BUSINESS WIRE: Mindtech, Synthetic Data Platform Provider, Announces Strategic Partnership With Appen and Raises $3.7 Million
MITTEILUNG UEBERMITTELT VON BUSINESS WIRE. FUER DEN INHALT IST ALLEIN DAS BERICHTENDE UNTERNEHMEN VERANTWORTLICH.
** Commercial partnership with Appen to drive adoption of synthetic data across the global AI industry **
** Company raises $3.7 million from Appen and existing Mindtech investors to support rapid growth **
SHEFFIELD, England --(BUSINESS WIRE)-- 10.03.2022 --
Mindtech Global, developer of the world’s leading platform for the creation of synthetic training data for AI vision systems, has announced a strategic investment round led by Appen, the global leader in data for the AI Lifecycle.
This press release features multimedia. View the full release here: https://www.businesswire.com/news/home/20220310005300/en/
This new investment round, including participation from Appen and existing Mindtech investors, follows a $3.25 million funding round in July 2021 and will be used to support the company’s rapid growth.
In addition to the investment, Appen and Mindtech have formed a commercial partnership to provide a range of real and synthetic images and associated data and metadata annotation services to the market. Appen’s leadership in labelling real-world data combined with Mindtech’s end-to-end platform for the creation and management of synthetic data will accelerate the development of more accurate AI systems.
Mindtech’s platform, Chameleon, is highly complementary to Appen’s existing data and annotation services. Chameleon’s ‘no-code’ platform is designed for the creation and automated annotation of synthetic data to train human-to-human and human-to-world AI applications. Using Chameleon is more than 50 times faster than sourcing and annotating ‘real-world’ data.
Mark Brayan, CEO, Appen said, “Synthetic data is an invaluable resource in the training of AI models and when combined with real-world data can enable outstanding results. We’re excited to partner with Mindtech as their automated end-to-end end synthetic data platform produces the right synthetic data for our customers, faster than competing solutions.”
Steve Harris, CEO at Mindtech said, “We’re excited about this strategic partnership with Appen - it’s going to enable more customers to rapidly train their AI systems on scalable synthetic data while complementing Appen’s existing products in real-world data collection, management and annotation. By working in partnership, we’ll further accelerate the development of AI systems that better understand how humans interact with each other and the world around them.”
Mindtech Global www.mindtech.global
Mindtech Global is the developer of the world’s leading end-to-end ‘synthetic’ data creation platform for the training of AI vision systems. The company’s Chameleon platform is a step change in the way AI vision systems are trained, helping computers understand and predict human interactions in applications ranging across retail, smart home, healthcare and smart city.
Mindtech is headquartered in the UK, with operations across the US and Far East and is funded by investors including Mercia, Deeptech Labs, In-Q-Tel and Appen.
Interviews, media images and demos available on request.
About Appen www.appen.com
Appen is the global leader in data for the AI Lifecycle. With over 25 years of experience in data sourcing, data annotation, and model evaluation by humans, we enable organizations to launch the world’s most innovative artificial intelligence systems. Our expertise includes a global crowd of over 1 million skilled contractors who speak over 235 languages, in over 70,000 locations and 170 countries, and the industry’s most advanced AI-assisted data annotation platform. Our products and services give leaders in technology, automotive, financial services, retail, healthcare, and governments the confidence to launch world-class AI products. Founded in 1996, Appen has customers and offices globally.
View source version on businesswire.com: https://www.businesswire.com/news/home/20220310005300/en/