Field Frequency

Hard Truths About EV Charging ROI: Rohan Puri on Making Sites Profitable


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In this episode of Field Frequency, Rohan Puri, co-founder of Stable, breaks down how data and predictive analytics are transforming EV charging from guesswork into a disciplined, ROI-driven business.

The conversation explores how better site selection, utilization forecasting, and dynamic pricing are key to building profitable charging networks—and why the industry must move beyond early deployment habits toward financially sustainable strategies.


Guest: Rohan Puri, Co-Founder, Stable

Overview:

  • Stable provides software to optimize EV charger placement, pricing, and performance
  • Focus on maximizing utilization and accelerating ROI

Key Topics:

  • Why early EV charging deployments missed the mark
  • Importance of data-driven site selection
  • Utilization as the key driver of profitability
  • Dynamic pricing and its growing adoption
  • Common misconceptions (traffic ≠ charging demand)

Industry Insights:

  • High utilization is concentrated in a small number of sites
  • Co-locating chargers can increase usage, not reduce it
  • Private equity interest signals market maturation

Big Takeaway:

  • EV charging success depends on treating infrastructure like a business—driven by data, pricing strategy, and disciplined investment decisions

Featured Guest Bio 

Rohan Puri is the Co-Founder and CEO of Stable Auto, an EV charging data analytics platform. He focuses on addressing one of the biggest barriers to widespread EV adoption—the lack of reliable and scalable charging infrastructure—by enabling more informed, data-driven decision-making.

To support this, Stable’s proprietary software leverages AI to analyze prospective charging sites and predict long-term profitability. Drawing on more than 70 million data points, the platform helps charging networks, infrastructure developers, and financial institutions forecast EV charging usage and costs over the lifecycle of a charger.

Prior to founding Stable, Rohan developed software and machine learning models at MIT Media Lab, where he contributed to the advancement of diagnostic devices and biometric sensors. In parallel with his work at MIT, he advised technology startups through Techstars and the Harvard Innovation Lab and has also spoken at TEDx event


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Field FrequencyBy Jason Cortes