Rifraux AI's Industrial Pilot lets manufacturers, oil servicing firms, and energy operators surface hidden losses in their sensor and operational data with a clear findings report, zero integration cost, and a pay-only-if-we-find-value guarantee.
Everything you need to uncover hidden losses in your operations — no engineering team required
Connect existing sensors or upload CSV / historian exports — no engineering team required
Automated baseline modelling for all monitored assets
Real-time anomaly detection across vibration, temperature, pressure, flow, and energy data
Machine downtime detection, logging, and root-cause tagging
Predictive maintenance alerts with configurable lead-time thresholds
Process optimisation recommendations backed by explainable AI
Maintenance scheduling engine with work-order generation
Multi-site dashboard with per-asset health scores and roll-up reporting
Weekly findings report highlighting top loss drivers and quick wins
Dedicated analyst support throughout the discovery period
Compatible with MQTT, OPC-UA, Modbus, and standard industrial protocols
Applicable to manufacturing, oil & gas, energy, and utility operations
Most industrial pilots deliver first insights within 2 weeks — often within days of data connection
Identify key assets, existing sensor coverage, and data sources — from live feeds or historical CSVs
Stream live sensor data via gateway or upload historian exports. Rifraux handles all ingestion and normalisation
Models learn equipment baselines and surface anomalies, downtime events, and process inefficiencies in real time
Detailed findings report quantifying losses found, recommended actions, and options for ongoing deployment
If your operations generate sensor data, operational logs, or maintenance records, you qualify
Examples: FMCG, food & beverage, cement, textiles, auto assembly
Cut unplanned line stoppages. Improve OEE and reduce energy waste.
Examples: Well operators, ESP owners, pipeline and midstream firms, oilfield service companies
Predict ESP and pump failures. Reduce costly emergency workovers.
Examples: Power generators, distribution companies, renewable energy operators
Prevent transformer faults. Predict generator maintenance. Reduce outages.
We define success through quantified loss prevention and measurable operational improvements.
Predictive alerts prevent failures before they stop production.
Models surface anomalies well before equipment failure occurs.
Every hidden inefficiency and yield loss is surfaced and costed.
No engineering resources required. Works with exported data or existing sensors.
Upload your data or connect your sensors. We find the losses. You decide if the value is real — then we talk.