Datoric
YC S26 · Active · The secure training data R&D engine for physical AI
Competitors
| Company | Category | Status | Program |
|---|---|---|---|
| MaxinsightsShared: training data, physicalNot statedAI, Devtools | AI, Devtools | Not stated | SPC2025 |
 SureformShared: data labeling, robotics, trainingActiveAI, Data | AI, Data | Active | YCX25 |
 Moving AtomsShared: training data, data labeling, roboticsActiveAI, Data | AI, Data | Active | YCS26 |
 HubShared: training data, robotics, frontierActiveAI, Data, Devtools | AI, Data, Devtools | Active | YCX26 |
 SenseiShared: training data, robotics, collectionActiveAI, Data | AI, Data | Active | YCS24 |
Adjacent
| Company | Category | Status | Program |
|---|---|---|---|
 The Robot Learning CompanyShared: robotics, machine learning, physicalActiveAI | AI | Active | YCX25 |
 Sepal AIShared: training data, data labeling, modelAcquiredAI, Data | AI, Data | Acquired | YCS24 |
 Mundo AIShared: training data, machine learning, modelActiveAI, Devtools | AI, Devtools | Active | YCW25 |
 LightlyShared: data labeling, machine learning, modelActiveAI, Data, Devtools | AI, Data, Devtools | Active | YCS21 |
 SpadeShared: data labeling, machine learning, modelActiveAI, Data | AI, Data | Active | YCW22 |
Also from S26 in AI
All of S26| Company | Category | Status |
|---|---|---|
 CoArenaThe biggest crowdsourced benchmark for Computer-UseActiveAI, Data, Devtools | AI, Data, Devtools | Active |
 DeepReach Inc.Network for Physical AI Data BusinessActiveAI | AI | Active |
 6thSenseNervous System for Physical AIActiveAI | AI | Active |
 Agnost AIWe find where AI agents fail, then train better models to run them.ActiveAI, Data, Devtools | AI, Data, Devtools | Active |
 BelvedirThe custom AI model factory.ActiveAI | AI | Active |
 DreamUsing VLMs to Catch DamageActiveAI | AI | Active |
Founders
- Nikhil ReddyFounder/CEO
- Jeffrey LinFounder/CTO
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 and model failures 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, we scale it up as a solution to the model failure and it also becomes a reusable data recipe for future custom projects or independently collected, rights-cleared data products.
- YC batch
- S26 · Summer 2026
- Status, per YC
- Active
- Category
- AI, Data
- Team size
- 2
- Location
- San Francisco, CA, USA
- Founded
- 2025
- Checked
- 32m ago
YC tags: Artificial Intelligence, Machine Learning, Robotics, Data Labeling
Datoric: questions
Which YC batch was Datoric in?
Datoric was in Y Combinator's Summer 2026 batch (S26).
Is Datoric still active?
Y Combinator lists Datoric as active.
Who founded Datoric?
Datoric's founders, as listed on its YC page: Nikhil Reddy (Founder/CEO), Jeffrey Lin (Founder/CTO).
Where is Datoric based?
Datoric lists San Francisco, CA, USA as its location on YC's directory.
Sources: each program's public company list, read twice a week. Not affiliated with Y Combinator or any other program. Logos via logo.dev; trademarks belong to their owners.