FAQ.
We invest in Pre-seed and Seed companies. Our model enables us to flex up or down, but our initial check is typically 750k-$1.5M. We structured our fund to give founders the best advantage at the most critical early stage, meaning: we right-size checks to what your company needs. The result is less dilution for you and greater latitude to bring the best partners into your round, while focusing our time on your company growth.
We typically make investment decisions within 1-2 weeks, following the first meeting. We meet once over Zoom or in person with prospective founders, and then bring in the rest of the team for a couple more meetings. We don’t require consensus, but all of us have to be excited about every investment.
We’re focused on AI native companies. We look at the founders, the opportunity they’re going after, and how they think. We ask ourselves: What about this person and their history demonstrates they can do things that are extremely unlikely? In what ways are they reinventing an existing market, or creating a totally new one? And what is it about these individuals that give them an innate edge?
We focus on product and go-to-market because that’s where our team has a lot of experience. Right after the investment, we set-up a WhatsApp thread with each founding team so we can jump in on any big challenges or critical milestones. That often leads to calls or in-person sessions, plus introductions to key people in our circle. We are highly responsive, and we take our role with each company seriously.
We poll our founders regularly for feedback, here’s what they say.
AI companies are built differently.
We're a crew of product and go-to-market leaders from OpenAI, Meta, Twitter, and a16z. We exist to back the world's best AI native founders and help them reshape our world for the better. We go wide on product and deep on GTM. We are most often the first backer, and we invest selectively so we can give our maximum time and effort at the critical early stages.
We surround ourselves with some of the greatest minds in technology.
Our founders aren't a portfolio - they're our people.
Companies past and present.
Whatnot
The largest live shopping platform in the US, UK, and Europe.
Baseten
Building the infrastructure layer for AI inference at scale.
SpaceX
Designs, manufactures, and launches advanced rockets and spacecraft.
Figma
The leading collaborative design tool for building meaningful products.
Abridge
Enterprise-grade AI for Clinical Conversations
Poolside
Generative AI to speed up software development.
Sunday Robotics
Developing AI agents designed to deeply understand and interact with the physical world.
Statsig
Modern product development platform that helps teams run experimentation (like A/B tests), manage feature rollouts, and analyze product performance in one unified, data-driven solution.
Periodic Labs
Building “AI scientists” and autonomous labs to accelerate materials discovery—moving from simulations and predictions to closed-loop, automated experimentation in the physical world.
Stoke Space
Seamless mobility to, through, and from space.
Motherduck
A serverless, easy to use data analytics platform.
Peregrine
Provides a real-time crime intelligence and data analytics platform that helps public safety and government agencies integrate and analyze disparate data to make faster, smarter decisions in critical operations.
Aptos
Web3 technology company building scalable, secure infrastructure and products on the Aptos blockchain, a high-performance Layer-1 network designed to accelerate decentralized applications and mainstream blockchain adoption.
Mitra Chem
Building a North American battery materials champion.
Hadrian
Building the factories of the future for the advanced and precision manufacturing industries (space, defense, energy, semiconductor, medical devices).
Streamline
AI for in-house legal intake, workflows, and reporting.
Superdial
AI that automates outbound healthcare phone calls.
Atmo
Ultra-precise AI-weather forecasting.
Applied Compute
Unlocking the knowledge inside a company to train custom models and deploy an in-house agent workforce.