ManufacturingAI Consulting & Strategy7 Weeks
Brackish Oyster Farms manages 26 lease sites and 11 million oysters a year across the Gulf Coast, and harvest timing still ran on manual water pulls and crew instinct. We assessed where AI fit into their field operations, deployed monitoring and forecasting tools, and trained their growers to work from predictive data.
31K
Seasonal Mortality
3.5 hrs
Daily Time Reclaimed
$174K
Recovered Yield

“The team makes faster decisions with better information and it's showing up in the numbers.”
Margaret Moore
Operations Manager, Brackish Oyster Farms
Before
4 hour daily sampling runs, 130K seasonal oyster losses, Harvest timing by crew instinct
After
Continuous sensor monitoring, 31K seasonal losses, Forecasting dashboard harvest calls
Narrative
The Challenge
Brackish's crew was spending about 4 hours before first light each day on water sampling across active beds just to decide which sites were ready. That process still missed the mark often enough to cost roughly 130,000 oysters per season to mortality or poor shell quality, around $185K in yield left on the table. The team had tested sensors twice before but couldn't get the right tools matched to tidal lease conditions or get the crew comfortable enough with the output to actually change how they worked.
What We Built
We ran a 12 day assessment alongside Brackish's crew leads, mapping every decision from water checks through harvest scheduling and grading. We put continuous water quality sensors on all 26 sites feeding into an AI forecasting tool for harvest windows, added a mobile alert system the crew could pull up from their boats, and ran six training sessions with the 8 growers and operations manager over three weeks. 13 days after training wrapped, the crew was calling harvests from the dashboard without reverting to manual pulls.
Results
Harvest timing went from about 6 good calls out of 10 to 9 out of 10 across all sites. Seasonal losses from mistimed harvests came down from 130,000 oysters to under 31,000. The crew picked up 3.5 hours a day that had been going to sampling runs. The $68K engagement brought back an estimated $174K in recovered yield over the first growing season.
Technical proof
Implementation details and the stack behind the delivery.
Implementation highlights
Key engineering decisions from this project.
Stack snapshot
Tools and platforms used in the delivery.
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