Deeptech startup Oorja raises $1.5 million in pre-Series A funding

Share

oorja, a Bengaluru-based deep tech startup that uses a combination of Physics and ML to perform predictive modelling, today announced that it has raised $1.5 million in seed funding. The funding round was led by Micelio Fund, the first venture capital fund in India dedicated exclusively to enabling radical and sustainable innovation in the clean mobility ecosystem and co-led by Capital-A. Java Capital, Anicut Capital and Lead Angels also participated in the funding round. oorja will utilise the funds to build their product and make inroads into Europe and North American markets.

Headquartered in Bengaluru, India, oorja is a deep tech startup that was launched in 2022. oorja uses a combination of Physics and ML to perform predictive modelling. Through its ‘first of its kind’, easy-to-use cloud-based platform that uses a hybrid (Physics and ML) approach, oorja enables designers and engineers to create accurate and reliable solutions with predictable performance under real-life conditions. oorja is currently working to empower automotive OEMs and designers to make informed decisions to optimize battery packs by reducing time to market and costs.

Within a year of its existence, oorja has already launched its product and an extensive range of apps that address every battery design challenge including material, range, capacity fade, thermal management, and cell design. oorja currently has over 15 customers spread across Asia and Europe.

 “Physics-based tools that are currently used are complex, difficult to deploy and slow down time to market. Our motivation behind oorja has been to solve complex engineering problems at the design stage with a cutting-edge world-class product made in India. Our Hybrid approach uses a combination of physics + ML to improve accuracy and speed up time to market,” said Dr. Vineet Dravid, Founder, oorja energy. “We are grateful to our investors for reposing their faith in our capabilities and empowering us in our journey towards making oorja the go-to design analysis tool in the new age mobility industry.”

Alok Chauhan, Principal, Micelio Technology Fund said, “We are very excited to partner with oorja. They are solving a crucial global problem to ensure the transition to clean mobility is safe and efficient. Engineering design is getting complex and time-consuming leading to long release cycles and need user-friendly, time-efficient tools to assist new technology development and launch products faster. Vineet and team have the most relevant background and have built an impactful solution that has the potential to be a global category-leader in the space.”

Ankit Kedia, Founder and Lead Investor – Capital-A, who had also invested in oorja at the seed stage said, “From the very beginning, Capital-A recognized the immense potential of oorja’s groundbreaking approach to predictive modelling. We were the first believers in their vision and their unique fusion of Physics and ML to revolutionize the clean mobility landscape. Our deep expertise in the EV and Mobility sectors enabled us to collaborate closely with oorja, contributing to the development of a powerful thesis in this domain. In a world where regulatory environments around EVs are rapidly evolving, simulation emerges as the future path. oorja’s cloud-based platform aligns perfectly with this trajectory. We are happy to play a crucial role in supporting their journey to become the go-to design analysis tool in the new age mobility industry.’’

 

oorja is part of Indian Science Technology Engineering facilities map ( ISTEM) program which operates under the aegis of the Office of the Principal Scientific Advisor to the Government of India. Through ISTEM, students in over 800 colleges across India have access to the oorja application suite for research and education. oorja has also received the SISFS grant via Pandit Deendayal Energy University (PDEU), Gandhinagar and is currently incubated in NSRCEL, the flagship business incubator of IIM Bangalore, under Mobility Cohort – 2.