- Agentic AI in BrahMos and Akashteer acts like a battlefield commander, making independent decisions under pressure.
- Machine learning (ML) algorithms process data from Hybrid Navigation Systems like INS, GPS, GLONASS, NavIc and active/passive radar homing to optimise flight paths.
- Deep learning models classify threats, distinguishing hostile drones from friendly assets, while predictive analytics forecasts trajectories for pre-emptive intercepts.
- By blending agentic AI for quick thinking and metadata-driven LLMs for data mastery, these systems give India a strategic edge.
Artificial Intelligence (AI) is redefining modern warfare, and India’s BrahMos supersonic cruise missile and Akashteer air defence system are at the forefront of this revolution. Developed by the Defence Research and Development Organisation (DRDO), Bharat Electronics Limited (BEL), and ISRO, these systems leverage advanced AI technologies to achieve unparalleled precision, autonomy, and defensive capabilities. Their standout performance during Operation Sindoor (May 7-10, 2025), a pivotal India-Pakistan conflict triggered by a terror attack in Pahalgam, showcased how AI can turn the tide when the stakes are high. From obliterating enemy targets to shielding Indian skies, BrahMos and Akashteer are rewriting the defence rules of the Indian Armed Forces
Machine Learning and Hybrid Navigation in BrahMos: Offensive Posturing
The BrahMos missile, a joint venture with Russia’s NPO Mashinostroyeniya, is a supersonic cruise missile reaching Mach 3 speeds and striking targets up to 290 kms with a jaw-dropping precision and an accuracy boasting of a circular error probability (CEP) of under 1 meter.
Its AI-driven autonomy enables ‘fire-and-forget’ functionality, navigating complex battlefields with precision. Machine learning (ML) algorithms process data from Hybrid Navigation Systems like INS, GPS, GLONASS, NavIc and active/passive radar homing to optimise flight paths, executing evasive manoeuvres like the ‘C’ and ‘S’ patterns to dodge the enemy’s defences. During Operation Sindoor, BrahMos struck 11 Pakistani airbases, including Bholari, where it destroyed a Saab 2000 Erieye AWACS with four missiles, thus ensuring Pakistani Pilots could not secure the aircraft. IACCS’s data feeds, processed by real-time ML trajectory adjustments, allowed BrahMos to bypass Pakistan’s HQ-9 and HQ-16 air defence systems, as noted by Warfare expert Colonel (Retd) John Spencer. This precision crippled 20% of Pakistan’s air force assets, highlighting ML’s role in offensive posturing.
DSMAC and TERCOM: The Eyes in Unknown Terrains
Apart from the Hybrid Hardware Navigation, BrahMos’s navigation relies on Digital Scene Matching Area Correlator (DSMAC) and Terrain Contour Matching (TERCOM), advanced AI-driven systems that enhance its low-altitude precision. DSMAC compares real-time imagery from onboard sensors, cameras to determine location, ensuring accuracy in cluttered or urban environments. TERCOM uses a contour map of terrain and matches terrain elevation data to guide missile flights as low as 10 meters, minimising the missile’s radar cross-section (RCS), which makes it easier to identify Targets. These systems were critical during Operation Sindoor, enabling BrahMos to strike high-value targets like the Noor Khan Airbase. DSMAC’s image-matching capability ensured the missile distinguished targets from decoys, while TERCOM’s terrain-hugging flight path evaded radar detection. Together, they allowed BrahMos to navigate contested airspace, contributing to the destruction of radar installations at Pasrur and Sialkot, as verified by satellite imagery. BrahMos II and BrahMos-NG versions are also slated to include Altitude matching based on Altimeter measurements from the Terrain, superimposed in prerecorded Terrain maps.
Agentic AI’s real-time decisions overwhelmed Pakistan’s HQ-9 and HQ-16 systems, bypassing and jamming them, allowing the missile to have an optimised RCS that makes the BrahMos nearly undetectable until impact.
Use of Agentic AI in BrahMos: Wolf Pack Strategy
BrahMos’s wolf pack configuration, where multiple missiles coordinate to overwhelm defences, is driven by agentic AI. Unlike conventional AI, which operates within rigid parameters, agentic systems analyse, learn, and evolve. The AI’s agency enables autonomous decisions, such as rerouting to avoid radar or prioritising targets, with missiles sharing data in real-time. The IACCS facilitates this by providing a unified command network, ensuring seamless coordination between BrahMos units and air assets like Sukhoi-30 MKI jets. During Operation Sindoor, wolf pack strikes on Rafiqui and Murid airbases used AI for synchronised low-altitude approaches. Agentic AI’s real-time decisions overwhelmed Pakistan’s HQ-9 and HQ-16 systems, bypassing and jamming them, allowing the missile to have an optimised RCS that makes the BrahMos nearly undetectable until impact.
