misson flagOur Mission

API for Ground Truth Data

The age of machine learning is a new phase of computing.Powered by a dynamic research community, computers can now recognize images and audio, translate languages, generate realistic text, and beat humans at games.Machine learning is likely the most significant technological shift happening between 2010 and 2030. Aside from a few innovative products from large tech companies, ML has not yet made a tremendous impact.

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Labeled Data Is Key

Labeled data is the key bottleneck to the growth of the machine learning industry. In fact, labeled data is even more essential than algorithms.

ImageNet is a repository of 14 million labeled images in more than 20,000 categories.
By 2011, AlexNet, the first modern neural network, was the top performer on the ImageNet leaderboard. This kicked off the deep learning craze.


Data labeling is not only practically important, it is also philosophically important to the field. Machine learning is a form of metaprogramming—the developer doesn't directly write the program; the developer writes a program which itself writes the program.

The developer provides a rough framework for what the program should look like (usually a neural network), and what its goal should be (usually a labeled dataset), and that spits out a program that is nonsensical to humans, but is better than any program a human could ever write.

It's a bit demoralizing—as Andrej Karpathy once tweeted, gradient descent writes better code than you. I'm sorry.

Framework + Goal

Humans can influence both the framework and the goal. The framework is the machine learning architecture and algorithm.

The goal is the labeled dataset. This is the ceiling for how good a model can ever be. The labeled dataset directly programs the final model.

It gets “compiled” into the model via back propagation. As more and more of the software of the world is written with machine learning software, the amount of data required to power these systems will also grow.

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accelerate hexaWhat we do

Accelerate The Development of AI

Machine learning replaces a specialized resource constraint (software engineers) with a commoditized one (data labelers). This significantly accelerates technological progress on a global scale. The growth rate of software will accelerate over the next decade as more software is created by machine learning.

Traditional Dev Cycle

Traditional Dev Cycle

Early & Influential

It is early in the age of machine learning. Deeply impactful technology takes time to gestate.

Google was founded 15 years after the invention of the internet. iPhone was invented 24 years after the invention of the internet. It’s only been 8 years since AlexNet was first launched.

Being early makes our work exciting. We have the opportunity to be profoundly influential.

AI Dev Cycle

Traditional Dev Cycle


Building infrastructure is more durable than building applications—Scale will amplify the whole impact of machine learning if we succeed, which will reach further than any single application. In this way, we will bend the curve of technology, and therefore the curve of humanity.

Our mission is critically important, and needs to happen now. By structurally increasing the coefficient of growth, we are enabling a new age of software.

accelerate hexaOur Investors

We're fortunate to have incredible investors.

Individual Investors

  • Greg Brockman
    Greg Brockman
    Greg is currently the CTO and co-founder of OpenAI, and before that was CTO of Stripe.
  • Charlie Cheever
    Charlie Cheever
    Charlie is currently cofounder of Exponent. He previously co-founded Quora and was an early employee at Facebook.
  • Adam d’Angelo
    Adam d’Angelo
    Adam D'Angelo is co-founder and CEO of Quora.
  • Justin Kan
    Justin Kan
    Justin is founder and CEO of Atrium. Previously, he co-founded Twitch and was a partner at YC.
  • Mike Krieger
    Mike Krieger
    Mike Krieger is co-founder of Instagram.
  • Nat Friedman
    Nat Friedman
    Nat Friedman is CEO of Github. Previously, he co-founded Xamarin, which was acquired by Microsoft.
  • Drew Houston
    Drew Houston
    Drew is the co-founder and CEO of Dropbox.
  • Jessica McKellar
    Jessica McKellar
    Jessica is the co-founder and CTO of Pilot. She was an early employee at Ksplice (acquired by Oracle) and co-founded Zulip (acquired by Dropbox).
  • Guillermo Rauch
    Guillermo Rauch
    Guillermo has co-founded companies such as LearnBoost, Cloudup, and Zeit, created MongooseJS and socket.io.
  • Kevin Systrom
    Kevin Systrom
    Kevin Systrom is co‑founder and CEO of Instagram.
  • Ilya Sukhar
    Ilya Sukhar
    Ilya is currently a General Partner at Matrix Ventures, and previously was co-founder and CEO of Parse.
  • Jonathan Swanson
    Jonathan Swanson
    Jonathan Swanson is co-founder and executive chairman of Thumbtack.
  • Lan Xuezhao
    Lan Xuezhao
    Lan is the founding partner of Basis Set Ventures, a early stage venture firm focused on the Future of Work through AI.

Our Board

  • Alex Wang
    Alex Wang
    Alex is the CEO of Scale AI. He was inspired to solve ML infrastructure problems and accelerate the development of AI through his work at Quora where he worked as a technical lead.
  • Daniel Levine
    Daniel Levine
    Daniel Levine joined Accel in 2010 and focuses on product-first startups aimed at consumers, developers, and bottoms-up business users.
  • Mike Volpi
    Mike Volpi
    Mike Volpi joined Index in 2009 to help establish the firm's San Francisco office. He invests primarily in artificial intelligence, infrastructure, and open-source companies.

Scale is growing. Grow with us.

Join us as we accelerate the development of AI applications.

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