Late last year, we were approached by two Stanford and YC researchers building @getoro_xyz to solve AI's critical bottleneck: access to high-quality private data that can't be scraped or simulated.

Their technical solution impressed us immediately: a consumer app and privacy preserving protocol using zkTLS and TEEs that enables private model training without exposing raw data. This preserves both privacy and data value.

After our first call, we didn't have to think twice to accelerated Oro through @Delphi_Labs Accelerator. The founders' backgrounds at Stanford AI Lab, YC, Salesforce and Replit demonstrated they understood both technical execution and market dynamics where others had only theorized. In addition they had the network to connect supply and demand.

We're proud to be supporting Oro alongside investors @a16zcrypto, @ocularvc, @OrangeDAOxyz, @NEARProtocol and @0G_labs in their $6M seed round. With their consumer app launching soon, we expect Oro to be among the first distributed AI projects achieving genuine market adoption by creating huge value for both individuals and AI companies.

Congrats on the raise @dgmonsoon and @ck_oro, looking forward to the release of the consumer app and start of Season 1.