Commercial fleet customers can enjoy end-to-end infrastructure plans in under 60 seconds, to support fleets of 5 to 5,000+ vehicles across 800+ makes and models, with real-time and real-world intelligence
SparkCharge, the world’s largest off-grid electric vehicle fleet charging network and creator of the first mobile, off-grid EV charger, announced the launch of SparkAI, the first AI-driven charging infrastructure planning platform specifically designed for commercial EV fleet deployments. The platform combines real-world intelligence, project location-specific datasets, weather forecasts, and a comprehensive global EV database to create optimized charging infrastructure plans for fleet owners and operators. SparkAI is immediately available for streamlined, intelligent infrastructure planning across the United States, Canada, and Mexico.
Today, more than 80% of electrification projects face grid capacity limitations that can delay deployments by 18 to 24 months. Traditional infrastructure planning is slow, fragmented, and heavily reliant on costly utility upgrades. SparkAI eliminates these delays through a proprietary enterprise-grade AI model capable of performing thousands of energy simulations instantly. The system accounts for fleet composition, local weather conditions, terrain, and available power sources to deliver precise, site-specific configurations, helping fleets deploy scalable infrastructure in as little as 3 days without overloading the grid.
“SparkAI isn’t just about faster planning, it’s about smarter energy deployment,” said Joshua Aviv, Founder and CEO of SparkCharge. “Right now, we’re channeling that precision into EV charging, helping fleets electrify without overloading the grid. But the bigger opportunity is optimizing how and where energy flows, for EVs and beyond. It’s a smarter grid strategy, powered by real-time intelligence.”
Alleviating Grid Strain—and Supporting AI Economy
Beyond fleet electrification, SparkAI enables intelligent energy distribution that supports broader grid stability. By prioritizing location efficiency, energy independence, and load balancing, SparkAI helps free up grid capacity and reduce peak demand, directly benefiting energy-intensive sectors such as AI computing and data centers. SparkCharge’s mobile battery trailers and off-grid power hubs can be deployed anywhere to stabilize remote grid-limited regions.
Real-Time, Real-World Intelligence
SparkAI’s intelligence engine cross-analyzes live environmental and geographic data against energy demand forecasts to calculate exact power requirements per site. This gives operators AI-driven energy independence in areas previously considered uneconomical for electrification—rural regions, congested areas, industrial zones, and aging grid corridors. The platform can also design hybrid and off-grid charging systems that scale dynamically with fleet growth, allowing users to bypass traditional grid bottlenecks entirely.
Smarter Planning, Lower Energy Costs
SparkAI helps fleet operators reduce total infrastructure and operating costs by 15–30% through accurate forecasting and intelligent system sizing. By preventing both costly overbuilding and energy shortfalls, SparkAI improves asset utilization, lowers exposure to peak utility rates, and enables fleets to leverage off-grid or hybrid energy sources at a fraction of the traditional cost.
“SparkAI is a game-changer for infrastructure ROI,” said David Piperno, CFO of SparkCharge. “By eliminating over-provisioning and planning delays, we’re helping fleets reduce capital expenditures while accelerating deployment timelines. It’s not just about planning faster, it’s about deploying smarter and scaling profitably.”
Today’s announcement follows sustained momentum from SparkCharge. In the past year, the company has provided EV charging solutions for fleets at the US Open and Masters Tournament. SparkCharge also announced $30.5 million in a capital raise earlier this summer.
Contact SparkCharge or visit here to learn more about SparkAI and the company’s portfolio of EV charging solutions.
