When we started Scale nearly five years ago, our mission was to accelerate the development of AI. Today, I’m proud to say that we’re seeing this mission come to life, as customers across industries, from finance to e-commerce to transportation to government, are shipping AI projects that touch our everyday lives.
But we’re still just scratching the surface of the potential that AI has to transform every business and industry, which is why we’re happy to share that Scale has raised $325 million in Series E funding, co-led by Dragoneer, Greenoaks Capital, and Tiger Global. Additional new investors in the round include Wellington Management and Durable Capital followed by existing investors Coatue, Index, Founders Fund, and YC. The interest and opportunity for AI is only accelerating, and this new funding will help us continue to expand our team and products to meet this growing demand. Additionally, Jeff Wilke, former CEO of Amazon’s Worldwide Consumer business, will be joining as Advisor to the CEO.
“The AI industry is at an inflection point where every business is looking to implement an AI strategy and we are starting to see a real-world impact. We believe Alex and his team at Scale have been critical to enabling businesses across industries reap the full benefits of AI and are taking the industry from proof of concept to reality,” said Neil Mehta, Founder and Managing Partner at Greenoaks Capital.
As we discussed with over 9,000 of the leading minds in AI at our inaugural Scale Transform conference, we’re moving from a theoretical and research based industry to one that’s rooted in impact and real business results. However, making this shift means companies are facing new challenges, which requires a systematic, data-centric approach to rapidly deploy their most important models.
At Scale, we’re building the foundation to enable organizations to manage the entire AI lifecycle. Whether they have an AI team in-house or need a fully managed models-as-a-service approach, we partner with our customers to build their strategy from the ground up and ensure they have the infrastructure in place to systematically deliver highly-performant models.
We set out to solve this problem by starting with an essential building block, data annotation. Building on our expertise in delivering high-quality training data to world-leading machine learning teams, we are now applying our technical expertise and understanding to close the loop on the ML development lifecycle.
Learn more about how we accelerate ML development with an end-to-end solution.