Bridging biology and vision models.
AquaHealth started because visual inspection — the thing that actually catches most problems early in fish and shrimp farming — doesn't scale past a handful of sites. We're building the software layer that gives it a second set of eyes.
Our Vision
A world where no commercial fishery — finfish, shrimp, or hatchery — loses yield to a problem that was visible in a photo days before it became a crisis.
Our Mission
To give B2B aquaculture operators — starting in Nigeria, then across Africa — a subscription AI copilot that reads the inspection photos they already take and turns them into early, reviewable flags — no hardware to buy or install.
The Core Problem
In commercial aquaculture, by the time a stress event or a parasite outbreak is obvious to everyone on the team, days of preventable yield are already lost. Manual visual inspection works, but it depends entirely on a trained eye covering every tank, every day, and remembering what looked different yesterday. Past a few sites, that's not consistent — it's just hope.
We started AquaHealth on a simple bet: your team is already taking inspection photos. If a model can read those photos as well as a second technician, you don't need new hardware — you need a second opinion that never gets tired.
Our Founding Team
Deep expertise across commercial hatchery operations and hyper-scale cloud AI.
Onyedika Onuorah Ikechukwu
Co-Founder & CEO
Co-founder of AquaHealth. Leads product and spends most weeks talking directly to the early pilot operators using the tool.
Peace Oyaleke
Co-Founder & CTO, ML Architect
Peace builds and trains the computer vision models behind every flagged photo, and the pipeline that turns an upload into a reviewable finding.