BiOceanOr provides AI-powered underwater weather stations that monitor key water quality parameters such as dissolved oxygen and temperature, enabling fish farmers to anticipate environmental changes. This data-driven approach enhances fish health and growth while mitigating operational risks in aquaculture.
Funding
$3.4M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Aquaculture faces challenges in maintaining optimal water quality, as fluctuations in parameters like dissolved oxygen and temperature can negatively impact fish health and growth. Traditional monitoring methods may lack the real-time insights needed to proactively manage these environmental changes and mitigate operational risks.
Solution
BiOceanOr offers AI-powered water quality services that provide fish farmers with real-time analytics and predictive capabilities. The AquaREAL platform collects data from hardware-agnostic sources, analyzes key water quality parameters, and generates 48-hour rolling forecasts for dissolved oxygen, temperature, and harmful algal blooms (HABs). By leveraging machine learning models trained on over 200 million data points, BiOceanOr helps anticipate risks, optimize feeding windows, and improve overall fish welfare and sustainability. The platform delivers actionable insights through reporting, efficiency meetings, and visualizations designed to enhance control over aquaculture operations.
Target Audience
The primary target audience includes fish farmers and aquaculture operations seeking to improve fish health, optimize feeding strategies, and mitigate risks associated with fluctuating water quality conditions.
Features
- Hardware-agnostic data collection for integration with existing monitoring systems
- Real-time water quality analytics with correlation and bio-guided services
- 48-hour rolling forecasts for dissolved oxygen, temperature, and harmful algal blooms (HABs)
- Machine learning models trained on extensive historical data
- AquaREAL platform for visualizing forecasts and identifying optimal feeding windows
- Reporting and efficiency meetings for tailored support
- Early warning services to anticipate risks and reduce operational expenses (OPEX)