Our Mission

Every year, vegetation causes billions of dollars in damages to critical infrastructure. Trees fall on power lines, causing outages and wildfires. Roots damage pipelines. Overgrowth blocks telecommunications signals.

The tools available to manage this risk haven't kept pace. Most organizations still rely on manual inspections and reactive maintenance—identifying problems only after they've already caused damage.

Canoptics is changing that. We combine satellite imagery, LiDAR, and machine learning to predict vegetation growth and risk before failures occur. Our goal is simple: no outage, wildfire, or insurance claim should ever be caused by a tree someone should have seen coming.

Forest canopy aerial view

Our Values

Accuracy Over Speed

Our customers make critical decisions based on our data. We'd rather be slower and right than fast and wrong. Every model is validated against ground truth.

Customer Obsession

We build for the vegetation manager in the field, not the executive in the boardroom. If our tools don't work for the people using them daily, we've failed.

Transparency

We show our work. Every risk score comes with confidence intervals and the factors that drove it. No black boxes.

Leadership Team

Our team combines deep expertise in remote sensing, machine learning, and utility operations.

Sarah Chen

CEO & Co-Founder

Previously VP Engineering at Planet Labs. PhD Remote Sensing, Stanford.

Marcus Rodriguez

CTO & Co-Founder

Former ML Lead at Google Earth. MS Computer Science, MIT.

Jennifer Walsh

VP Operations

20 years in utility vegetation management. Former Director at PG&E.

David Park

VP Sales

Built enterprise sales at Samsara and Uptake. MBA, Wharton.

Backed by the best

We're fortunate to be supported by investors who understand infrastructure and climate.

Andreessen Horowitz
Lux Capital
Congruent Ventures
Energy Impact Partners

Join our team

We're hiring across engineering, sales, and operations. Help us build the future of vegetation intelligence.

View Open Positions →