Aquaculture technology developer Aquaticode has officially launched AquaLens, a real-time, AI-driven optical scanning system designed to automate the detection and sorting of deformed juvenile fish in hatcheries.

Key Details

• High Throughput: A single AquaLens unit can process and sort up to 350,000 fish per day without manual handling, accelerating a task traditionally reliant on manual labor by 15 to 30 technicians per shift.
• Multi-Angle AI Precision: Utilizing deep learning and multi-camera imaging, the system evaluates juveniles weighing between 1 and 10 grams. It scans for deformities in the operculum, jaw, snout, spine, and fins with near 100 percent accuracy before using soft-touch mechanism sorting to separate commercial-grade stock.
• Pay-per-Fish Model: Offered under a Service (SaaS/HaaS) structure based on sorted volume, eliminating heavy upfront capital expenditure for hatcheries.
• Proven Track Record: Built on Aquaticode’s existing SORTpro salmon platform, the technology is rolling out initially in sea bass and sea bream hatcheries, with additional finfish species adaptations following.

For trout hatcheries managing high-density fry and fingerling raceways, early identification of skeletal and opercular deformities is critical to maintaining feed conversion ratios (FCR) and farm profitability:

• Feed & Space Efficiency: Deformed juveniles that bypass early manual culling consume feed and occupy raceway volume for months, dragging down batch uniformity and processing yields at harvest.
• Labor Relief: Manual grading is labor-intensive and subject to operator fatigue across long shifts. Automated grading maintains uniform standards from the start of a run to the end.
• Flexible CAPEX: As machine learning vision expands across finfish aquaculture, no-upfront-cost service models make automated phenotyping accessible to regional facilities looking to modernize stock management.