Electravehicles offers an AI‑driven software platform, the "AI Brain for Batteries," that ingests real‑time sensor data from batteries to deliver high‑resolution state‑of‑charge and state‑of‑health estimates, predictive degradation analytics, and adaptive charging strategies. By integrating with existing BMS, EMS, and ERP systems via cloud dashboards and APIs, the platform helps EV manufacturers, battery pack OEMs, utility‑scale storage operators, and fleet managers extend battery life, improve safety, and lower total cost of ownership.
Funding
$27.1M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
SVFounders
Product
Problem
Battery performance, safety, and lifespan are difficult to optimize across diverse applications such as electric vehicles, stationary storage, and robotics because traditional battery management relies on static algorithms and limited real‑time data, leading to premature degradation, unexpected downtime, and sub‑optimal return on investment.
Solution
Electra provides an AI‑driven software platform—referred to as the “AI Brain for Batteries”—that continuously ingests sensor data from individual cells and packs to generate high‑resolution state‑of‑charge (SoC) and state‑of‑health (SoH) estimates. The platform leverages machine‑learning models and physics‑based digital twins to predict degradation pathways, recommend optimal charging strategies, and trigger preventive actions before failures occur. Results are delivered via cloud‑hosted analytics dashboards and APIs that integrate with existing battery management systems (BMS) and enterprise resource planning tools. By turning raw battery telemetry into actionable insights, Electra helps OEMs, fleet operators, and energy‑storage managers extend battery life, improve safety, and increase overall profitability.
Target Audience
Primary customers are electric‑vehicle manufacturers, battery‑pack OEMs, utility‑scale energy storage operators, and large‑scale vehicle or robot fleet managers seeking to improve battery utilization and reduce total cost of ownership.
Features
- Real‑time SoC/SoH monitoring using AI models trained on fleet‑scale data
- Predictive degradation analytics powered by physics‑based digital twins
- Adaptive charging and control algorithms that optimize performance and reduce wear
- Cloud‑based analytics platform with customizable dashboards and API access for integration with BMS, EMS, and ERP systems
- Scalable licensing for both on‑vehicle (edge) deployment and centralized fleet or BESS monitoring
- Battery design and testing tools (EnPower) that accelerate development cycles for manufacturers