Today we are excited to share several key updates that build on Scale AI’s

mission to accelerate the development of AI.

First, we are officially announcing Scale’s Series D funding round. Following

our Series C fundraise last year, Scale has raised $155M at a post-money

valuation north of $3.5B led by Tiger Global.

We are in the midst of one of the most impactful technology transformations of

human history with AI. The potential applications of AI are going to deeply

improve the world: scalable medical diagnosis to everyone in the world,

massive reduction in driving accidents, goods which are dramatically cheaper

to manufacture and transport, and much more. What’s holding us back from

building those dreams is lack of infrastructure. While many organizations are

adopting AI, they are forced to build their technology stack from scratch,

significantly slowing progress.

Four years ago, we recognized this problem and sought to unlock the

bottlenecks holding back AI development. We started by building a platform

that solves the necessary, foundational layer that fuels all machine learning

models: large annotated datasets. Our solution gives developers the ability to

send data to our platform through the Scale API and receive high-quality

training data that’s ready for building production-grade AI algorithms. We use

a combination of machine learning and human intelligence to annotate tens of

millions of data points per week for hundreds of customers like OpenAI,

DoorDash, Pinterest, General Motors, NVIDIA, Nuro, and Toyota.

We’ve chosen to stay focused on the applications of AI with the greatest

potential for impact: autonomous driving, government, and cutting-edge

consumer technology. As AI has transformed every industry, we’ve continued to

see demand for our platform to grow—from e-commerce and AR /VR to relevance

& personalization and financial services. We are still very early in the

journey of AI, and we remain optimistic about all the future dreams we will

support.

Our team is tackling the next bottleneck in AI development: managing the full

life cycle of AI development across teams. Building and deploying scalable

machine learning infrastructure is slow, manual and costly, and in August we

launched Nucleus to enable seamless

collaboration across the AI development cycle. Teams can visualize and

organize their datasets, test and compare models, and share data with

colleagues. With Nucleus, our goal is to become the mission control for your

data, and over time we’ll be rolling out support for more data types and

adding more features to make developing AI easier and faster than ever.

As part of today’s announcement, we are also excited to announce the

acquisition of Helia AI. Helia’s team brings deep expertise in applying AI

to real-time video, from core algorithm development to necessary AI

infrastructure. Their AI infrastructure experience aligns closely with what

we’re building with Scale Nucleus, and the Helia team will help advance the

Scale platform as we expand its capabilities.

We look forward to continuing our work of building AI infrastructure with

Scale’s hundreds of customers, and our new funding will allow us to

accelerate hiring, expand to new markets and build more robust products to

match the evolving needs of AI as the technology matures. We’re still in the

early days of AI, and we believe Scale will enable a future where AI is as

easy to build and manage as any other software. If you are interested in

joining us on our mission, check out our

open positions. If you’re interested

in partnering with us, please

reach out.