oorja | Physics and ML Software for Battery Engineers
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Company Overview
oorja is a Bengaluru-based deep-tech startup that builds cloud-based software for battery design, testing, and lifecycle management. Founded in 2022 by Vineet Dravid, alongside co-founders Prashant Kumar Srivastava and Prajakta Vaidya-Sabnis, the company was built around a hybrid modelling approach that combines physics-based simulation with machine learning to predict battery behaviour.
The founding team previously worked together at COMSOL, a physics-based simulation software company, and applied that background to build tools specifically for lithium-ion battery engineering in electric vehicles and energy storage systems. The company’s stated aim is to reduce the time, cost, and physical prototyping traditionally required to design, qualify, and monitor batteries.
oorja’s product line spans two areas: a design and analysis suite for engineers working on new battery and pack designs, and a fleet-monitoring dashboard for batteries already deployed in the field. The company has been incubated at NSRCEL, the business incubator of IIM Bangalore, and is part of India’s ISTEM programme, which gives students at partner institutions access to its software for research and education.
oorja has raised early-stage venture funding from Indian cleantech and mobility-focused investors and was recognised as a winner of Nasscom’s Emerge 50 awards in the Energy and Climate category in 2024.
oorja’s software is used to design and monitor batteries for electric vehicles and energy storage systems, technologies that are central to expanding access to clean, reliable energy infrastructure. By helping battery and pack designers improve safety, performance, and reliability, the company supports the broader deployment of the clean energy and clean mobility systems central to SDG 7.
The company’s core offering, a physics-informed machine learning platform built specifically for battery engineering, is itself a direct example of the technological innovation described in SDG 9, and its incubation within India’s national deep-tech and research infrastructure (NSRCEL, ISTEM) reflects this same innovation-and-infrastructure focus.
oorja’s tools are explicitly designed to reduce reliance on physical prototyping and destructive testing, while its remaining-useful-life prediction capability is aimed at extending the working life of deployed batteries. Both reduce material and resource waste across the battery lifecycle, aligning with SDG 12’s emphasis on more efficient and responsible use of resources in production processes.
- oorja Battery Suite: cloud-based battery design and analysis platform
- Material module: electrode and pack material database
- Data module: cycler data cleaning and management tools
- Optimize module: rapid battery parameter estimation
- Volt module: cell performance and fast-charging prediction
- Design module: battery pack and cooling system design tool
- Range module: EV range and drive-cycle estimation
- Heat module: thermal runaway and safety simulation
- Fade module: battery degradation and warranty modelling
- oorja Battery 360: deployed battery fleet health dashboard
- Slow, costly physical battery testing and prototyping cycles
- Difficulty predicting long-term battery degradation and remaining life
- Limited visibility into the health of deployed battery fleets
- Assessing thermal runaway and safety risk during pack design
- Time-consuming parameter estimation requiring extensive lab testing
- Estimating real-world EV range across varied drive cycles
oorja’s platform is built around a hybrid modelling approach that combines physics-based battery models with machine learning, an approach the company positions as more accurate than pure data-driven ML and faster to deploy than conventional physics-based computer-aided engineering (CAE) tools. The Battery Suite is organised into ten modules covering the battery design lifecycle, from a materials database and cycler data cleaning through to parameter estimation, cell performance prediction, pack and thermal design, drive-cycle range estimation, and degradation or fade modelling.
For batteries already in the field, oorja Battery 360 applies the same hybrid approach to live telemetry from EV fleets and energy storage systems, generating prognostic alerts across maintenance, usage, safety, and remaining-useful-life categories. The company describes this deployed-asset layer as using federated machine learning, which refines predictions using real-world operational data while keeping that data private to each customer.
