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Aerospace & Defense 

Major Trends & Gaps  


  • Revolution in Military Affairs 2.0 : Dense C4ISR, Urgent threat detection, composite picture of the operational area of interest

  • Military lags behind the commercial sector to take advantage of massive sensor data, including shortfalls in data storage and AI computational power.

  • Transformation of Sustainment and Operations through CBM and Predictive Maintenance. 

  • Lack of theoretical development on large data, AI learning, and prediction models.

  • Data Fusion of space, airborne, terrestrial, weather, and auxiliary data sources.

  • Accelerate decision making and tempo of operations


  • Providing real-time satellite imagery 

  • Foliage Penetration

  • Damage Assessment

  • Trafficability and Mobility / Soil Stability (snow depth, soil moisture)

  • Unified Logistics  & Predictive Maintenance

  • Border Surveillance

  • Mine Detection

  • Communication & Control

  • HADR - Humanitarian & Disaster Relief

  • Forest fire management

  • Flood and storm 



  • Detection, Tracking, Identification of Vessels (including Dark Vessels)

  • Sustainable Fishing incl IUU

  • Offshore Infra mapping

  • Oil Spills / Pollution

  • Voyage optimization

  • Port Monitoring

  • Coastal Health

  • Bathymetry

  • EEZ monitoring

  • Inland Waters

  • Oceanographic Applications



  • Intelligence, Surveillance, and Reconnaissance

  • Predictive Maintenance

  • Airfield Maintenance

  • UAVs

  • Counter Drone

  • Weather and Climate

  • Command and Control

  • Communication/Navigation

VegaMX Core Capabilities 

Analytics & Computing Capabilities

  • Explainable and AI-enabled Analytics

  • Novel AI/ML algorithms, frameworks and applications

  • Federated/distributed AI/ML

  • Broad Area Search & Change Detection (airborne and satellite)

  • Big DATA -

  • Communication - SDR / Tactical Radio


System and System Integration Solutions

  • Custom sensing solutions airborne

    • Radar / EO/ IR

  • Custom drone solution

    • Fixed and rotary wing drone solutions for extreme environment

    • Predator class drones to commercial cost

  • Unmanned Airborne Systems (large drone)

    • Stealth technology

    • Conformal phased array antennas

    • Hybrid propulsion system

  • Model and Data integration

    • Sensor fusion, Data fusion, Analytics

Sensors (through 3rd party) : EO, RF, IR, SAR, multi-spectral imagery, SIGINT, HUMINT, text data, etc.

VegaMX Services

  • Operational Planning & Integration

  • Software development & Program Management

  • Systems Engineering & Development

  • Modeling and Simulation

  •  Electromagnetics / SIGINT / IMINT / HUMINT etc analysis

    VegaMX and its partners have extensive experience in designing, developing, and deploying complex physics-based and machine learning systems. Our hybrid edge/cloud platform can orchestrate deployment across thousands of edge locations and cloud machines. In this way, we can handle vast datasets with minimal data movement and processing latency. When combined with agile development, these capabilities enable rapid prototyping of new systems and easy maintenance and updating of already deployed systems.

    Tailorable products will enable strategic, operational, and tactical effects with a better understanding of the operational environment (systematically, spatially, and temporally); allowing decision-makers and to better orient themselves to the current and predicted situation and enable decisive action

Predictive Maintenance

HUMS (Health and Usage Monitoring System) is already widely used across operators of important western aircraft fleet in the civilian helicopter market. HUMS is a preventive maintenance tool requiring constant management by a team of experts. Our predictive maintenance solution goes one step further by implementing intelligence help for decision-making.


We also focus on outlier aircraft not covered by preventive maintenance programs such as non-western products or an aging fleet.


VegaMX passed the selective first step of the AFWERX bids process on USAF maintenance solutions competition. Our proposal combines several AI-based tools which can be incorporated into a next-generation maintenance approach


Vision-based detection of Corrosion patches


VegaMX is working on a Mi-17 predictive maintenance program by implementing an intelligent algorithm able to predict component failure and thus improving aircraft operation and readiness.

vegamx machine learning, predictive maintenance

Sample ISR and Data Processing Capabilities


Small satellite collection capability in low Earth orbit: Any type of rasterized Earth data can be managed and processed by including SAR and optical satellite imagery, image time series, 4D x/y/z/t atmospheric data, 2D DEM, as well as any sort of thematic data.


Advanced analytics software with cloud-based machine learning algorithms for object detection Analytics engine offers an analysis-ready view on data stored, thereby boosting ML and other AI applications through (i) massively simplified Spatio-temporal access (ML code can concentrate on its core task, disregarding all data wrangling) and (ii) scalable processing close to the data, thereby providing real-time input to ML tools. 


Edge compute capabilities supports edge computing in various directions such as federating data sources by having instances onboard the sensor carriers; users can flexibly retrieve, process, and combine data sitting on both the platforms and the data centers. federating client tools to make them members of the federation.


Demonstration of reduced latency direct downlink of data/imagery to tactical ground terminal  Through the Big Data principle of “ship code to data” processing can be propagated transparently to the sensors, in other words: queries are evaluated on board. 


In-theater data processing Theaters generate massive amounts of simultaneous requests which need concurrent, real-time responses. Through our horizontal and vertical scalability architecture, in combination with the federation capabilities, an unlimited number of requests can be supported with almost linear scalability. Simultaneous access to the same or similar areas can benefit from highly effective optimization, such as space/time aware caching.

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