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Defense & Aerospace

We improve costumer

experience with AI

Use Case 1

Intelligent document management
Design, development and implementation of an advanced intelligent document management solution, based on Artificial Intelligence (AI), natural language processing (NLP) and deep learning technologies, capable of comprehensively transforming document creation, search, classification and validation processes within enterprise environments. The solution addresses both structured and unstructured data from multiple sources.

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Reduction of document management time

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Increased productivity of technical personnel

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Automatic indexing of processed documents

Positive impacts:

  • Operational time savings: Reduction of time spent on document generation, review and indexing through automation using AI models.
  • Improved document quality: Automatic identification of frequent errors in the dossiers.
  • More efficient access to information: Cognitive search on structured and unstructured documents.
  • Security and control in document management: Access control based on roles and security levels.
  • Technological scalability: Technological base prepared to integrate multimodal processing.

Use Case 2

Intelligent Systems for the Prediction of Natural Disasters with Impact on Resilient Agriculture in the Olive Sector in the Mediterranean Basin.

Development and implementation of an intelligent platform based on Artificial Intelligence technologies, deep learning and IoT sensors, integrating satellite, climate and historical data in order to predict natural disasters such as droughts, heat waves, floods and pest outbreaks that severely affect olive cultivation in the Mediterranean Basin.

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Reduction in water and fertilizer use

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Reduction of losses due to pests and inclement weather

Positive impacts:

 

  • Reduction of economic losses
  • Optimization of the use of resources
  • Improving agricultural sustainability
  • Strengthening climate resilience
  • Access to new markets

Use Case 3

EcoVision AI

Design and development of an intelligent computer vision platform, based on convolutional neural networks (CNN), for automated environmental monitoring using satellite and drone imagery. EcoVision AI is a scalable, accurate and real-time tool for identifying green areas, measuring forest cover, monitoring vegetation health and validating carbon offset activities.

Positive impacts:

 

  •  Automation and reduction of operating costs
  • Increased accuracy of environmental monitoring 
  • Regulatory compliance support
  • Contribution to sustainability and decarbonization
  • Reduction of operational carbon footprint
  • Geographic and sectoral scalability

Positive results

Months of deployment of a working prototype

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Reduction in costs related to field monitoring

Automated monitoring of forest cover and green areas in large geographic extensions.

With precise segmentation and classification by vegetation type.

Access to smart environmental monitoring market and validation of carbon credits

Stimulated by more demanding regulations and pressure for ESG (environmental, social and governance) transparency.