Multi-INT Analysis & Archive System (MAAS)
The Scalable Solution for Multi-INT Capture, Exploitation, Dissemination and Archiving
General Dynamics’ Multi-INT Analysis and Archive System (MAAS) supports the Motion GEOINT mission and a solution for analysts providing a scalable, open, service-based platform to capture, exploit, disseminate and archive intelligence, surveillance and reconnaissance (ISR) data. MAAS enables real-time and forensic analysis of multiple intelligence (Multi-INT) sources supporting missions as they occur along with Structured Observation Management (SOM) and Activity-Based Intelligence (ABI).
- Generation of custom reports in real-time
- Completely configurable report templates
- Customizable tool set for rapid reporting to senior decision makers
- Hybrid/Cloud-ready solution for diverse deployment environments
- Observations captured for ease of data sharing and federation across missions
General Dynamics vision for Multi-INT Exploitation 2019 – 2024
The number of traditional and non-traditional data sources available to Analysts is growing at an unprecedented pace. Helping to manage this exponential increase in data is General Dynamics Multi-INT Exploitation strategy. It accelerates the creation of actionable intelligence with greater veracity and relevant context, while optimizing system performance.
The five keys to delivering actionable intelligence faster and more efficiently:
- Extract: Extracting and delivering the right information to users for their mission needs by identifying and integrating community algorithms and data sources.
- Correlate: Improve object discovery, recognition and extraction by automatically correlating data across multiple “INTs”.
- Derive: Derive meaning from data and anticipate future outcomes through probabilistic and mathematical inference to align data with key indicators and analytic models.
- Accelerate: Optimize and accelerate system performance through High Performance Computing *HPC techniques
- Employ: Generate higher-value intelligence by utilizing relevant data.