Quarkitech, a deep-tech startup based at the IIT Madras Research Park in Chennai, has raised ₹2 crore in a pre-seed funding round from Artha Access — a programme of Artha Venture Fund II — and Finvolve, alongside a separate ₹1.5 crore grant from the IITM-CDOT Samgnya Technologies Foundation under India's National Quantum Mission, a national programme approved by the Union Cabinet in 2023.
The company is building a core compression algorithm library designed to reduce sensor-generated data at the source — before it is stored, processed or transmitted — addressing a problem that is becoming increasingly acute as drones, satellites, radar systems and industrial sensors generate far more raw data than available bandwidth, storage or onboard power can practically handle.
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 problems, with applications spanning finance, deep science and mission-critical systems. The company's core claim is that its algorithms can compress sensor data by 10 to 100 times, depending on sensor type, while retaining the information most relevant to the specific downstream application — rather than applying a one-size-fits-all compression approach.
In laboratory testing, the company said its technology reduced data volume from drone-captured imagery by 26 times while retaining 98% of mission-critical information — a result Quarkitech is now working to validate under real-world operating conditions, including moving platforms and environments involving heat, vibration, limited onboard power and intermittent connectivity, all of which can degrade compression performance in ways that clean laboratory conditions do not reveal.
The technology is aimed squarely at applications where sensor-generated data volumes routinely exceed available transmission capacity: UAV and surveillance platforms, satellite earth-observation payloads, radar and LiDAR mapping systems, and ground-based sensor networks. Quarkitech says the same underlying approach can extend to other bandwidth-constrained communications and infrastructure use cases beyond its initial target markets, positioning the compression library as horizontal infrastructure rather than a single-application product.
The dual backing — commercial pre-seed capital alongside a National Quantum Mission grant — reflects how India's deep-tech funding landscape increasingly blends private venture capital with public research funding, particularly for startups working at the intersection of quantum-inspired computing and applied engineering problems. For Quarkitech, the combination provides both the credibility of government-backed research validation and the flexibility of private capital to move quickly on commercialisation.
With the fresh capital and grant funding in hand, Quarkitech's near-term priority is moving its compression technology from controlled laboratory validation to field-tested deployment readiness — the step that will determine whether its 26x compression claims hold up in the messy, resource-constrained environments its target customers actually operate in. If they do, the startup's data-compression approach could offer a meaningful edge to India's growing base of drone, satellite and industrial-sensor companies, all of which face the same underlying constraint: generating more data than they can practically move, store or process.
