Algae Risk Monitoring
AI-based early warning of harmful algae risk for fish farms.
Not just an alert, but a clear action plan for each site and each pen.
Algae Risk Monitoring brings together water data, weather signals, lab results, and farm operating data to show where risk is building, when intervention is needed, and what actions to take next. AI models help surface patterns earlier, prioritize the most exposed sites and pens, and support faster operational decisions.
Problem
Why the current response process is often too slow
When algae risk starts rising, decisions are often made under pressure and based on fragmented data. Teams have to manually gather signals from different sources, align the context, and coordinate actions across biology, operations, and management. That slows the response and increases the risk of losses.
What usually happens:
- Signals appear in different systems at different times.
- Risk is detected late, when the window for lower-impact actions is already narrow.
- There is no single decision trail explaining why a specific decision was made.
- After an incident, it is difficult to run a strong review and improve the process.
Solution
Turn fragmented signals into faster, more defensible decisions
Algae Risk Monitoring integrates with your existing monitoring environment and strengthens current workflows without requiring a full infrastructure replacement.
The platform provides:
- Risk forecasts for each site and pen 24-48 hours ahead.
- Clear explanations of which factors are driving risk right now.
- Playbook-based actions: what to do now, what to prepare, and what to monitor next.
- A complete decision log for internal control and audits.
Team outcomes:
- Faster intervention at the early stage.
- Less noise and fewer false alarms.
- A shared operating language across biology and operations.
- A controlled process instead of manual firefighting.
How It Works
- Data Collection. Connect external and internal sources, including water conditions, lab results, weather and hydro data, welfare data, and operational events.
- Risk Assessment. A risk model calculates exposure for each site and updates the score every few hours.
- Action Playbooks. For each risk level, the system suggests concrete actions with priority, deadline, and owner.
- Audit Trail. The decision context is stored: signal, recommendation, completed action, and outcome.
Who It Is For
Teams that need a practical pilot, not another passive dashboard
- Production leaders and site managers.
- Fish health and veterinary teams.
- Operations directors and quality/compliance functions.
- Companies with multiple sites and distributed teams.