Autonomous, real-time charging control that learns and adapts.
Prevent degradation. Extend lifespan. No hardware changes.
Not a chemistry problem. Batteries degrade early because charging logic is static and blind to real-world conditions.
Fixed rules ignore battery age, temperature, and duty cycles. Every battery charged the same way, regardless of state.
Traditional monitoring observes failures after they happen. By the time you see degradation, the damage is done.
Batteries are treated as dumb storage. But they're dynamic electrochemical systems that respond to every charge decision.
A closed-loop AI system that doesn't just monitor—it controls. Learning-based charging decisions generated in real-time, adapting as batteries age and usage patterns change.
"Charging decisions are generated by trained models, not fixed rules, and evolve as the battery ages and usage patterns change."
Our models don't just observe—they learn from how batteries respond to active charging interventions. This creates a compounding data advantage OEMs cannot simulate.
Model-driven charging policies that rewrite behavior in real-time based on battery state and history.
Longitudinal data on how batteries age under different conditions, building predictive accuracy over time.
We learn from what happens after a charging decision—not just passive telemetry, but active outcomes.
Protected IP on core charging technology strengthens our defensibility against replication.
Deep expertise in batteries, charging systems, and energy infrastructure deployment.
Experience deploying and operating learning systems in production. Core system architecture design.
Ready to extend your battery life by 30-40%?