Both products are delivered as cloud-based software rather than on-premise tools, and the company reports that its models have been validated against experimental data with accuracy of up to 95% for design-stage predictions and up to 93% for remaining-useful-life estimates.
oorja operates in the battery engineering software space, positioned between traditional physics-based CAE tools (the category its founders previously worked in at COMSOL) and pure data-driven battery analytics tools. Its customers are primarily electric vehicle manufacturers, battery pack designers, and operators of energy storage systems and EV fleets, with Scania Group cited as a user of the platform in company-published material.
The company differentiates itself through its hybrid physics-plus-ML methodology, which it positions as combining the accuracy of physics-based modelling with the speed and adaptability of machine learning, delivered through a subscription-based cloud platform rather than licensed desktop software.
- Confirm which specific Battery Suite modules are required, since the ten-module suite may be priced or licensed by module
- Clarify data privacy and hosting terms for cycler and fleet telemetry data uploaded to the cloud platform
- Review validation methodology and accuracy benchmarks (up to 95% for design predictions) against your own cell chemistry and use case
- Assess integration requirements with existing battery management systems (BMS) or fleet telemetry infrastructure
- Confirm subscription terms and whether customer success or onboarding support is included
- Check compatibility with your specific cell form factors and chemistries before procurement
- Verify current company scale and support capacity given its early stage (founded 2022, small team)
- $1.5 million pre-Series A funding round (2023), led by Micelio Fund and co-led by Capital-A, with participation from Java Capital, Anicut Capital, and Lead Angels
- Earlier investment from Capital-A’s cleantech fund, Evolve (2022)
- Incubated at NSRCEL, the business incubator of IIM Bangalore, under its Mobility Cohort
- Recipient of a Startup India Seed Fund Scheme (SISFS) grant, administered via Pandit Deendayal Energy University, Gandhinagar
- Included in India’s ISTEM (Indian Science Technology Engineering facilities Map) programme, under the Office of the Principal Scientific Advisor to the Government of India, giving students at partner institutions access to its software
- Winner, Nasscom Emerge 50 (2024), Energy and Climate category
- Additional investors reported by PitchBook include Maruti Suzuki Innovation, AirAsia, and Axilor Ventures
oorja is targeting a genuine bottleneck in the electric vehicle and energy storage transition: battery engineering teams need faster, cheaper ways to predict how a cell or pack will perform and degrade, without relying entirely on slow, expensive physical testing. Its founding team’s background at COMSOL, a well-established physics-simulation software company, gives it a credible technical starting point for a hybrid physics-plus-ML approach, and its early customer references and inclusion in Nasscom’s Emerge 50 cohort suggest the product has moved past a purely conceptual stage.
The company’s two-product structure, a design-stage suite and a deployed-fleet monitoring dashboard, gives it relevance across the battery lifecycle rather than a single point in it, which is a reasonable strategic bet in a market where EV and energy storage deployments are scaling quickly and operators increasingly need visibility into asset health after deployment, not just at the design stage.
As an early-stage company founded in 2022 with a small team and roughly $1.5 to $1.8 million in disclosed funding, oorja’s scale and track record are still developing relative to larger, more established CAE and battery analytics vendors. Procurement teams evaluating the company should weigh its technical differentiation and India-based deep-tech ecosystem support against its relatively early stage and limited public case study base.
- oorja Battery Suite product page: https://oorja.energy/battery-suite/
- oorja Battery 360 product page: https://oorja.energy/battery-360/
- oorja About Us page (team, awards, at-a-glance figures): https://oorja.energy/about-us/
- pv magazine India, “Deeptech startup Oorja raises $1.5 million in pre-Series A funding”: https://www.pv-magazine-india.com/press-releases/deeptech-startup-oorja-raises-1-5-million-in-pre-series-a-funding/
Bengaluru, Karnataka, India
oorja is headquartered in Bengaluru, India, and its team, product development, and current publicly disclosed customer relationships are concentrated in India. The company has stated an intention to expand into European and North American markets following its 2023 funding round, and its cloud-based delivery model allows it to serve customers internationally without local infrastructure.
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