The Indian Army successfully deployed indigenous AI in Operation Sindoor. 23 AI applications helped detect enemy sensors, achieve precise targeting, and create a shared battlefield picture. This gave the Army an advantage over the enemy and strengthened national security.

During Operation Sindoor , the Indian Army used indigenous artificial intelligence applications, from detecting enemy sensors to obtaining full-scale battlefield imagery. These AI applications were developed by the Indian Army itself. Lieutenant General Rajeev Kumar Sahni, DG (EME), stated that 23 artificial intelligence applications were used during Operation Sindoor, giving the Indian Army an edge over the enemy. Lieutenant General Sahni was DG (Information Systems) during Operation Sindoor.

He stated that while there may be varying perceptions about China's AI capabilities, the Indian Army is fully prepared and, while remaining focused on national security, is continuously developing and developing robust, indigenous AI technologies. Lieutenant General Sahni stated that these AI applications helped during Operation Sindoor.

Indigenous Electronic Intelligence System

This is an indigenously developed application used by all intelligence agencies. During Operation Sindoor, the system was quickly modified to suit the needs of all agencies. It significantly assisted in detecting enemy sensors.

Precision targeting

Detailed weather reports were generated for long-range weapons. Artificial intelligence-based weather reporting systems enabled accurate targeting of enemy positions.

Establishing a common surveillance picture and targets

The Trinetra system helped create a common operational and intelligence picture at the tactical and operational levels, ensuring better coordination of resources across the three forces. This accelerated decision-making and provided a unified picture to military commanders at all levels.

This improves operational capabilities by predicting threats through artificial intelligence.

Artificial intelligence predicted threats based on complex interactions between time, space, and resources. This modeling enabled the deployment of resources at the right place at the right time. Techniques such as multi-sensor data fusion and multi-source data fusion combined information from disparate sources in near-real time, enabling commanders to better understand and manage the battlefield, thus providing an advantage over the enemy.

 PC:NBT