Quarkitech, a deep-tech company based out of IIT Madras Research Park, has raised ₹2 crore in pre-seed funding from Artha Access, a programme of Artha Venture Fund II, and Finvolve to develop its proprietary data compression technology for defence, aerospace, and other data-intensive applications.

The company has also been awarded a ₹1.5-crore grant by IITM-CDOT Samgnya Technologies Foundation, under the National Quantum Mission, the national programme approved by the Union Cabinet in 2023.

The funding will develop Quarkitech’s core compression algorithm library, designed to reduce sensor data at the source, before it is stored, processed, or transmitted. As India expands its drone, satellite, and defence capabilities, onboard sensors such as radar, LiDAR, and hyperspectral imagers are generating more data than platforms can continuously store or transmit, particularly in remote environments without a live connection to a ground station. This forces operators to trade off between data volume, quality, transmission speed, and cost.

Quarkitech addresses this at the point of capture. Its algorithms compress sensor data by 10 to 100 times, depending on sensor type, while retaining the information relevant to the mission, allowing platforms to move more usable data through the same bandwidth and power constraints without additional hardware or communication infrastructure.

The product is a software library that runs on a platform’s existing onboard compute, with separate tuning for radar, LiDAR, hyperspectral and electro-optical streams, so the same approach can sit on a UAV downlink, a satellite payload, or a ground-segment archive. The company uses tensor networks, mathematical frameworks originally developed to model complex quantum systems, to identify and remove redundancy in high-volume sensor data.

Sanyam Parashar, CEO and Founder of Quarkitech explained: These algorithms are inspired from the mathematical framework used in quantum many body physics. It enables high-dimensional data to be represented in extremely compressed form. “This results in much faster and cheaper computation, and 10-100X more efficient data transmission from high-value sensors,” he added.

“By applying the mathematical frameworks used to model complex quantum systems, we are untangling the massive data bottlenecks of modern defence and aerospace,” said Shashikant Singh Kunwar, Co-founder and CTO of Quarkitech. “We are translating the theoretical power of tensor networks into an immediate, real-world tactical advantage.”

Artha invested through Artha Access, a pre-seed programme under Artha Venture Fund II that co-invests alongside the academic incubators and accelerators that have already backed a company, on terms set by the partner institution.

“Sensor redundancy is a physics problem before it is a software problem, and Quarkitech is attacking it at the point of capture instead of after the data is already stuck onboard,” said Anirudh A. Damani, Director, Artha Group.

In laboratory testing, Quarkitech reports a 26X reduction in data volume while retaining 98% of mission-critical information, measured on drone captured images. The company is now working towards validating these results under real-world operating conditions, including moving platforms and in environments with heat, vibration, limited onboard power, and intermittent connectivity.

The technology is aimed at operators whose sensors generate more data than their links can carry: UAV and surveillance platforms, satellite earth-observation payloads, radar and LiDAR mapping fleets, and the ground segments that store and process what comes down. The same compression approach extends to other bandwidth-constrained environments across communications and infrastructure.

Ashish Bhatia, Co-founder of Finvolve, said, “Classical computing has scaled remarkably, but it is now hitting hard limits on cost, energy, and latency, and a lot of the problems India needs solved sit exactly at that wall. Quarkitech is building quantum-inspired algorithms that work on today’s hardware, starting with the data bottleneck in defence and space and extending to a much wider class of optimisation problems across communications and infrastructure.”

Published - August 13, 2026 11:41 am IST