Quarkitech Raises Rs 2 Crore in Pre-Seed Funding

Quarkitech, a pioneering deep-tech startup, has successfully secured Rs 2 crore during a pre-seed funding round with investment from Artha Access, part of the Artha Venture Fund II, along with Finvolve. Located in Chennai, the startup has also benefitted from a Rs 1.5 crore grant awarded by the IITM-CDOT Samgnya Technologies Foundation, which is aligned with the National Quantum Mission, a government initiative approved by the Union Cabinet in 2023.

Allocation of Funds

The financial backing will be allocated towards the development of a core compression algorithm library aimed at efficiently reducing sensor data directly at the source before it undergoes storage, processing, or transmission, as stated in a press release by Quarkitech.

Company Overview

Founded in January 2025 by Rajesh Narayanan, Sanyam Parashar, Shashikant Singh Kunwar, and Vishnu P.K., Quarkitech focuses on crafting simulation and quantum-inspired algorithmic solvers tailored for large-scale combinatorial optimisation across various sectors such as finance, deep science, and mission-critical applications.

Innovative Data Compression Techniques

The startup’s algorithms are capable of compressing sensor data between 10 to 100 times, contingent on the type of sensor being used, while ensuring that application-relevant information is preserved. This capability can enable platforms to transmit a greater amount of usable data within the current bandwidth and power limits without the need for additional hardware or enhanced communication infrastructure.

Software Library Functionality

Quarkitech’s software library operates on the existing onboard computer of a platform and can be customized for various data streams, including radar, LiDAR, hyperspectral, and electro-optical data. This technology has the potential to be implemented on unmanned aerial vehicles (UAVs), satellite payloads, and ground-segment systems.

Results from Laboratory Testing

In its laboratory evaluations, Quarkitech reported that its technology achieved a data volume reduction of 26 times while retaining 98% of mission-critical information in images captured by drones. The company is currently focused on verifying these outcomes under realistic operating conditions, which include dynamic platforms and environments characterised by heat, vibration, limited onboard power, and intermittent connectivity.

Target Applications

This technology is designed for scenarios where sensor-generated data surpasses the capacity for transmission. Potential applications include UAV and surveillance platforms, satellite earth-observation payloads, radar and LiDAR mapping systems, and ground-segment data processing. The company noted that this approach could also be beneficial for various bandwidth-constrained communication and infrastructure scenarios.