Our story
From an experiment to a mission
Travis Comfort grew up on California's Eel River — a watershed defined by its wild steelhead, its history of over-extraction, and its ongoing struggle toward recovery. That upbringing shaped both his reverence for aquatic ecosystems and his frustration with how poorly equipped most conservation efforts are to understand them at scale.
A technology innovator and designer by trade, Travis spent years working at the intersection of emerging technology and complex real-world problems. When he began talking seriously with conservationists, watershed groups, and fish biologists, a recurring theme emerged: the data gap.
"Organizations doing incredible restoration work were still counting fish by hand, reviewing hours of tape, and filing reports based on estimates. The tools hadn't kept up with the need."
So Travis began experimenting — starting with a simple question: could a computer vision model reliably identify salmon and steelhead from video footage collected in the field? The answer, after considerable testing, was yes. And that answer opened a much larger door.
What started as an experiment
The early prototypes were rough. But the signal was clear: intelligent video analysis could dramatically reduce the manual burden of fish monitoring while improving the consistency and reliability of the data being collected.
Current Sight was founded to develop that insight into practical, deployable tools — starting with software that works with existing camera infrastructure and growing toward a complete in-field monitoring system.
Conservation-first by design
From the beginning, Travis made a deliberate choice: Current Sight wouldn't lead with the technology. The goal isn't to build impressive AI — it's to help conservation organizations see more clearly, work more efficiently, and make better decisions for the rivers they protect.