-code-on-building-energy-costs-with-edgecom-energy
Markdown
/podcast/earthlings-2-0-podcast-4600078/168-cracking-the-code-on-building-energy-costs-with-edgecom-energy.md

Actions

  • POST https://stenobird.com/v1/public/podcasts/earthlings-2-0-podcast-4600078/episodes/168-cracking-the-code-on-building-energy-costs-with-edgecom-energy/transcription-requests
    Idempotently request low-priority transcript generation for this episode.
  • GET https://stenobird.com/podcast/earthlings-2-0-podcast-4600078/168-cracking-the-code-on-building-energy-costs-with-edgecom-energy.md
    Read the agent-friendly Markdown representation of this episode resource.

Summary

In this episode of Earthlings 2.0 , we speak with Behdad Bahrami, CEO of Edgecom Energy, about how artificial intelligence is changing the way industrial facilities manage electricity. As energy prices become more volatile, AI data centers drive unprecedented demand on the electric grid, and utilities introduce increasingly complex pricing structures, manufacturers and other large energy users need better visibility into how and when they consume electricity. Behdad explains how Edgecom's AI-powered energy management platform combines utility billing, real-time energy monitoring, grid signals, and predictive analytics to help industrial facilities reduce costs, improve operational efficiency, and make smarter energy decisions. The conversation explores industrial energy management, demand response, grid modernization, AI-powered energy optimization, and why energy should be treated as a controllable business cost rather than a fixed expense. Key Points: AI is making industrial energy management more proactive – By combining real-time facility data with utility pricing, demand response programs, and predictive AI models, industrial facilities can identify inefficiencies, automate energy decisions, and reduce electricity costs. Industrial facilities have significant untapped opportunities to improve energy efficiency – Many manufacturers still rely on fragmented utility bills and limited energy monitoring, making it difficult to understand where electricity is being used or where savings can be achieved. Greater visibility enables better operational and financial decisions. The growth of AI data centers is accelerating the need for a smarter electric grid – As electricity demand rises, utilities, manufacturers, and large commercial facilities will need better energy orch…