Predict failures on-premise
without touching your PLC.
Predictive maintenance for regulated plants: on-site ML inference, read-only OPC-UA (zero PLC write), and IEC 62443 SL-1–aligned deployment. Explainable predictions — your data never leaves the site.
Three pillars of predictive intelligence
Anomaly Detection
Real-time vibration, temperature, and pressure monitoring. LSTM autoencoders catch deviations invisible to threshold-based rules.
RUL Prediction
Remaining Useful Life with P10/P50/P90 confidence intervals. Plan maintenance windows with statistical certainty.
Fault Diagnostics
Integrated Gradients attribution on every prediction. Your engineers see exactly which sensors drove the alert—not a black box.
See it in action
Three types of intelligence, one platform. Click through each scenario to see how Prevly detects, predicts, and diagnoses.
Everything looks good — the pump is running as expected. No action needed.
See Prevly in 5 minutes
Watch how a reliability engineer connects sensors, trains models, and gets the first alert — all without writing code.
Product walkthrough — coming soon
In the meantime, try the interactive demo above or request a demo
Want to see this on your machines?
Request a demo, connect your sensors, and watch Prevly detect anomalies on your real data — running on-premise and read-only, with no changes to your PLC.
From sensors to savings in four steps
Connect
Plug into existing sensors. OPC-UA, MQTT, Modbus, SCADA CSV—no hardware changes needed.
Learn
AI builds a baseline from your data in 48 hours. Isolation Forest starts immediately; LSTM trains in background.
Predict
Progressive ML: Isolation Forest → LSTM Autoencoder → Transformer. Models improve as data grows.
Prevent
Alerts route to PagerDuty, ServiceNow, or mobile push. Auto-generate work orders. Track ROI in real-time.
Up and running in 48 hours, not 6 months
Most PdM projects fail because deployment takes forever. Prevly works with your existing sensors — OPC-UA, MQTT, Modbus, CSV. No new hardware, no rewiring.
Built for industrial scale
Know WHY, not just WHAT.
Every prediction comes with per-feature attribution. Your engineers see exactly which sensors drove the alert—no black box, no guesswork.
Your engineers will trust it — because they can verify it
Every alert comes with per-feature attribution: exactly which sensors contributed and by how much. Not a black box — a tool your reliability team will actually use.
Real results from real plants
See how predictive maintenance transforms operations across industries.
Centrifugal Pump Monitoring
A municipal water plant experienced 12 unplanned pump failures per year, each costing €8K in emergency repairs and €15K in lost capacity.
Prevly’s LSTM autoencoders detected bearing degradation patterns 14 days before failure, invisible to threshold-based SCADA alarms.
Electric Motor Diagnostics
A Tier-1 supplier’s CNC spindle motors caused 3-hour production stops when faults went undetected until quality defects appeared.
CNN-1D fault classification with Integrated Gradients attribution identified stator winding issues from vibration spectra, giving engineers actionable diagnostics.
Compressor RUL Prediction
Reciprocating compressors in an ethylene plant required conservative 3-month overhaul cycles, wasting 40% of component useful life.
Weibull-RNN with P10/P50/P90 confidence intervals enabled condition-based maintenance scheduling with statistical certainty.
Enterprise-grade security
Your production data is critical. We built Prevly to meet the security standards your IT team requires — and explain them in terms everyone understands.
GDPR Compliant
Your data stays in your region. Full data processing agreements available.
We treat your production data like you would — it never leaves your control.
Encrypted End-to-End
TLS 1.3 in transit, AES-256 at rest. Zero-trust architecture.
Bank-level encryption from your sensor to your dashboard. Nobody can intercept.
99.9% Uptime SLA
Multi-region deployment with automatic failover.
When your machines run 24/7, so do we.
Multi-Tenant Isolated
Row-level security. Each tenant's data is fully isolated with RLS.
Your data never mixes with anyone else's. Complete tenant separation enforced at the database level.
