Agentic Data: Amplifying AI Without the Crash

Autodata: Using AI agents as data scientists to generate high-quality synthetic training data

We introduce Autodata, a general method that enables AI agents to act as data scientists who build high quality training and evaluation data

Autodata: Using AI agents as data scientists to generate high-quality synthetic training data

We introduce Autodata, a general method that enables AI agents to act as data scientists who build high quality training and evaluation data

Autodata: Using AI agents as data scientists to generate high-quality synthetic training data

We introduce Autodata, a general method that enables AI agents to act as data scientists who build high quality training and evaluation data

Autodata: Using AI agents as data scientists to generate high-quality synthetic training data

We introduce Autodata, a general method that enables AI agents to act as data scientists who build high quality training and evaluation data

Sponsored: Why data storage, not compute power, may be AI's next major bottleneck

SPONSORED FEATURE: As AI evolves from novelty to autonomy, the real bottleneck isn't processing power—it's where to put all that data.

What is Agentic AI?

Active Monitoring: How Agentic AI Auto-Heals and Protects Enterprise Data Pipelines

> **Cross-posted.** This article's canonical home is [Data Lakehouse Hub](

Autodata: An agentic data scientist to create high quality synthetic data

Authors: Ilia Kulikov, Chenxi Whitehouse, Tianhao Wu, Yixin Nie, Swarnadeep Saha, Eryk Helenowski, Weizhe Yuan, Olga Golovneva, Jack Lanchan