About Sigma5
Sigma5 builds hyperspectral sensors and AI software that reveal what objects are made of, not just their shape. The sensors can tell transparent and reflective objects apart, judge textures for robotic grasping, flag crop stress, detect gas and fluid leaks, and track stages of corrosion. The platform combines this sensing with world models and AI reasoning layers so robots and existing cameras can use the added information.
The company is based in Santa Cruz, California. It was founded by Kevin Bundy, a professor of astronomy and astrophysics at UC Santa Cruz, along with Jay Bartels, Doug Lee, and Matthew DeMartino. Bartels serves as chief financial officer, Lee as chief technology officer, and DeMartino as chief hardware officer.
Funding Rounds (SEC Form D)
| First sale | Filed with SEC | Amount sold | Investors | Avg. check | Terms | Filing |
|---|---|---|---|---|---|---|
| Oct 6, 2026 | Nov 4, 2026 | $270,000of $500K target | 3 | $90,000 | Simple Agreements for Future Equity (SAFEs), convertible into equity securitiesRule 506(b) | Form D ↗ |
First sale is the date the first investor in the offering committed to invest. Companies must file Form D within 15 days of that date, so filing dates run later.
Why Investors Backed Sigma5
Sigma5 builds hyperspectral sensors and AI software that reveal what objects are made of, not just their shape. The Santa Cruz, California startup was founded by astrophysicists and Silicon Valley engineers. Its platform aims to serve agriculture, energy, infrastructure, and robotics companies that need to measure material condition. Sigma5's case is that pairing spectral sensing with AI reasoning can open up new kinds of automated measurement that used to need costly lab testing.
The problem it targets
Cameras and LiDAR sensors can map the shape and location of objects but cannot tell what they are made of. Sigma5's case is that this gap leaves industries measuring crop stress, gas leaks, and corrosion by hand, or not measuring them at all.
What the product does
Sigma5 splits its platform into four layers. A perception layer reads spectral signatures that plain cameras and LiDAR cannot pick up. An AI and machine-learning layer trains models on that data and also sharpens ordinary camera readings. A world-data layer builds up a growing record of material and condition data over time. A deployment layer applies the models across agriculture, energy, infrastructure, and robotics uses.
We wrote this summary from public statements by Sigma5 and its investors. It is not investment advice.
Leadership Team
Executive officers and directors listed on Sigma5's Form D filed Nov 4, 2026.
