P.01
Locked in the vendor's cloud
Readings go to the device maker's servers first. Access depends on their terms, and in 2026 those terms tightened.
The open data layer under wearables
Wearable data, straight from the device, into the AI you choose.
Otolo reads supported wearables directly over Bluetooth, keeps the raw readings in open files on your own phone and computer, and serves them to Claude, ChatGPT or a local model. No vendor cloud in between.
- Working prototype today
- Open-source core: early 2027
- iOS and Android
Example session.
Why nowBody data got more useful as it got harder to reach.
46%
of US adults own a wearable.
Rock Health, Dec 2025 survey2026
Oura and Strava restrict passing their data to AI, Garmin paused new developer access, and the Fitbit Web API shuts off on 2 November.
Google Health developersMCP
One open standard lets Claude, ChatGPT and local models use outside data and tools.
Model Context Protocol01 / Problem
Your devices measure you. The data rarely comes back to you.
P.02
A score, not the signal
Data comes back as a vendor's score. Raw measurements, and the method behind them, stay out of reach.
P.03
No history you can move
Switching devices means losing your history. Using the data in your own AI means trusting yet another cloud.
02 / How it works
Capture locally. Store in open files. Serve to the AI you choose.
Otolo reads supported devices to your phone and computer, keeps the readings in files you can open and move, and serves them through MCP, an open standard supported by Claude, ChatGPT and local models.
03 / For teams
Built for teams that run studies and programs on many people and many devices.
Research and R&DFirst offer
Multi-device studies
Run studies across many people and devices, with raw readings in open files and no vendor terms in the way.
AI and L&D leaders
Otolo Cohort
Your champions build working AI agents on data they capture themselves. Each person's body data stays with them.
DevelopersFree
Otolo Core
Open source and local. Connect a supported device to the AI you already use in minutes.
04 / Why Otolo
The open data layer under wearables.
Cloud aggregators read vendor clouds. Device makers keep data inside their own apps. Open phone apps read devices but stop at the phone. Otolo reads supported devices directly, stores the data in open files you control and serves it to the AI you choose.
| Capability | Cloud aggregators | Single ecosystems | Open phone apps | Otolo |
|---|---|---|---|---|
| Reads devices directly, without the vendor cloud | No | Own devices | Yes | Supported devices |
| Data on your computer, in open files | No | Export only | On the phone | SQLite, Parquet |
| Works with the AI you choose | Through apps | Limited | No | Any MCP client |
| Multi-device studies for R&D teams | Yes | No | No | Yes, device-direct |
05 / Company
Free for people. Teams and programs pay.
Otolo Core is free and open source. Revenue comes from studies and cohorts first, then a platform API and our own open, low-cost wearable.
- Now
Teach and measure
Ship the open core, first studies and cohorts, and publish accuracy data for the first supported devices.
- Next
Open the platform
A growing driver library and a platform API for builders, labs and partners.
- Then
Our own instrument
An open, low-cost wearable, first for programs, labs and makers.
- Ahead
The default layer
Large programs and consumers on an open, trusted data layer.
06 / Founder
Built by a bioengineer who has shipped body-sensing hardware.
Stephen Robinson, PhD
Founder and CEO
- EducationPhD in Bioengineering, Georgia Tech
- EducationMBA, UCLA Anderson (FEMBA, Class of 2027)
- ExperienceMedical device product management
- ExperienceConsumer hardware Kickstarter campaigns
- ExperienceSystems engineering; Robinson Tech Design LLC
- TeachingDeveloping an applied AI workshop series at Anderson
HiringHiring a technical co-founder for mobile Bluetooth and device drivers. See the role.