Aquatic Conservation Technology

Leave it better than you found it.

Current Sight develops practical computer vision technology to help conservation professionals better understand and protect wild fisheries.

90.1%
Species ID accuracy & improving
7,500+
Annotated training images
Weekly
New training data added
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Technology isn't the mission. Conservation is.

Every project begins with a simple question:
How can we leave our rivers healthier
than we found them?

Computer vision in action

See the technology at work

Built on curiosity, collaboration, and continuous learning, Current Sight is exploring how artificial intelligence can make fish monitoring more efficient, scalable, and actionable.

In this clip, the model identifies a Sacramento Pike Minnow from underwater video — the kind of analysis that would otherwise require hours of manual review.

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Live analysis

Current Focus

Where we are in the work

01

Building & Validating

Developing and refining an underwater computer vision model for reliable species identification in real-world conditions.

02

Expanding the Dataset

Our training library now exceeds 7,500 annotated underwater images and grows with every field day.

03

Preparing for the Field

Improving species recognition across multiple fish classes and preparing for edge deployment and real-world field testing.

California watershed · Current Sight field work

Who we work with

Built for the people doing the work

Current Sight exists to build practical tools that support the scientists, biologists, tribes, and conservation organizations working toward healthier rivers.

Conservation Organizations

Watershed groups & land trusts

Watershed Councils

Restoration & habitat

State & Federal Agencies

Fish & wildlife depts.

University Researchers

Field teams & studies

Resource Managers

Hatcheries · Dam operators

Still in its early chapters.

Every new dataset, field day, collaboration, and lesson learned helps shape better technology — and, hopefully, better outcomes for our rivers.

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