Appen Limited, a leader in data for the AI Lifecycle, announced the investment in Mindtech, a synthetic data company specializing in the creation of high-quality training data for AI computer vision models. As part of the investment, Appen has formed a commercial partnership agreement with Mindtech.
Mindtech is the creator of Chameleon, a self-serve platform that enables customers to create and curate vast computer vision synthetic data assets used to build accurate neural networks. Mindtech’s customers include leading retailers and consumer electronics companies.
“Mindtech has created a scalable platform for the generation of large volumes of synthetic training data. The partnership between Appen and Mindtech will provide customers with the ability to curate a combination of real-world and synthetic data across a wide variety of use cases,” shares Appen CEO Mark Brayan.
Synthetic data is an emerging component of the training data market that is used to augment real-world data. It is particularly useful for the creation of edge-case data that is difficult to capture. The synthetic data market segment is forecast to grow to $1.15B by 2027, representing 48% CAGR1.
“We’re excited about this strategic partnership with Appen,” shared Steve Harris, CEO at Mindtech. “It’s going to enable more customers to rapidly train their AI systems with high-quality, precisely annotated synthetic data while complementing Appen’s existing products of real-world data collection, management, and annotation. By working in partnership, we’ll accelerate the development of AI systems that better understand how humans interact with each other and the world around them.”
The investment is a continuation of Appen’s strategy to deploy capital into product-led businesses that generate new and emerging sources of training data to support AI lifecycles.
In addition to the investment in and partnership with Mindtech, Appen released their full-year earnings results on 24 February. Revenue grew to $447M, cementing Appen’s position as the market leader.
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