Solving the spectrum of battery design challenges


Material property database for cells and all pack materials. Create your own databases, or use available data to create your cell and pack level projects.

 Cell material and design property database

  Custom material creation


Upload cycler data and clean it to make it machine readable. Built in cleaning algorithms which clean spikes in experimental data and fill in missing points using state-of-the art algorithms and make them ready for further analysis. Supports all cyclers and HPPC, DCIR, aging and ARC data.

  Automatic data cleanup

  Automatic detection of key inflection points


Web based tool to design complex battery packs and cooling systems. Enables quick creation of battery pack design for various cell form factors.

   Complex design creation in few clicks

   Automated meshing

Redefining Product Features

Keeping your eye on the ball while performing a deep dive on the start-up mentality to derive convergence on cross-platform integration.

Cell Venting

Account for two stage venting to ensure high fidelity predictions during pack level thermal runaway initiation and propagation modeling. Automatic detection of onset of thermal runaway and cell pressure variation within the pack and accounts for heat convection due to vent gases. Enables more accurate prediction of thermal runaway initiation throughout the pack and enables design of pack vent location.


Thermal predictions for battery packs. Optimize pack design, thermal management and predict thermal runaway initiation in packs. Hybrid approach used to maximize accuracy and speed.

   Accurate thermal predictions for active and passive cooled packs

   Thermal runaway initiation and propagation at pack level


Predict vehicle performance and range at the get go. Estimate the impact of real life driving conditions, road conditions and temperature on vehicle range over the life of the vehicle.

  Range prediction for any real life driving condition

  EV drive cycle generation


Degradation predictions for cells and packs. Capture the impact of real life driving and operating conditions on battery life. State-of-the art hybrid algorithms capture both physical degradation mechanisms and manufacturing uncertainties.

   Accurate fade prediction for cells and packs

   Prediction for arbitrary drive cycles, road and ambient condition


Estimate cell performance at the get go. Predict cell behaviour for various design and material parameters of electrodes and electrolytes using state of the art physics based models

  Capacity and discharge efficiency calculation

   Volumetric energy density evaluation


A data-driven battery intelligence hub offering detailed visualizations of battery performance and actionable insights. This app showcases intuitive graphs and suggests improvements for informed decision-making, empowering users to optimize battery systems efficiently.

Generate detailed visualisations of battery performance

Gain actionable insights for design optimisation

New Features


Account for two stage venting to ensure high fidelity predictions during pack level thermal runaway initiation and propagation modeling


Account for cell to cell variations and predict pack degradation for real life drivecycles


6 times faster and 5% more accurate than the nearest competitor


No hardware investment required, run unlimited jobs on secure servers. Flexible plans catering to your company’s simulation needs.