Datoric
Secure training data shaped by experimentation
About Datoric
Datoric develops custom datasets for voice models, robotics, and world models, treating research, collection, verification, and production as one continuous process. We work closely with frontier model teams to turn emerging limitations into testable data hypotheses, while running our own experiments ahead of customer demand. This allows us to operationalize validated methods into repeatable collection systems at scale. Data is collected through private invite-only applications separated by modality, customer, and trust level. Every submission remains linked to the contributor, device, task, session, consent, rights, and processing history that produced it, giving our internal QA and fraud models the context to detect problems that may appear legitimate in the finished file. Each collection reveals new failure cases and quality signals that improve the systems behind the next dataset. Once a collection method is validated, it becomes a reusable data recipe for future custom projects or independently collected, rights-cleared data products. This allows Datoric to turn what is emerging at the frontier into datasets available ahead of broader market demand.
Founders
Nikhil Reddy
Founder
CEO @ Datoric. Prev Quant & SWE Intern. Math/Econ/CS @ UChicago; Bypassed Google OAuth 2.1 and QA testers to automate 15,000+ hours on paid data annotation sites in early 2023.
Jeffrey Lin
Founder
CTO @ Datoric. Prev AI/ML & SWE Intern. Math & CS & Robotics at NYU.