Deep-tech startup Quarkitech has raised Rs 2 crore in a pre-seed funding round from Artha Access, a programme of Artha Venture Fund II, and Finvolve. The Chennai-based company has also received a Rs 1.5 crore grant from IITM-CDOT Samgnya Technologies Foundation under the National Quantum Mission.
The National Quantum Mission is a government-backed initiative focused on developing quantum technologies in India. IITM-CDOT Samgnya Technologies Foundation describes itself as an initiative under the National Quantum Mission of the Department of Science and Technology.
Quarkitech said the newly raised capital and grant will support the development of its core compression algorithm library. The technology is designed to reduce sensor-generated data at the source before the information is stored, processed or transmitted.
Algorithms Designed to Cut Sensor Data at the Source
Founded in January 2025 by Rajesh Narayanan, Sanyam Parashar, Shashikant Singh Kunwar and Vishnu P.K., Quarkitech develops simulation and quantum-inspired algorithmic solvers for large-scale combinatorial optimisation.
The startup is working on applications across areas including finance, deep science and mission-critical systems. Its technology is also aimed at situations where large volumes of sensor data need to be handled within limited bandwidth, computing and power resources.
According to the company, its algorithms can compress sensor data by between 10 and 100 times, depending on the type of sensor, while retaining information considered relevant to the application. The approach is intended to allow platforms to transmit more usable information without adding new hardware or communication infrastructure.
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Hardware-Agnostic Technology Targets Multiple Sensor Systems
Quarkitech’s algorithm library is designed to be hardware-agnostic, meaning it can operate on existing computing infrastructure rather than requiring specialised hardware.
The company said the technology can run on CPUs and GPUs already available on platforms and can be integrated with onboard computers used in unmanned aerial vehicles, satellites and ground systems. It can also be configured for different types of sensor data, including radar, LiDAR, hyperspectral and electro-optical imagery.
This approach is aimed at reducing the amount of data that needs to move through communication systems while allowing existing computing and hardware infrastructure to remain in use.
Laboratory Tests Show 26x Data Reduction
In laboratory testing, Quarkitech said its technology reduced data volume by 26 times while retaining 98% of mission-critical information in images captured by drones.
The startup is now working to validate these results under real-world operating conditions. These tests are expected to examine the technology on moving platforms and in environments affected by factors such as heat, vibration, limited onboard power and intermittent connectivity.
The next stage of validation is important for determining how the algorithms perform outside controlled laboratory conditions, particularly in systems where communication and computing resources are constrained.
Focus on UAVs, Satellites and Sensor-Heavy Systems
Quarkitech is targeting applications where the amount of sensor-generated data can exceed available transmission capacity. These include UAV and surveillance platforms, satellite earth-observation payloads, radar and LiDAR mapping systems, and ground-based sensor processing.
The company said the same approach can also be applied to other bandwidth-constrained communication and infrastructure use cases.
With the latest funding and grant, Quarkitech plans to continue developing its compression algorithm library and move its technology towards validation in practical operating environments. The startup’s broader focus remains on developing quantum-inspired and simulation-based algorithmic solutions for large-scale optimisation problems.
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