Unusual Ventures

Unusual Ventures, established in 2018 and headquartered in Menlo Park, California, is a venture capital firm specializing in early-stage investments. It focuses on pre-seed and seed-stage companies, providing not only capital but also hands-on support and expertise. The firm invests in enterprise software, consumer products, and fintech, with a typical investment size ranging from $250,000 to $7 million. Unusual Ventures also runs educational programs like Unusual Academy and Get Ahead to support and invest in early-stage startups.

Lars Albright

General Partner

Tyler Crown

Vice President

Haley Daiber

Senior Associate

Andrew Johns

Partner

Sarah Leary

Venture Partner

Dakota McKenzie

Senior Associate, GTM

Eric Peter

Partner

Scott Schwarzhoff

Operating Partner - Founder Services

Rachel Star

Principal

Guergana Tomova

CFO

John Vrionis

Founder and Managing Partner

Ryan Wexler

Vice President

Past deals in Streaming

Chalk

Seed Round in 2023
Chalk is a data platform designed to enhance the deployment of machine learning and generative AI by streamlining data infrastructure. It provides a robust developer experience, allowing data teams to define features and their dependencies using Python across various environments, including online, streaming, and batch processing. Chalk compiles these definitions into efficient parallel pipelines that operate on a Rust-based engine, ensuring that training sets for data scientists and live feature values for models remain temporally consistent. This approach minimizes discrepancies between online and offline contexts, significantly reducing development time. By managing data infrastructure, Chalk allows engineers, data scientists, and analysts to concentrate on their specific projects, facilitating better access to analytics and machine learning capabilities.

Databento

Series A in 2021
Databento offers a streamlined platform for accessing financial market data, founded by professionals with backgrounds in trading and engineering from leading quantitative hedge funds. The company provides a self-service model that allows users to access live exchange feeds and vast amounts of historical data efficiently. Clients can choose between a pay-as-you-go system or flat-rate pricing, providing flexibility based on their needs. By hosting servers in colocation facilities at various trading venues, Databento ensures low-latency and high-fidelity data capture directly from the source. Its platform also automates data licensing and reduces onboarding time, making it easier for businesses and financial institutions to obtain reliable, institutional-grade data while minimizing storage costs.

Databento

Convertible Note in 2021
Databento offers a streamlined platform for accessing financial market data, founded by professionals with backgrounds in trading and engineering from leading quantitative hedge funds. The company provides a self-service model that allows users to access live exchange feeds and vast amounts of historical data efficiently. Clients can choose between a pay-as-you-go system or flat-rate pricing, providing flexibility based on their needs. By hosting servers in colocation facilities at various trading venues, Databento ensures low-latency and high-fidelity data capture directly from the source. Its platform also automates data licensing and reduces onboarding time, making it easier for businesses and financial institutions to obtain reliable, institutional-grade data while minimizing storage costs.

Sunshine App

Seed Round in 2020
Sunshine App enables to instantly and easily share, access and stream content across any device - without cloud storage. No uploading, no downloading; simply streaming content device-to-device on the fly. Sunshine, formerly ShareON, was founded by a former Samsung design engineer whose vision was to advance the way anyone could share or access files across their devices.

Chalk

Chalk is a data platform designed to enhance the deployment of machine learning and generative AI by streamlining data infrastructure. It provides a robust developer experience, allowing data teams to define features and their dependencies using Python across various environments, including online, streaming, and batch processing. Chalk compiles these definitions into efficient parallel pipelines that operate on a Rust-based engine, ensuring that training sets for data scientists and live feature values for models remain temporally consistent. This approach minimizes discrepancies between online and offline contexts, significantly reducing development time. By managing data infrastructure, Chalk allows engineers, data scientists, and analysts to concentrate on their specific projects, facilitating better access to analytics and machine learning capabilities.
Spot something off? Help us improve by flagging any incorrect or outdated information. Just email us at support@teaserclub.com. Your feedback is most welcome.