Lithuanian BSV Ventures Supports FirstQFM’s ML Approach to Quantum Hardware Challenges

• FirstQFM raises EUR 1.2M Pre-Seed for its quantum ML models, led by Lithuania’s BSV Ventures
• Founders combine significant expertise in both entrepreneurship and quantum computing
• The startup’s patent-pending foundation models improve quantum hardware performance, scalability, and cross-device applicability
• Investors are convinced by FirstQFM technology’s transformative potential across industries and partnerships with hardware developers

This October, Vilnius-based VC fund BSV Ventures became the lead investor in FirstQFM’s Pre-Seed round. FirstQFM is the Swedish developer of ML foundation models to enhance the performance and scalability of quantum computers (the models are patent-pending). The round amounts SEK 13.1M / EUR 1.2M, and other investors include Almi Invest, Further Than Capital, and Luminar Ventures.

Founders with Vision and Expertise

Vish Ramakrishnan (CEO) and Isaiah Hull (CTO) started FirstQFM in 2024. Mr Ramakrishnan is a serial entrepreneur behind CogniFrame, QuAccel, and Logistrics, with leadership experience at Emergis, HSBC, and Scotiabank. He holds an MBA from the University of Mumbai. Mr Hull, in turn, is a quantum research scientist and former academic with 10+ years in quantum computing and machine learning. He is a Quantum Research Fellow at UNC’s Rethinc Labs, consultant for DeepLearning.AI, published author, DataCamp instructor, and holds a PhD from Boston College.

‘Quantum computers continue to face challenges with noise, instability, and scalability. Early efforts to address them relied on manual tuning or small, task-specific ML models. We saw an opportunity to take an alternative approach by developing foundation models for the calibration of superconducting circuit-based quantum processors, reducing the device time required to achieve high-fidelity operations. Without more efficient calibration routines and higher fidelity operations, we cannot realize theoretical quantum speed-ups in practice,’ Mr Ramakrishnan tells ITKeyMedia.

The project was originally incubated within CogniFrame, where the co-founders filed patent applications for the core technology prior to the recent boom in generative AI. The idea that originated within CogniFrame evolved into a dedicated initiative that came to spin out earlier this year. Since then, the team expanded development to other quantum modalities and layers of the stack by exploiting the flexibility and generality of foundation models.

Solving Real-World Problems Across Industries

‘Quantum computers have the potential to solve problems in chemistry, finance, the life sciences, and mobility that are unlikely to ever be solvable on any classical computational device. But this will not happen unless hardware performance improves and devices scale from hundreds to hundreds of thousands of qubits. FirstQFM builds machine learning foundation models that address these two critical areas. In this sense, we are working with hardware developers to make quantum computing a practical reality,’ Mr Hull explains.

‘This is a transformative technology with applications across major verticals. We have received great feedback from our industry experts about its potential and are excited to support its development,’ Luminar Ventures’ partner Reid Jackson adds.

Scaling Across Devices and Quantum Modalities to Unlock Customer Value

FirstQFM is developing models for collections of devices, typically at the quantum modality level or lower. These models allow for application across devices and to multiple tasks across the quantum stack.

‘The beauty of FirstQFM’s solution is how it’s reshaping how quantum technology can be deployed to unlock customer value – by reducing the costs and time it takes to get outcomes and run workloads from any quantum hardware,’ BSV Ventures’ general partner Erik Bhullar comments.

The startup’s partners are primarily quantum hardware developers. As such, FirstQFM defines our success in terms of those partners’ roadmaps.

‘We want them to achieve the performance and scale that is needed to ensure the eventual commercial viability of their devices. When they succeed, we succeed, even if it is quietly and behind the scenes,’ Mr Ramakrishnan clarifies.

Accelerating the Path to Fault-Tolerant Quantum Computing

The Pre-Seed investment of EUR 1.2M allows FirstQFM to expand its technical team, deepen collaborations with hardware partners further, and extend coverage across major quantum modalities. As for the most pressing concern, it remains about aligning with partners’ objectives and helping them to accelerate their roadmaps.

‘We’re quite impressed by the performance gains FirstQFM achieved on superconducting hardware and excited to see this developed further and rolled out across the various quantum modalities. The value is apparent,’ Almi Invest’s fund manager Peter Gullander states.

The FirstQFM team firmly believes that fault tolerant quantum computing is poised to become a collective milestone as the company is working with the quantum hardware developers to accelerate this future. As performance and scalability improves, one is to anticipate meaningful advances in areas such as materials science and the life sciences, where quantum computing is known to offer theoretical speed-ups.

Shaping the Future of Quantum Computing

‘FirstQFM’s technology, intellectual property, and global partnerships position it to have a strong impact on the emerging quantum computing sector,” Further Than Capital’s partner Stefan Lindeberg concludes.

FirstQFM’s work sits at the critical intersection of quantum computing and machine learning, addressing one of the field’s most urgent challenges—scalability. By developing foundation models that optimize performance across diverse quantum hardware, the company is laying essential groundwork for the transition from experimental to commercially viable quantum systems. In doing so, FirstQFM is not just advancing technology—it’s accelerating the timeline for when quantum computing begins to deliver real-world impact across science and industry.