Bengaluru-based quantum startup Quanfluence has reportedly raised $10 million. Chiratae Ventures led the round. Rainmatter by Zerodha joined in, along with existing investor Pi Ventures.
The company will use the money to build photonic quantum computing hardware, expand manufacturing and work towards scalable quantum processors. Quanfluence was incubated at IIT Madras. It aims to deliver its first quantum processors by 2027 and larger, scalable quantum computers by 2029. These are company targets, not confirmed launch dates.
Building a Full-Stack Photonic Quantum Platform
Superconducting circuits and trapped ions power many quantum computers. Photonic systems take a different route. They use photons, or particles of light, to process quantum information.
Quanfluence is building a full-stack platform. It brings together photonic chips, electronic control systems and software in one computing system. The company is also working on manufacturing scale-up, component integration and hardware delivery. These steps are meant to move it from lab prototypes to larger machines.
Early Revenue Through Optical Computing
Universal quantum computing is the long-term goal. In the meantime, Quanfluence is selling optical computing products.
The startup has built an optical Ising machine. It targets optimisation problems with many linked variables, such as resource allocation, scheduling and logistics. The system can handle hundreds of interconnected variables at once.
This machine is not a universal quantum computer. It is built for specific optimisation tasks. Universal quantum computers aim to run a wider range of quantum algorithms.
Quanfluence has reportedly sold about three optical Ising machines. It is also running paid pilots with 10 to 15 corporate customers. The company sells hardware directly and offers remote, usage-based access to its systems. It has not shared revenue figures, customer names or independently assessed performance benchmarks.
Developing Photonic Integrated Circuits
Sujoy Chakravarty, Ravi Mehta, Biman Chattopadhyay, Aditi Vaidya, Anil Prabhakar and Sandeep Goyal founded Quanfluence in 2021. The company builds its technology around photonic integrated circuits and supporting electronics.
It has reported several technical milestones. These include the design and fabrication of multiple photonic and electronic integrated circuits. It has also improved low-loss coupling between chips and fibre. In addition, it has demonstrated the generation of quantum states of light.
The next challenge is bigger than building single components. Quanfluence must combine them into reliable systems that can handle more complex computations. It is also building the manufacturing and delivery capacity needed to move beyond prototypes.
The startup has about 25 employees. It reportedly plans to grow the team to around 40 over the next year.
Funding History and Investor Interest
The new round follows a $2 million seed round announced in December 2024. That money was meant to speed up quantum computer development and expand near-term products.
The two reported rounds total $12 million. However, the company’s full funding history and the exact structure of the latest round have not been independently confirmed.
The backing from Chiratae Ventures, Rainmatter and Pi Ventures points to investor interest in specialised computing. These technologies need heavy research and development before they mature. For Quanfluence, optical computing offers an early route to revenue while it works on a more versatile quantum architecture.
India’s Quantum Technology Push
The funding arrives as India builds its domestic quantum ecosystem. The National Quantum Mission provides a policy framework. It supports research and development in quantum computing, communication, sensing and materials.
Private investment is also growing across quantum segments. Quantum cybersecurity firm QNu Labs raised ₹200 crore in a Series A1 round in September 2026. The National Quantum Mission and Speciale Invest led that round.
For now, Quanfluence is focused on specialised optical computing systems. It is also strengthening the hardware and components needed for future quantum processors. Its progress will depend on reliable performance, successful hardware integration and its ability to scale beyond early prototypes.
