As drones and unmanned systems move to the centre of modern defence, the hardest problem is no longer getting a platform into the air. It is keeping that platform useful when GPS is spoofed and the radio link to its operator is cut. Bengaluru-based defence and physical AI startup Paar Autonomy has raised over ₹10 crore in a seed round led by AdvantEdge Founders to build exactly that capability in India.

The “eyes and brain” of an unmanned system

Paar focuses on the perception and autonomy layer of unmanned aerial, ground and maritime platforms rather than the airframe or hull. Its gyro-stabilised, multi-sensor payloads give drones, rovers and boats day-and-night vision, while an on-board AI stack lets a platform keep navigating and complete its mission even when satellite navigation and operator communications are jammed. According to the company, most Indian drone makers currently import this capability from foreign vendors.

The product line spans three pieces:

• Sentinel – gimballed electro-optic and infrared payloads, from sub-55g cameras for FPV drones to 40x-zoom day/night systems for tactical drones and loitering munitions.
• NorthStar – a visual navigation module for GPS- and GNSS-independent trajectory and course holding.
• On-board AI stack – vision-language and small language models trained on a proprietary aerial dataset, which convert plain-language mission instructions into actions that run fully offline at the edge.

Why edge AI matters on the battlefield

Electronic warfare increasingly targets the two things unmanned systems depend on most: satellite positioning and the operator link. Advances in edge computing now make it possible to run real-time computer vision and compact language models locally, within the tight power and weight budgets of small platforms. Paar’s bet is that autonomy which works without the cloud, and without a human constantly in the loop for navigation, will become a baseline requirement.

“The real differentiator rests in an unmanned system’s perception and its capacity to execute missions autonomously amid heavy GPS interference and severed communications. Paar was founded to build and own this critical stack locally,” said Vignesh Sivaram Jayaraman, Founder and CEO, Paar Autonomy.

Sovereign IP and the investor view

The startup designs its gimbals, electronics and software source code in-house, an approach it says aligns with the Defence Acquisition Procedure 2026 requirement for Indian-designed and Indian-owned IP across source code, circuit layouts and design documentation. Paar works with platform manufacturers and systems integrators who integrate its payloads into their own defence offerings, and primarily serves uses such as border surveillance and tactical tracking, along with civilian work like industrial inspection, infrastructure monitoring and disaster response.

“Unmanned systems have shifted the value share from hardware to payloads, software, and autonomous execution, and succeeding requires owning the full stack,” said Kunal Khattar, Founder and Managing Partner, AdvantEdge Founders.

Where the money goes

The fresh capital will be used to move Paar’s aerial payloads into serial production, set up a dedicated manufacturing and testing facility in Bengaluru, and complete field validation of NorthStar. The company had earlier raised about ₹3.5 crore in a pre-seed round led by Venture Catalysts, which funded its first manufacturing line and pilot units.

Founded in June 2024 by Jayaraman, previously Head of Product at Asteria Aerospace and a robotics product manager at Bossa Nova Robotics, Paar’s team brings experience from DRDO, Cyient, Asteria Aerospace and Foxconn.

The bigger picture

Paar’s raise adds to a growing wave of Indian “physical AI” companies building intelligence for machines that operate in the real world, from robotics to autonomous defence systems. For India’s push towards self-reliance in defence technology, home-grown perception and autonomy stacks could prove as strategic as the platforms that carry them. The test now, as with any seed-stage deeptech company, will be moving from pilots to production and proving reliable performance in the field.

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