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How does Catchwise find optimal fishing areas?
Here you'll find information about how Catchwise uses AI to find optimal fishing areas.
What is this?
Catchwise's catch predictions are like Yr – but for fish. We use historical catch data and environmental data to predict where fish gather.
How does it work?
We combine: Historical catch data and recent fishing activity Environmental conditions (depth, current, temperature, plankton and nitrates) AI models that find patterns and connections
What ocean conditions and factors do we use for predictions?
Catchwise’s AI learns from thousands of fishing trips combined with environmental and seasonal data to predict where and when the chances of a good catch are highest. The model analyzes historical catches and recent fishing activity to identify patterns of where fish have been caught in the past. It also looks at ocean conditions—such as bottom temperature, plankton, nutrient-rich areas, nitrate, oxygen, and salinity—to understand which environments attract fish. In addition, the model uses weather data (wind and currents) to predict how fish are likely to move from day to day, along with seasonal factors like moon phase, seasonal trends, and light penetration in the ocean that influence fish behavior.
Can I trust it?
There's no definitive answer in fishing – but many skippers report that the AI tips match their own experience and that it's a practical tool that helps them make decisions based on history and ocean conditions without needing a marine scientist.
From logbooks to catch forecasts
AI isn't magic – it's just smart calculations based on patterns from thousands of previous fishing trips. We see it as a natural evolution of the old logbooks where skippers wrote down catches, weather, and conditions to find out when areas were best for fishing.
How do you use it?
You see recommended areas on the map – updated daily or every 6 hours. The colors show where the chance of catch is highest or where the expected catch rate is highest.