Bengaluru-based AuraML, a synthetic image data platform for computer vision and robotics, has raised Rs 1.88 crore in a Pre-Seed funding round from Indian Angel Network (IAN). Uday Sodhi, Neeraj Saran and KRS Jamwa were the lead angel investors from IAN in this round.
The company intends to utilise the investment to optimise its synthetic data generation engine. It has plans to hire skilled staff for its founding engineering team and wants to expand its footprints in the US and European markets. Additionally, the company will use the capital for the official launch of its cloud platform in the coming months.
Launched in January 2023, AuraML is led by Ayush Sharma and Arjun Gupta. According to a company statement, both have experience in robotics and AI/ML and have encountered challenges in data collection and labeling while training machine learning models for computer vision in their previous avatars. The company has claimed to develop a proprietary synthetic data engine and is currently running closed projects with its initial customers.
Addressing the fundraising, Ayush Sharma, CEO of AuraML, said, “We are grateful to IAN for trusting us and supporting us in our growth journey. This investment will be a key accelerator for us to take the technology from a prototype to a fully functioning product. We plan to utilize these funds to hire our founding engineering team, develop core technologies and expand our global presence in the US and European markets. This funding will also help us work on building cutting-edge generative AI-based IP.”
Padmaja Ruparel from IAN, added, “Even in today’s digitally-driven times, the data collection and labeling process is completely manual. Millions of images need to be labeled by humans for training computer vision algorithms. This costs companies a lot of time and money. Additionally, the challenges related to data privacy and sharing and data collection of rare cases cannot be ruled out. AuraML, with its synthetic image data platform, is on a mission to offset all these concerns and improve the accuracy of the ML models, thereby allowing complete control over the generated dataset. As they have embarked on a new journey, we are happy to help them grow and support them in all ways possible.”