Rajesh Solanki: The Vision Behind The Transformation of Fuel Stations Into EV Ecosystems

What happens to 1 million fuel stations when the vehicles they serve vanish from the roads? The question haunts executives across the energy sector. Each location represents prime real estate, established customer patterns, and grid connections worth millions of dollars. Yet 29% of EV charging attempts fail on the first try, sending frustrated drivers back to gasoline. The infrastructure exists, but no one knows how to convert it.

Rajesh Solanki found the answer. His company, Energos.ai, has just proven that the economics work across 200 Shell retail locations. While competitors argued about building new charging networks from scratch, he saw existing fuel stations as the solution, not the problem. The stakes are monumental: 150,000 sites in the United States alone, each one either headed for demolition or rebirth.​​

Decoding the Shell Blueprint

Working with Shell demanded precision. Solanki’s team constructed digital twins of each station, virtual replicas that simulate energy loads down to the kilowatt level. The models revealed something counterintuitive. More charging capacity requires fewer physical charging units when managed correctly. Traditional thinking assumes each new charger needs proportional infrastructure. Wrong.​​

“We analysed the effect on energy requirements as stations add more EV chargers and reduce fuel dispensers,” Solanki explained. “The number of EV charges increases while dispensers decrease. Nobody else addresses this transition systematically.”​

Results validated the methodology. The Economic Times confirmed Energos implemented AI-driven tools to boost energy efficiency across Shell’s retail sites. The system creates digital twins of each station and analyses the effect on energy requirements from increasing energy loads as more EV chargers are added while reducing fuel dispensers. These deployments are live environments benefiting from Shell’s infrastructure and operational access.​​

Patent-Driven Energy Intelligence

Solanki holds a U.S. patent for monitoring and controlling devices that facilitate energy and load management, which is crucial for maintaining grid stability during peak charging times. The patent covers a system for conserving and efficiently using energy through the control and monitoring of devices. It specifically addresses autonomous energy flow selection and energy management.​​

Most operators handle this manually or through rigid programming. Manual intervention fails at scale. Rigid rules break when conditions change. Solanki’s AI models adapt in real time, learning from each station’s unique load patterns. The software predicts equipment failures before drivers are aware, enabling a shift from reactive repairs to predictive maintenance.​​

American Scale, Global Implications

The United States alone operates 150,000 fuel stations and convenience stores. Each one sits on premium real estate with existing electrical service, parking infrastructure, and customer recognition. Demolishing them wastes capital. Leaving them unchanged wastes opportunity.​​

Solanki, a serial entrepreneur with exits in access control and video analytics, brought two decades of experience in both hardware and software to the problem. His previous ventures taught him how distributed systems fail and how to prevent it. Energos.ai’s mobile-first platform reduced mean time to repair by 40% for pilot users. The system automatically converts error codes into work orders, guiding technicians through repairs via multilingual voice interfaces.​​

Recognition followed results. Solanki spoke at the AI for Good summit and participated in accelerators including Clean Tech Global, LACI, Shell E4, and Startup Bootcamp Melbourne. The Shell E4 program confirmed Energos implemented AI-driven tools to boost energy efficiency across Shell’s retail sites. Industry awards from Independent Power Producers and the Indian Smart Grid Forum validated the technical achievements.​​

The death of fuel retail, long predicted but poorly executed, finally has a credible pathway. Solanki proved the economics work, the technology scales, and existing assets convert profitably. Now the question shifts from whether fuel stations can survive to how quickly they’ll change.