Feed conversion loss, early mortality signals, equipment deviation — the data showing these events is already in your systems. Eyer's autonomous AI reads it continuously and alerts your team before drift becomes damage.
RAS and CCS operations generate more data per facility than ever before. But data and insight are not the same thing. Threshold alarms fire constantly on non-events. The signals that matter — slow FCR drift, early oxygen deviations, equipment wear patterns — arrive below the threshold and get lost in noise.
FCR degrades gradually — 0.05 points at a time — across multiple tanks or pens before any operator notices. By the time it registers on weekly reports, the cost is already incurred.
$1.1–1.3M per 0.1 FCR per 5,000t cycleOxygen crashes, disease outbreaks, and other mortality events are preceded by hours or days of anomalous sensor patterns. The data was there. It wasn't read in time.
$0.16–0.32/kg on 8% mortality reductionPumps, aerators, filtration systems, and feeders degrade gradually. The performance signature of a failing component exists in your sensor data weeks before failure — threshold alarms only fire at breakdown, not before.
Planned vs emergency maintenance: 3–5× cost differenceDowngraded fish from superior to production grade is one of aquaculture's most predictable and preventable margin leaks. Stress, handling deviation, and water quality drift are detectable weeks before harvest.
$0.53–1.05/kg on superior → production downgradeEyer's AI builds a dynamic baseline for every metric you ingest — across tanks, pens, sites and systems. Baselines update automatically as production conditions change. No data scientists. No rule configuration. No threshold management.
Detect correlated deviations across dissolved oxygen, CO₂, ammonia, nitrite, temperature, pH, and flow — before they affect fish health.
Correlate feed dispensed, appetite signals, and growth curve deviations to surface FCR drift in real time — by pen, by site, with root cause context.
Detect wear patterns and performance deviations in pumps, aerators, feeders, and filtration before failure — planned maintenance instead of emergency intervention.
Eyer ingests from SCADA historians, sensor APIs, feed management and MES outputs. No migration. No changes to existing infrastructure.
Eyer's models map normal operating behaviour across all connected metrics — automatically accounting for production phase, stocking density, and environmental conditions.
Your team receives correlated, context-rich alerts via Slack, SMS, email, or any webhook — with indication of affected systems and likely downstream impact.
API-first. No proprietary sensors. No replacement of existing systems. Eyer adds an anomaly detection layer on top of what you already have.
Eyer is part of ABB Synerleap — ABB's program for technology companies building solutions for operational environments. Selected from applicants across 30+ countries, Eyer works alongside ABB's global network of industrial customers and R&D teams.
Before you commit to a live integration, we run Eyer against your historical sensor and process data — and show you the anomalies, drift patterns, and correlated events that were present but not detected at the time.
If Eyer finds nothing meaningful, we tell you directly. We only pursue live integrations where the proof of value is clear.
Request received.
We'll be in touch within 2 business days to discuss your data and arrange the historical analysis.
