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.

Built on curiosity, collaboration, and continuous learning, Current Sight is exploring how artificial intelligence can make fish monitoring more efficient, scalable, and actionable—so the people doing the work can spend more time restoring rivers and less time processing data.

96.6%
Species ID accuracy & improving
9,100+
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?

Technology with Purpose

Built for the people doing the work

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

Technology should never replace experience in the field—it should strengthen it by providing better information, saving valuable time, and helping people make better decisions.

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Live analysis

Current Project

Building Current Sight

Current Sight is an independent conservation technology project focused on developing underwater computer vision for fisheries monitoring.

01

Building & Validating

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

02

Growing the Dataset

A dataset exceeding 9,100 annotated underwater images, recognizing 9 fish classes including life-stage variations.

03

Preparing for the Field

Improving real-world performance through continuous testing and preparing for future edge deployment and live river monitoring.

Every new image, every field day, and every conversation helps improve the project.

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California watershed · Current Sight field work

Follow the Journey

Every project has a story

Current Sight is more than a technology project. It's a journey of learning, problem solving, collaboration, and conservation.

The Field Notes document that journey honestly—from first ideas and early mistakes to field testing, partnerships, and lessons learned along the way.

If you're interested in conservation, computer vision, or simply enjoy watching ideas become reality, I invite you to follow along.

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Field Work

Days on the river collecting data

Technology

Building & training the model

Collaboration

Learning from fisheries professionals

Lessons Learned

What's working and what isn't

Milestones

Progress worth celebrating

Let's leave it better than we found it.

Meaningful conservation doesn't happen overnight. It grows through curiosity, collaboration, persistence, and countless small improvements made over time. Current Sight is still in its early chapters, and that's part of what makes the journey exciting. Thank you for being here.

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