%%Standalone AI Agent%% for Secure Decision Making
Proposed by UPES Dehradun, this project develops an Integrated AI-Driven Decision Support Module to strengthen defense readiness by overcoming siloed intelligence and slow manual analysis.
The system combines predictive decision simulation with secure, indigenous GenAI-based interaction, automated reporting, and continuous learning—enabling faster, adaptive, and context-aware decisions in critical operational scenarios. It fuses multi-source data (EO, IR, SAR, LiDAR, RF) with AI analytics to deliver real-time situational awareness.
Key Highlights
Unified Multi-Sensor Intelligence
Fuses EO, IR, SAR, LiDAR, and RF data into a single, real-time operational picture.
AI-Driven Threat Assessment
Automatically detects, classifies, and prioritizes threats with dynamic severity scoring.
Predictive Strategic Simulations
Enables commanders to run multi-variable “what-if” scenarios with risk–benefit insights before action.
Secure Indigenous NLP Interface
Allows natural-language, context-aware queries using a military-trained, secure GenAI system.
Autonomous Operational Management
Automates maintenance logs, resource allocation, and strategic reporting to reduce manual overhead.
Secure Central Data Backbone
Provides encrypted, access-controlled integration of structured and unstructured intelligence data.
Continuous Learning Loop
Improves accuracy by feeding real-world operational outcomes back into threat models and simulations.
Impact
The project tackles delayed decision-making and fragmented data in modern defense, where siloed tools and manual analysis slow response to fast-evolving threats. By unifying data fusion, automated threat assessment, and predictive insights into a single AI-driven framework, it sharply reduces the time between threat detection and decisive action.
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