GRID Ventures
VC Fund
New York, United States
Grid Ventures is a startup studio based in New York City.
- Total investments:
- 2
- Last investment:
- Lead investor:
- 0%
Last updated:
For AI agents: llms.txt
Industries GRID Ventures invests in
Stages GRID Ventures invests in
Countries GRID Ventures invests in
Contacts
| Name | Phone | Socials | |
|---|---|---|---|
Michael Scissons
|
|||
Investment Focus
Industry
- Robotics 1 (50%)
- Health Care 1 (50%)
- Electric Vehicle 1 (50%)
- Machine Learning 1 (50%)
- Autonomous Vehicles 1 (50%)
Stage
- Seed 1 (50%)
- Series B 1 (50%)
Team
| Name | Title | Investments | Links | |
|---|---|---|---|---|
|
Michael Scissons
Founder, Chairman & Managing Director
|
Founder, Chairman & Managing Director | Total investments: 1 | Find email |
Investments
| Company | Description | Round | Links |
|---|---|---|---|
Syntegra
|
Syntegra applies state-of-the-art machine learning models to create validated, synthetic data derivatives of health care data that match all of the statistical properties of the underlying data, but guaranteed to contain none of the original data, and cleared of privacy issues. Healthcare systems and data aggregators are forced to impose evergreater barriers to clinical data access. Syntegra is unique in developing a very large, open-access data platform of high quality, patient-level real-world data, trained using modern machine learning methods on health system information. Users can leverage our platform to conduct analytics, building predictive models, generating synthetic control groups for clinical trials and more.Since training is done on data at rest, and only deep learning model parameters are sent from the Syntegra API to the Syntegra servers, there is no risk of identifiable personal information leaving our secure platform. To satisfy health system security teams and end-users, numerous methods of validation, leak-testing and benchmarking are applied to the data derivatives before they pierce the health system’s firewall. Syntegra’s solution is scalable, and usable across many types of data, from images to financial information to sensor streams, will be securely added to our data lake over time. The company is led by a team of extraordinary serial entrepreneurs and university faculty with deep knowledge in medicine and data science. | $5.6M / Seed / Aug 28, 2020 | |
Optimus Ride
|
Optimus Ride is a self-driving vehicle company based in Boston, MA. It designs technologies to enable efficient, sustainable, and equitable mobility systems and solutions.As an MIT spinoff company, it combines over 30 years of interdisciplinary university research in self‑driving technologies (DARPA Urban Challenge), electric vehicles (CityCar),and Mobility-on-Demand Systems. The team includes decades of industrial and entrepreneurial experience that combines manufacturing robots, urban design, and shared vehicle fleet management. | $50M / Series B / Nov 06, 2019 |
Co-Investors
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FAQ
What does GRID Ventures invest in?
GRID Ventures invests primarily in Robotics, Health Care and Electric Vehicle startups, most often at Seed and Series B stage. Most of the 2 investments tracked by Shizune back companies in United States. The Investment Focus section breaks down every industry, stage and country in the portfolio.
How do I contact GRID Ventures?
Public channels for GRID Ventures include LinkedIn and the website linked on this profile. For a verified work email and phone number, create a free Shizune account — contact data is searched across 20+ sources and validated before delivery, so your outreach lands in the right inbox.
Who are the partners at GRID Ventures?
The team at GRID Ventures includes Michael Scissons (Founder, Chairman & Managing Director). The Team section lists each member with their title, investment count and links.
Is Shizune's investor data accurate?
Yes — every stat on this profile is calculated from confirmed public funding rounds monitored across hundreds of sources since 2020. This profile was last refreshed in Aug 2026 and is updated monthly. Spotted something off? Use the “Suggest an edit” link near the top of the page.
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