European Predictive Intelligence

We monitor
the hidden evolution
of machines.

A European sensor-based intelligence layer for fleets, industrial assets and critical systems — detecting degradation patterns before they become failures.

0.986
Mean AUC across domains
1.000
Fleet F1-score (11 adversarial)
<24h
Deployment — no training data
8+
Industrial domains validated
48h
Failure anticipation window

Beyond individual alerts.
Fleet-level intelligence.

Most maintenance systems focus on isolated asset alerts. Synthaxis goes further — evaluating how an asset behaves inside its family, detecting whether a deviation is isolated, emerging, or systemic across an entire fleet.

01
Raw Signal Analysis Works directly from sensor streams — vibration, temperature, pressure, current, rotation. No labelled data required.
02
Systemic Pattern Detection Identifies whether a problem is isolated to one asset, or shared across a family — enabling batch, design or supplier-level review.
03
Domain-Agnostic Architecture Validated across wind, aerospace, vehicles, drones, batteries, industrial machinery and urban transit — same analytical core.
04
European Data Sovereignty Infrastructure hosted in Europe. No unnecessary data exposure. Compatible with NDA-based protected deployment models.

Industrial domains covered

From offshore wind to urban transit, from commercial vehicles to autonomous drones — the same analytical layer, adapted to the physics of each asset class.

🌬️
Offshore Wind
Turbine degradation detection, blade anomalies, systemic fleet patterns across wind farms.
AUC 0.983 Validated
✈️
Aerospace
Engine component health monitoring and remaining useful life estimation for critical propulsion systems.
AUC 0.989 Validated
⚙️
Rotating Machinery
Bearing degradation, gearbox anomalies, mechanical fatigue detection without labelled failure data.
AUC 0.991 Validated
🔋
Battery Systems
Electrochemical degradation regimes, capacity fade classification, early identification of premature failure groups.
AUC 0.988 Validated
🏭
Industrial CNC
Tool wear detection, milling anomalies and production-line machinery health in manufacturing environments.
AUC 0.978 Validated
🚌
Urban Transit
Pneumatic and electromechanical system monitoring for metro and rail assets. Tested on real operational data from Porto Metro.
AUC 0.856 In validation
🚁
Autonomous Drones
Mission-level risk triage for UAV fleets. Propulsion, battery, vibration and flight dynamics monitoring for critical operations.
AP 0.952 In validation
🚛
Commercial Vehicles
Fleet health monitoring from OBD-II and CAN bus signals. Supports maintenance, warranty and post-sale decisions at scale.
AUC 0.985 In validation
☀️
Solar & Energy Storage
Inverter and PCS health monitoring. Battery degradation analysis for solar assets and grid-connected energy storage systems.
In study Potential
🛳️
Marine & Subsea
Structural health monitoring for maritime assets, underwater vehicles and subsea inspection systems.
In study Potential
🏗️
Industrial Infrastructure
Compressors, pumps, elevators and building systems. IoT sensor networks for facility-wide predictive maintenance.
In study Potential
🛡️
Defence & Critical Assets
Production line integrity, fleet readiness monitoring and component lifecycle management for defence manufacturers.
In study Potential
Scientific Validation

Benchmarks against State-of-the-Art

Results obtained on public industrial datasets. No supervised training. No labelled data. Raw sensor signals only.
Scientific record: DOI 10.5281/zenodo.19695606

IMS Bearings · Mechanical
0.991
vs SoA 0.974 · +1.7pp
NASA C-MAPSS · Aerospace
0.989
vs SoA 0.981 · +0.8pp
CARE Wind · Eolic Fleet
0.983
vs SoA 0.971 · +1.2pp
Milling · CNC Industrial
0.978
vs SoA 0.962 · +1.6pp
NASA Battery · Electrochemical
0.988
vs SoA 0.760 · +22.8pp
Fleet Intelligence · Adversarial
1.000
F1-Score · 11 scenarios · zero variance
Pilot Programme

Controlled technical evaluation

Synthaxis can be evaluated through a short paid pilot using selected historical or live sensor data. The objective is to determine whether the system can identify early degradation and systemic fleet patterns in your operational context.

P1
Data Scope Definition

Selection of asset type, sensor channels, operational history and target events. Minimal sensitive data exposure.

P2
Blind Evaluation

Synthaxis analyses available signals without requiring access to full internal systems or proprietary data structures.

P3
Risk Mapping

Asset-level and fleet-level health indicators are generated. Early warning timeline, risk ranking and systemic patterns.

P4
Technical Review

Results compared with known maintenance history, failures or inspection records. Savings estimate produced.

P5
Deployment Roadmap

If validated, pilot evolves into a protected industrial deployment with defined performance criteria and pricing model.

Pilot Parameters

Duration 30 – 90 days
Investment €9,000 – €20,000
Data Required Raw sensor signals only
Sensitive Data Not required
Deployment European infrastructure
Success Fee 20% on verified savings
Confidentiality NDA available
Request Technical Evaluation →
Data Protection

Designed for sensitive industrial environments

🇪🇺
European Infrastructure
Hosted exclusively on European providers. No data routed outside EU jurisdiction.
🔒
Data Minimisation
Only required sensor streams are processed. No access to business intelligence, financial or operational databases.
📋
NDA-Based Evaluation
All pilot engagements can be structured under mutual non-disclosure agreements before any data exchange.
🏗️
Private Deployment
On-premise or private-cloud execution models available for clients requiring full data sovereignty.

Start a technical conversation

For industrial pilots, fleet evaluation or technical discussions, contact Synthaxis directly.

✉️
Email alberto@synthaxis.eu
🌍
Location Portugal · European Union
Scientific Validation Record
DOI: 10.5281/zenodo.19695606