Deep Learning and Predictive Analytics of IAACS: Akashteer Shield
The Integrated Air Command and Control System (IACCS), India’s automated air defence network, plays a pivotal role in coordinating both systems, enhancing their battlefield impact. Akashteer Shield is an AI-powered platform designed to counter drones, missiles, and aircraft, integrating deep learning and predictive analytics, processing data from 3D tactical radars, low-level lightweight radars, and using indigenous Navigation like NavIc into Akash missile systems. The IACCS acts as its backbone, fusing sensor data to create a comprehensive airspace picture, enabling rapid threat identification. Deep learning models classify threats, distinguishing hostile drones from friendly assets, while predictive analytics forecasts trajectories for pre-emptive intercepts. During Operation Sindoor, Akashteer neutralised 600 Pakistani (Turkish) drones, Fateh-1, Fateh-2 missiles and a barrage of rockets across 15 locations, including Srinagar and Amritsar. Air Marshal AK Bharti credited its 107 deployed units (of 455 planned) and IACCS integration for thwarting swarm attacks moving 18 km/minute.
AI’s Strategic Impact in Operation Sindoor: India’s Sudarshan Chakra
Operation Sindoor showcased AI’s transformative power in BrahMos and Akashteer, with IACCS as the unifying command layer. On May 7, BrahMos and Rafale jets with SCALP missiles struck nine terror hubs in Pakistan and PoK. Pakistan’s counterattacks on May 8-9, targeting 26 Indian locations with drones and missiles, were neutralised by Akashteer and S-400 Sudarshan Chakra systems, coordinated via IACCS. On May 10, 15 BrahMos missiles hit 12 Pakistani airbases, with AI-driven “dummy” UAVs like Lakshya-II and Banshee Jet-40-plus, exposing HQ-9 radars for wolf pack strikes. DSMAC and TERCOM ensured low-altitude accuracy, while agentic AI helped in synchronised attacks. Akashteer’s predictive AI, backed by IACCS, protected Chandigarh, intercepting PL-15 missiles stealthily. Satellite imagery confirmed damage to Pakistani runways, establishing the dominion of IAACS. Prime Minister Narendra Modi praised the “authenticity of Made-in-India weapons,” highlighting Atmanirbhar Bharat.
What makes these systems tick is how AI types work together. Agentic AI in BrahMos and Akashteer acts like a battlefield commander, making independent decisions under pressure. For BrahMos, this means choosing a new target if the primary one is neutralised; for Akashteer, it’s about redirecting missiles to counter a sudden drone swarm. Metadata-driven LLMs, meanwhile, are the brains behind data processing. In BrahMos, they fuse sensor inputs to maintain accuracy in contested environments, while in Akashteer, they analyse radar and satellite feeds to predict threat paths. These LLMs, trained on vast metadata, excel at pattern recognition, spotting anomalies like a rogue drone amid civilian air traffic. During Operation Sindoor, this combo was lethal: BrahMos’s AI-driven strikes crippled 20% of Pakistan’s air force, while Akashteer’s predictive AI ensured no major breaches of Indian airspace, as praised by Air Marshal AK Bharti for creating a “potent defense environment.”
Akashteer Shield is an AI-powered platform designed to counter drones, missiles, and aircraft, integrating deep learning and predictive analytics, processing data from 3D tactical radars, low-level lightweight radars, and using indigenous Navigation like NavIc into Akash missile systems.
Is Akashteer’s AI reliable? The Larger Question
AI’s power comes with hurdles. Ethical concerns loom large. BrahMos’s autonomy sparks debates about Lethal Autonomous Weapons Systems (LAWS), while Akashteer’s reliance on AI networks raises cybersecurity risks. The United Nations has maintained that LAWS are politically unacceptable and morally repugnant and has called for their prohibition under international law. Scaling Akashteer to cover all borders demands massive investment, and training troops to trust AI decisions is no cake walk. Still, the future looks bright.
Unlike Pakistan’s air defense systems, which use Chinese hardware and relies heavily on Chinese Software, Akashteer’s AI, has been designed and manufactured in India by the collaboration of India’s Tech Trident (BEL, ISRO and DRDO). The BrahMos-NG and Akash-NG are set to pack even smarter AI, with hypersonic speeds and longer-range interception. DRDO’s Project Kusha, eyeing a 2028 rollout, aims to rival the S-400 with AI at its core. These advancements shall ensure India keeps surging ahead in the global arms race.
BrahMos and Akashteer have achieved what has never been done on the World Stage, showing how India’s AI Shield can redefine Warfare. India decimated a nuclear power like Pakistan in 23 minutes and crippled its Defense and Offense capacities, calling out the Nuclear Bluff. BrahMos’s ability to strike with surgical accuracy and Akashteer’s knack for building an unbreakable shield proved their worth in Operation Sindoor. By blending agentic AI for quick thinking and metadata-driven LLMs for data mastery, these systems give India a strategic edge. As threats evolve, so will India’s AI arsenal, ensuring its skies and borders stay secure. This is more than just tech; it’s a testament to India’s entry in modern warfare, which shall ignite a chain reaction in India’s defence deterrence.
Abhinav is an accomplished Engineer, Technical Writer and consultant, who has worked for prestigious Navratna PSUs of India. He is an expert on matters related to Defense and Technology. Views are personal.
Parag Gilada 
Aayush Pal 
Piyush Anand