# AWSM VC

> AWSM VC is a pre-seed and seed venture capital fund backing the technical
> constraints that Physical AI (robotics and embodied AI) systems cannot scale
> without — robot data, simulation and sim-to-real, evaluation and safety, edge
> inference, manipulation, and fleet operations. Thesis: fund the constraint,
> unlock the system.

## About

- **Name:** AWSM VC (AWSM Venture Capital)
- **Type:** Pre-seed and seed venture capital fund
- **Focus:** The enabling layers of Physical AI — the "unglamorous middle" every robot program depends on, rather than robot hardware itself
- **Method:** The Pareto Constraint Method — every investment is scored on six questions: criticality, leverage, defensibility, productization, capital fit, and capture
- **Stance:** Analytical, selective, anti-hype. Aspirational claims are labeled as such; no track record is implied that has not been earned.
- **Contact:** hello@awsm.vc

## What AWSM VC invests in

The seven enabling categories (the "constraint map"):
1. Robot data — capture, curation, provenance, and feedback loops
2. Simulation and sim-to-real — synthetic data, digital twins, validation
3. Evaluation and safety — observability, regression, incident systems
4. Edge intelligence — inference, compute optimization, device-to-fleet orchestration
5. Manipulation — dexterous primitives, tactile sensing, force control
6. Fleet operations — teleoperation fallback, maintenance intelligence, coordination
7. Selective hardware — sensors, compute, power, hardware–software co-design where reusable

## Pages

- [Home](https://awsm.vc/): Fund thesis and overview
- [Portfolio](https://awsm.vc/portfolio.html): The constraint map, selection criteria, and portfolio construction
- [Team](https://awsm.vc/team.html): The people and operating principles behind the fund
- [Partners & Perks](https://awsm.vc/partners.html): The Frontier Stack — benchmark design, compute access, design partners, founder perks
- [Field Notes (News & Blog)](https://awsm.vc/news.html): Essays on the enabling layers of Physical AI

## For

- Founders building the data, simulation, evaluation, edge, manipulation, or fleet layer of Physical AI
- LPs seeking focused, honestly reported Physical AI exposure