Tech Explained: Here’s a simplified explanation of the latest technology update around Tech Explained: Indrajaal’s SkyOS: The Next Frontier In AI-Driven Air Defence Technology – Indian Aerospace and Defence Bulletin in Simple Termsand what it means for users..
Kamal Shah
Indrajaal’s mission is translated into concrete, operational reality through a unified, multi-layered C5ISRT architecture built around SkyOS, its autonomous defence operating system. At the technical level, this architecture integrates sensors, effectors, command logic, and AI-driven autonomy into a single grid that detects, tracks, identifies, classifies, and mitigates threats without human intervention.
Indrajaal is redefining aerial defence by turning the vision of “the world’s most advanced autonomous aerial defence systems” into a concrete, deployable reality. At the core is a unified C5ISRT architecture powered by SkyOS, an autonomy-first operating system that fuses radars, RF sensors, EO/IR, cyber-capture modules, and both soft- and hard-kill effectors into a single decision-making grid. Rather than patching together discrete countermeasures, SkyOS builds a continuously updated, wide-area threat picture and uses AI models trained on millions of signatures to detect, classify, and mitigate threats in real time—often in milliseconds—without routine human intervention. In an exclusive interview with Indian Aerospace & Defence, Kiran Raju, Founder & CEO of Indrajaal Drone Defence India, discusses the profound transformation from conventional, human-operated air defences to autonomous systems. Where legacy systems are linear, operator-heavy, and slow against fast, low-altitude, high-volume drone threats, Indrajaal’s AI-first model treats the machine as the operator and humans as supervisors who intervene only when necessary. Key drivers are technological mastery of sensor fusion and real-time autonomy, the strategic ability to scale protection across environments that are inaccessible to manual monitoring, and ethical guardrails that preserve human authority over lethal actions and ensure transparent engagement rules.
1. How does Indrajaal’s mission to create “the world’s most advanced autonomous aerial defence systems” translate into practical, technical, and strategic realities—specifically in terms of system architecture, AI-driven threat response, scalability across defence networks, and implications for modern security operations?
SkyOS serves as the autonomy engine that integrates radars, RF sensors, EO/IR systems, cyber-capture modules, and soft-kill and hard-kill effectors into a single decision-making ecosystem. Rather than treating each component as a standalone asset, the system creates a coherent, continuously updating threat picture. It uses AI models trained on millions of signatures to determine the most appropriate response in real time.
Strategically, Indrajaal’s systems scale horizontally across entire defence networks—from a single facility or border post to thousands of kilometres of national infrastructure—through a “networked dome” model. Each node operates autonomously yet cooperates with others to form a unified wide-area protective grid. The implications for security operations are profound: threats can be detected and neutralized before they mature, response times can shrink to milliseconds, and defence forces shift their focus from manned monitoring to exception handling and strategic oversight.
2. How would you characterize the transformation from conventional, human-operated air defence systems to modern autonomous aerial defence frameworks, and what key technological, strategic, and ethical considerations define this shift?
For autonomous systems, we start the design from the premise that there is no operator; only a supervisor. AI is the operator; however, a human supervisor can intervene if any unethical behaviour occurs.
The shift represents a move from human-centric control to AI-orchestrated operations. Traditional air defence systems are linear, operator-intensive, and slow to respond in environments where drones operate at high speeds, low altitudes, and high volumes. Modern autonomous systems invert this model: AI becomes the operator, humans become supervisors.
Indrajaal designs every system assuming the operator is absent. AI handles detection, identification, correlation, decision-making, and engagement. Human oversight exists only as a safety layer or intervention mechanism, invoked only when required to halt or override decisions.
Three considerations shape this transformation:
- Technological – mastery of sensor fusion, real-time data correlation, autonomy engines, and adaptive threat models.
- Strategic – enabling defence agencies to scale protection across vast areas that humans cannot monitor manually.
- Ethical – preserving human authority over lethal actions, enforcing rules of engagement, and ensuring transparency in autonomous decision pathways.
3. In what specific ways do Indrajaal’s autonomous defence systems distinguish themselves from traditional counter-UAS solutions—such as jamming devices, kinetic interceptors, and radar-based approaches—in terms of technology integration, operational adaptability, and overall threat-neutralization effectiveness?
Jammers and interceptors are components of a system. To bring in autonomy, there are two main aspects: control unification and sensor fusion. Autonomy requires real-time, accurate data for it to act or make decisions.
Indrajaal’s systems differ because they aren’t built around a single countermeasure or sensor. Instead, they integrate all sensors and effectors under a single AI-driven command fabric. Jammers, spoofers, cyber-takeover modules, directed-energy systems, and kinetic interceptors are all interchangeable tools within the autonomy engine.
The two pillars that differentiate Indrajaal are:
- Control Unification: A single AI layer governing all actions, rather than fragmented subsystems operated independently.
- Sensor Fusion: High-resolution, real-time correlation of RF, radar, EO/IR, acoustic, and protocol intelligence to create an accurate threat picture.
This integration enables rapid AI decision-making based on threat type, behaviour, payload risk, and historical engagement success. The result is significantly higher neutralization effectiveness and adaptability across diverse environments.
4. Could you elaborate on how Indrajaal leverages artificial intelligence and machine learning to enable real-time threat detection, classification, and autonomous decision-making? Additionally, how does the system adapt to counter challenges such as coordinated drone swarms and the emergence of low-cost, rapidly evolving adversarial technologies?
