DatologyAI builds tools to automatically select the best data on which to train deep learning models. Our tools leverage cutting-edge research—much of which we perform ourselves—to identify redundant, noisy, or otherwise harmful data points. The algorithms that power our tools are modality-agnostic—they’re not limited to text or images—and don’t require labels, making them ideal for realizing the next generation of large deep learning models. Our products allow customers in nearly any vertical to train better models for cheaper.

DatologyAI

Viviana Faga

Ari Morcos

Bogdan Gaza

Matthew Leavitt

Western US Information Technology Companies (Top 10K)

West Coast Companies With More Than 10 Employees (Top 10K)

San Francisco Bay Area Early Stage Companies With More Than 10 Employees

Startups Founded in 2023

DatologyAI is an AI-data curation startup that develops deep learning tools for automatic selection in data training. The company provides tools that help automate much of the creation of datasets. It identifies which information within a dataset is the most appropriate, based on what the AI model is designed to do. In addition, its tools can suggest ways to augment existing datasets with additional information, work out the best way to batch that information, or split it into more manageable chunks to streamline the model training process.

Felicis

Series A - DatologyAI

Amplify Partners

Seed Round - DatologyAI

Redwood City

California

United States

North America

DatologyAI raises $46M to streamline AI model training data diets

Ex-DeepMind and Meta AI Researcher Raises Nearly $50 Million To Help Developers With LLMs’ Secret Sauce

Are We Running Out of Training Data?

DatologyAI is building tech to automatically curate AI training datasets

DatologyAI raises $11.65M to automate data curation for more efficient AI training

Italy

Europe

Nigeria

Africa

India

Asia

Nepal

Developer of data curation tools for training AI models

GenAI

DatologyAI builds tools to automatically select the best data on which to train deep learning models. Their tools leverage cutting-edge research to identify redundant, noisy, or harmful data points, and are modality-agnostic, not limited to text or images, and don’t require labels, making them ideal for realizing the next generation of large deep learning models.

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DatologyAI