Datology AI

We believe every company should own its intelligence

DatologyAI is the frontier data research lab building the data refinery that AI teams use to curate high-quality data to train their own models

  1. The Compute Multiplier
  2. Frontier Data Curation
  3. For Every AI Team

Better data quality is a massive compute multiplier that keeps models learning by packing more signal into every token, making it possible to train frontier-quality models at a fraction of the cost. Datology brings frontier data curation to every model development team, going well beyond cleaning techniques to find the data that teaches a model what it needs to know about specific tasks a business and its customers care about. We believe that every AI team should have access to the technology to curate high-quality data to train their own models and have full control over the cost and roadmap for the models at the core of their business.

Frontier data curation for every AI team

We started Datology because we knew that curating data well, aligning it to specific tasks, and generating synthetic data grounded in the highest-quality organic content was the single most impactful lever to improve model performance.


As a frontier data research lab, we’ve built the infrastructure to do data curation and synthetic data research and engineering at production scale, running hundreds of thousands of experiments that we turned into the engine behind our product, proven at petabyte scale.


Datology Curation Studio makes our frontier data curation engine available as a straightforward, guided experience, with presets and automation on top of our algorithms, so any AI team, from beginners to experts, can have high-quality training data to train their own models.

Meet the team behind DatologyAI

Ari Morcos Profile

Co-Founder, CEO

Ari Morcos

Former FAIR@MetaAI and DeepMind, Best Papers at both NeurIPS and ICLR, leading expert in data research for deep learning, PhD in neuroscience from Harvard.

Co-Founder, CTO

Bogdan Gaza

Former CTO and co-founder of Moonsense, 10+ years infrastructure engineering and management experience at Amazon and Twitter.

Matthew Leavitt Profile

Co-Founder

Matthew Leavitt

Former Head of Data Research at MosaicML (acq Databricks), FAIR@MetaAI, PhD in neuroscience from McGill.


Backed by the best

Angels

Jeff Dean

Geoff Hinton

Yann LeCun

Adam D’angelo

Aidan Gomez

Ivan Zhang

Douwe Kiela

Naveen Rao

Jascha Sohl-Dickstein

Barry McCardel

Funds

Amplify

Partners

Radical

Ventures

Felicis

Ventures

Conviction

VC

Outset

Capital

Quiet

Capital

M12

Venture Fund

Amazon Alexa

Fund

Datology is your edge

With Datology Curation Studio, your team refines your training data to build your next great model.