Stuttgart-based Q.ANT, a pioneer in photonic processing for artificial intelligence (AI) and high-performance computing (HPC), announced the second closing of its Series A, bringing total funding to $80 million. The additional investment came from Duquesne Family Office, LLC, the investment firm of Stanley F. Druckenmiller, which joins existing lead investors Cherry Ventures, UVC Partners, and imec.xpand, along with L-Bank, Verve Ventures, Grazia Equity, EXF Alpha (Venionaire Capital), LEA Partners, Onsight Ventures, and TRUMPF.
As AI infrastructure expands, semiconductor chips have become strategic assets and geopolitical tools. McKinsey projects AI-related data-centre spending to exceed $5.2 trillion over the next five years. With data centres consuming growing shares of national power grids, energy efficiency is a primary constraint.
Q.ANT addresses this at the hardware level. Its photonic processors compute with light, delivering AI and HPC performance at a fraction of the energy of electronic chips, enabling more scalable, efficient computing.
Dr. Michael Förtsch, founder and CEO of Q.ANT, noted that AI is rapidly straining global resources, including energy, hardware, and financial capacity.
At Q.ANT, we achieve performance through efficiency, not brute power alone, redefining how AI can scale. The Duquesne Family Office shares our conviction that sustainable computing will define the next era of progress.
In the past five years, Q.ANT has introduced a commercial photonic processor for real-world AI and HPC workloads. Built on thin-film lithium niobate (TFLN), the Q.ANT Native Processing Server (NPS) integrates as a plug-in co-processor for existing data centres. Early internal benchmarks indicate up to 30× higher energy efficiency, 50× performance gains, and the potential for 100× capacity increases, without active cooling.
The system delivers 16-bit floating-point accuracy comparable to modern digital processors while retaining the advantages of analogue computation. Q.ANT aims to make photonic processing a core element of AI systems by 2030.
The new funding will accelerate commercialisation, advance next-phase technology development, and support expansion into the US market.
Would you like to write the first comment?
Login to post comments