Safran Group
Safran, the Paris engine and equipment group, sells AI maintenance services alongside its hardware, including Landing Life, which predicts faults in A350 landing gear and brakes.
With more than 100,000 staff, it also offers engine health monitoring for CFM56 and LEAP through its CFM joint venture with GE Aerospace, Iotec cabin-equipment monitoring, Smart Lander for hard-landing checks, EngineLife for helicopters and Cassiopee flight data analysis. Its engines and equipment are not counted as AI here.
Air Caraibes confirmed Landing Life for its A350s in June 2025. Safran reports more than 120 aircraft under contract, without naming the operators, and a 90 per cent fault-confirmation rate.
No verified deployments yet
Safran Group is profiled in the companies register, but no deployment has been verified against published evidence. Records are added as evidence is reviewed and graded.
Products & Solutions
6 productsPredictive Maintenance for Landing Systems (Landing Life)
Safran Landing Systems offers Predictive Maintenance for Airbus A350 aircraft, monitoring the health of ATA32 (landing and braking) systems in real time using hundreds of onboard sensors measuring vibration, temperature, and pressure.
- Real-time health monitoring of ATA32 landing and braking systems
- Hundreds of onboard sensors, vibration, temperature, pressure
- Proprietary AI algorithms analyse sensor data
- Safran expert recommendations sent to airline maintenance teams
2 more features
- Prevents unscheduled maintenance events
- Currently deployed for Airbus A350
Technical specifications (1)
- IoT sensor network. Proprietary ML algorithms. Cloud-based analysis. Expert-in-the-loop recommendation system.
CFM Engine Health Monitoring (EHM) — LEAP and CFM56
A machine-learning-based engine health monitoring system developed by CFM International (50/50 joint venture between Safran Aircraft Engines and GE Aerospace) for LEAP-1A, LEAP-1B, and CFM56 engines.
Reduces unplanned engine removals and maintenance disruptions for commercial airline operators by detecting engine anomalies earlier and providing accurate maintenance recommendations, reducing operators' reliance on reactive inspection schedules.
- Multi-sensor data modeling at takeoff, climb, and cruise phases
- Probabilistic diagnostic and prognostic machine learning tools
- Targeted alerts based on known engine operating signatures
- 60 percent earlier lead time in identifying preventative maintenance recommendations (vs. a decade prior)
8 more features
- 45 percent increase in detection rates over ten-year period
- False alert rate cut by 50 percent over ten-year period
- Covers LEAP-1A (Airbus A320neo family), LEAP-1B (Boeing 737 MAX), and CFM56 fleets
- Ground-based Customer Notification Reports delivered to airline engineering teams
- Airborne component transmits flight reports via SATCOM, ACARS, 3G, or Wi-Fi
- Ground system processes and delivers engine data within five minutes of flight report reception
- Customer-facing web portal with 99 percent availability target
- OSA-CBM and ISO 13374 compliant architecture
Technical specifications (6)
- Probabilistic ML models trained on CFM56 and LEAP fleet data
- Sensor inputs cover engine performance (EGT, N1, N2), fuel system, control system, and module-level thermodynamic parameters
- Fleet approaches 50 million cumulative flight hours (as of April 2024)
- Five-minute ground processing target from flight report receipt
- Airborne data transmission via SATCOM, ACARS, 3G, Wi-Fi
- OSA-CBM architecture compliance
Cassiopee Alpha
An all-in-one flight data analysis platform developed by Safran Electronics & Defense. It decodes, cleans, and analyzes flight data from civil and military aircraft and helicopters.
Enables airlines to move from manual, fragmented flight data review to automated, integrated analysis covering flight safety regulation compliance, pilot self-debriefing, fuel efficiency monitoring, and predictive and reactive maintenance, all within a single platform.
- Automated, online analysis and visualization of flight data
- All-in-one platform serving flight safety, flight operations, maintenance, and data science departments
- Modular, open, and flexible design; fully customizable per airline
- Available as SaaS or on-premises (customer's data center or cloud)
8 more features
- 'Pilot in the Loop' module: crew self-debriefing via intuitive visualization
- 'Green' module: monitors fuel efficiency and environmental performance
- 'Tech Profile' module: advanced analysis of system integrity and airworthiness for predictive and reactive maintenance
- Machine learning for predictive safety integration
- Integration with big data factories and third-party systems
- Reference platform for SFCO2 fuel efficiency optimization service (Safran Aircraft Engines)
- Smart ACMS Recordings (SAR) for predictive maintenance programs
- Trusted by over 150 airlines worldwide
Technical specifications (5)
- SaaS or on-premises deployment
- Processes flight data from civil and military aircraft and helicopters
- Integrates with third-party data ecosystems
- Web application interface
- Machine learning for predictive safety analytics
Smart Lander
A landing gear diagnostics service jointly developed by Safran Landing Systems, Safran Engineering Services, and ATR that uses machine learning to assess maintenance requirements following hard landings.
Eliminates multi-week delays in post-hard-landing maintenance decision-making for ATR regional aircraft operators, enabling rapid return-to-service decisions and reducing aircraft-on-ground time, associated costs, and schedule disruptions.
- Machine learning trained on hundreds of thousands of hard landing simulations
- Uses 10 years of hard landing case data from global ATR fleet
- Ingests flight recorder data: vertical/horizontal touchdown speeds, pitch, roll, and acceleration
- Converts aircraft-level dynamics to landing gear-level load analysis
3 more features
- Determines whether aircraft is fit to return to service or requires maintenance
- Issues recommendations in under one hour (previous process: up to 20 working days)
- First service of its kind in the aviation industry (at time of launch, May 2022)
Technical specifications (4)
- Response time: under 1 hour from submission
- Prior process time: 10-20 working days
- Training data: 10 years of ATR fleet hard landing cases plus hundreds of thousands of simulations
- Input data: vertical speed, horizontal speed, pitch angle, roll angle, acceleration at touchdown from flight data recorders
Iotec (IoT Edge Controller)
An IoT-based cabin maintenance solution developed by Safran Cabin. A small hardware box is installed at multiple cabin locations and autonomously collects operational data from galley inserts, lavatory equipment, and business/first-class seats.
Addresses the 'black box' problem in aircraft cabins, currently cabin equipment faults are detected reactively after failure or scheduled on fixed cycles. Iotec enables condition-based preventive maintenance and reduces corrective maintenance investigation time from weeks to under a day.
- Small hardware box installed at multiple cabin locations
- Autonomous data collection from galley inserts, lavatory equipment, and premium-class seats
- Background mobile gateway app triggers data transfer when crew pass with tablet
- Data transmitted to Safran cloud via available internet connection (air or ground)
5 more features
- Preventive maintenance: detects equipment degradation via sensor trend analysis (e.g. power draw anomalies)
- Corrective maintenance: identifies error, root cause, and location from multi-sensor context
- Reduces fault investigation time from up to several weeks to under one day
- Sold as a service based on cost-of-ownership reduction for the carrier
- Sensors can be added to existing recent-technology cabin equipment
Technical specifications (5)
- Technology Readiness Level 6 as of April 2025
- Ground testing completed as of April 2025
- Planned flight trial arrangement: end of 2025
- Planned certification: 2026
- Cloud-based data storage and processing (Safran cloud)
Profile data from the Aerostack companies register; deployment records from the verified register. Evidence grades: T1 first-party confirmation, T2 credible reporting. See Our approach for how records are graded.