Predictive Maintenance · Real-time Analytics
Ceto AI needed to turn massive streams of real-time vessel data into usable anomaly and root-cause insights so it could prevent machinery failures, streamline fleet operations, and manage maritime insurance risk.
Reported impact
Ceto AI can predict and preempt equipment failures earlier, deploy models quickly, and give maritime operators and insurers more proactive visibility into operational risk.
Ceto AI built its maritime decision-support platform on MongoDB Atlas and Atlas Vector Search so it could combine machine learning with real-time fleet telemetry without locking itself into rigid schemas. Thousands of onboard sensors feed high-frequency vessel data into Atlas, where Ceto stores rapidly growing data sets and labels 'points of interest' around anomalies. Atlas Vector Search adds contextual retrieval for those labeled events, helping the platform relate fresh anomalies to similar patterns and likely root causes. That lets Ceto surface AI-driven guidance for insurers and ship operators before failures escalate. Because Atlas scales without heavy schema management, the team can plug in new data quickly, deploy models faster, and keep a single operational store for ingest, context building, and predictive decision support as fleets grow.
Telemetry from thousands of sensors across customer fleets is ingested into MongoDB Atlas, where Ceto labels points of interest and stores anomaly context; Atlas Vector Search then retrieves similar patterns so AI and ML models can propose likely causes and preventative actions for operators and insurers.
Vector Search is becoming more and more important in our decision support system.
We capture and analyze high-frequency data to prevent machinery breakdowns and deliver connected insurance products to ship owners.
We needed a non-relational database that can scale that we don't have to be worrying too much about schemas for.
We're using machine learning models and AI models to detect these patterns and spot trends, similarities, and anomalies before we typically could.
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Scoring methodology
Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.
Traceability
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The contact page states: 'CetoAI is registered in the UK under no 12472339 at Hoults Yard, Mailing Exchange 120, Walker Road, Newcastle Upon Tyne, NE6 2HL, United Kingdom.'
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