Works with your existing systems
No rip-and-replace. Prevly plugs into the tools and protocols your plant already uses.
Custom integrations available for Enterprise customers. Don't see your system? We'll build the connector.
Built on proven technology
Enterprise-grade open-source stack — no vendor lock-in, full transparency.
Designed for heavy industry
Prevly works with rotating equipment, process systems, and utility infrastructure across sectors.
Transparent pricing. Sensor-agnostic. Mid-market mid-tier.
8-week pilot SLA — no other PdM vendor commits contractually.
Essential
Per-asset anomaly + RUL prediction. Customer-provided sensors or existing OPC-UA tags.
- OPC-UA ingestion
- LSTM autoencoder anomaly detection
- Remaining Useful Life prediction
- Dashboard + email alerts
- Discord community support
- Sensor-agnostic (IFM, SKF, PCB, Treon)
- Up to 50 assets
Professional
Adds ML depth for mid-cap manufacturers — drift detection, explainability, automated work orders.
- Everything in Essential
- Integrated Gradients explainability (“why this alert?”)
- Drift detection (PSI baselines)
- Composite trigger DSL
- Automated work order generation
- Multi-user RBAC (operator/engineer/manager)
- 24h response email + business-hours phone
- Up to 200 assets
Validated
GAMP 5 / CSV-ready validation pack for pharma + medical device manufacturers.
- Everything in Professional
- GAMP 5 / CSV validation documentation pack
- EU GMP Annex 1-aligned controls
- 21 CFR Part 11-capable e-signatures
- ALCOA+ data integrity audit trail
- 4-hour priority SLA + 24/7 support
- Dedicated Customer Success Manager
- Source code escrow (optional)
- Federated Learning (cross-site insights)
Implementation 18-22% of Year-1 ACV. Multi-site discounts up to 44% off (10+ sites). Annual prepay 8% off; 3-year prepay 18% off. CMMS integrations (Maximo / SAP PM / IFS) available as add-ons. The Validated tier provides validation-enabling tooling (GAMP 5 / CSV documentation pack, Part 11-capable e-signatures, ALCOA+ audit trail); validation of your specific installation is performed by you under your own quality system — Prevly is not itself a regulatory certification.
Frequently asked questions
How long does it take to deploy Prevly?
Prevly connects to your existing sensors (OPC-UA, MQTT, Modbus, SCADA CSV) with no hardware changes. AI builds a baseline from your data in 48 hours. Isolation Forest anomaly detection starts immediately while LSTM models train in the background.
What types of equipment does Prevly monitor?
Prevly monitors any rotating or process equipment with sensor data: pumps, motors, compressors, turbines, fans, gearboxes, and more. It supports vibration, temperature, pressure, current, voltage, flow rate, RPM, and acoustic sensors.
How does Prevly explain its predictions?
Every prediction comes with per-feature attribution — Integrated Gradients for the deep models (anomaly, fault) and SHAP-style contributions for the gradient-boosted RUL model. Your engineers see exactly which sensors drove each alert and by how much — no black box. This builds trust and enables faster root cause analysis.
Is my data safe with Prevly?
Yes. Prevly runs on-premise with no required outbound egress, and uses TLS 1.3 in transit, AES-256 at rest, and PostgreSQL row-level security (RLS) for complete tenant isolation. Your data never mixes with other customers and never has to leave your site. GDPR compliant with data-residency options.
What ML models does Prevly use?
Prevly uses a progressive ML approach: Isolation Forest for immediate anomaly detection (cold start), LSTM autoencoders for learned patterns, and TranAD transformers for advanced detection. RUL prediction uses LightGBM, Weibull-RNN, and PINN models. Fault classification uses CNN-1D with CBAM attention.
Request a Prevly demo
See predictive maintenance running on your machines — on-premise, read-only, no PLC changes. Tell us about your setup and we'll be in touch.