First Spark Ventures

First Spark Ventures, founded in 2021 and based in Menlo Park, California, is a venture capital firm that focuses on investing in deep-tech startups globally. The firm specializes in sectors such as advanced computing, biotechnology, digital biology, and cyber-physical systems. First Spark Ventures primarily targets investment opportunities at the pre-seed, seed, and series A stages, aiming to support innovative scientists and entrepreneurs in developing cutting-edge technologies and solutions.

Danny Chen

General Partner

Peter Olcott

Principal

Gal Treger

General Partner

Jennifer Wu

Principal

Haitao Zhu Ph.D

Partner

4 past transactions

Walking Fish Therapeutics

Series A in 2022
Walking Fish Therapeutics is developing a platform to harness B cells’ capability to activate the immune system in the treatment of cancer, and to serve as in vivo protein factories that produce replacement proteins for deficiency diseases, regenerative proteins, and engineered antibodies.

Tauk

Seed Round in 2022
Tauk is a platform that enables developers to release their apps with confidence at massive scale.

Latent AI

Series A in 2021
Latent AI accelerates AI implementation and workflows for the enterprise cost-effectively anywhere on the edge continuum with Adaptive AI.

Syntegra

Seed Round in 2020
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 ever greater 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.
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