Volytica Diagnostics provides manufacturer-independent battery health monitoring software utilizing AI and electrochemistry-based algorithms to analyze field data. The platform delivers insights into degradation, state of health, and safety risks across applications like BESS and e-mobility. This scalable technology enables users to maximize performance, optimize maintenance, and make informed decisions regarding battery asset management.
Funding
$8.2M 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.
ENSIFounders
Product
Problem
Battery systems in electric vehicles and energy storage solutions are complex and degrade over time, leading to performance changes and potential safety risks. Traditional monitoring methods often require time-consuming initial training, lab testing, and are not easily scalable for large deployments. A lack of real-time insights into battery health makes it difficult to optimize performance, predict remaining useful life, and schedule maintenance effectively.
Solution
Volytica provides manufacturer-independent battery health monitoring software that leverages AI and electrochemistry-based algorithms to assess the condition of battery systems in real-time. The software analyzes field data transmitted by battery systems to provide insights into degradation, state of health, anomalies, and safety risks. The platform offers scenario-based predictions of remaining useful life and optimization recommendations. Its API-integrated cloud platform enables automated monitoring of battery system safety, maximizing performance and longevity while saving costs through early warnings and optimized maintenance schedules.
Target Audience
The primary customers are in the transport sector (e-buses, cars, trucks, trains), battery energy storage systems (BESS) manufacturers, operators, suppliers, distributors, and banks, lessors, and insurance companies.
Features
- AI- and electrochemistry-based algorithms for real-time battery diagnostics, independent of cell type
- Scenario-based prediction of remaining useful life and optimization potential
- Scalable API-integrated cloud platform for automated safety monitoring
- Diagnostics of the current state of battery systems
- Identification of anomalies and safety risks
- Integration with third-party platforms
- Customizable dashboards and reporting