AI is synonymous with the internet; it’s a technology capable of making decisions and learning. So to decide what weapon to launch based on the threat incoming is one of the key areas where it makes a difference… the clearer the sensor picture is on the threat, the better the decision based on machine learning of success in the past… doing this across 15000 km of the border is where AI scale comes in …
SkyOS uses machine learning models trained on vast datasets of drone behaviour, RF signatures, flight dynamics, and adversarial tactics. Once a threat is detected, AI simultaneously analyses the sensor image, extracts features, classifies the threat type, predicts intent, and selects the most effective mitigation method.
The clearer and richer the sensor fusion, the more precise the AI’s decision-making becomes.
For swarms, the system uses distributed processing across nodes, enabling simultaneous tracking of dozens or hundreds of drones. Rather than reacting sequentially, the AI predicts group behaviour and optimally allocates effectors.
Indrajaal’s architecture is built to scale across 15,000 km or more of border or coastline, where AI becomes the only viable mechanism to detect and respond to threats faster than humans can process.
5. How have insights and lessons learned from battlefield trials directly informed and shaped the key design principles and functional improvements implemented in the current system architecture?
Not every drone is on the battlefield; we are going to have more drones, legal and illegal, in border and urban areas. This fundamental principle led us to design the Indrajaal Ranger as a solution specific to drug and weapons trafficking.
Key lessons have come from observing real-world drone intrusions along borders and from operational trials with forces. The insight that threats are no longer limited to war zones but will increasingly occur in grey zones—urban areas, civilian airspace, and smuggling corridors—shaped the development of the Indrajaal Ranger.
Ranger was explicitly built for the emerging operational reality where counter-UAS systems must:
– operate on highways, farmlands, and dense villages
– chase fast-moving drones carrying contraband
– run continuous patrols without fixed infrastructure
– neutralize threats without collateral impact
Battlefield and border lessons helped refine autonomous zoning, cyber takeover tools, rapid-deployment workflows, and mobility-oriented sensor layouts.
6. To what extent does the platform’s modular design allow defence forces to tailor its configuration—adding, upgrading, or removing specific capabilities—to adapt efficiently to varying mission profiles and operational requirements?
Modularity is in the sensors, weapons, and SOPs for that particular use case. The autonomy engine remains the same.
Modularity is central to Indrajaal’s design. Forces can add, remove, or upgrade sensors (RF, radar, EO/IR), swap effectors (cyber takeover, soft kill, hard kill), and configure rules of engagement as required by the mission.
However, the autonomy engine—SkyOS—remains constant. This ensures that, regardless of the configuration, the system maintains:
– unified control
– consistent decision logic
– interoperability across nodes
– ease of upgrades and maintenance
This modularity allows the same platform to secure a refinery one day, a border village the next, and an airport the third—simply by changing modules, not architecture.
7. Given the critical importance of rapid response and wide-area defence in modern security systems, how swiftly can Indrajaal deploy its countermeasures upon detecting a threat, and what is the maximum geographical coverage or area of protection that a single Indrajaal network is capable of providing under optimal operational conditions?
Indrajaal is engineered to react within milliseconds. Once a threat is detected, sensor fusion and classification occur in near-real time, and countermeasures are deployed almost instantaneously via pre-approved autonomous engagement logic.
Coverage depends on the configuration:
– A single fixed node provides approximately a 5–10 km radius of protection.
– A mobile Ranger unit covers a 10 km detection bubble while patrolling.
– A network of nodes scales linearly into hundreds or thousands of square kilometres.
Under ideal conditions, an Indrajaal grid can protect entire borders, coastlines, or metropolitan regions through continuous overlapping domes.
8. As the level of autonomy in Indrajaal’s defence systems continues to advance, what specific measures and cybersecurity protocols are implemented to effectively mitigate the risks of adversarial hacking, spoofing, or other forms of cyber warfare that could compromise operational integrity and national security?
These systems are offline, and when online, they transmit only limited, highly encrypted data. There is no remote command-and-control, thereby making it relatively cyber-secure.
Indrajaal’s systems are architected with a “cyber-first” security posture. Core operations are conducted offline, thereby eliminating most attack vectors. When connectivity is required, only metadata and encrypted telemetry are transmitted using nationally compliant encryption protocols.
There is no remote command-and-control channel, thereby eliminating the most significant single vulnerability in most EW and C-UAS systems.
Additionally, hardened firmware, authenticated sensor-to-node communication, and multi-layer spoofing detection fortify the ecosystem against GPS manipulation, RF deception, and protocol injection attempts.
9. What specific electronic warfare (EW) capabilities have been integrated into the system’s design to enhance its operational survivability and resilience when confronted with modern anti-defence tactics and countermeasures?
Indrajaal integrates a full spectrum of EW capabilities, including wideband RF detection, protocol decoding, GNSS spoofing detection, smart jamming, directional jamming, cyber takeover, and adaptive soft-kill profiles.
These EW tools allow the system not only to defend itself but also to degrade and disrupt hostile drones actively. The resilience comes from the AI’s ability to adapt EW patterns in real time based on the adversary’s behaviour, power levels, frequency hopping, or evasive tactics.
10. How do you envision Indrajaal shaping the future of AI-powered autonomy over the next decade—will it lean toward greater human oversight, or evolve into a seamlessly self-regulating system that redefines how we collaborate with intelligent technologies?
It will shift toward reduced human oversight as we begin to trust AI systems.
Over the next decade, Indrajaal will evolve toward systems that require progressively less human oversight. As trust builds through operational success, AI-driven defence will shift from supervised autonomy to conditional autonomy, and eventually toward near-independent regulation within tightly defined rules of engagement.
Human involvement will remain as a safety valve. Still, the bulk of sensing, correlation, decision-making, and engagement will be managed by AI engines that can learn autonomously, update tactics, and coordinate with neighbouring nodes.
This shift will redefine how nations manage airspace, making autonomous defence grids as foundational as radars and airbases were in earlier eras.