{"id":193108,"date":"2025-10-11T16:09:07","date_gmt":"2025-10-11T16:09:07","guid":{"rendered":"https:\/\/www.newsbeep.com\/uk\/193108\/"},"modified":"2025-10-11T16:09:07","modified_gmt":"2025-10-11T16:09:07","slug":"stockholm-quantum-tech-firm-firstqfm-ab-secures-e1-2-million-for-ai-powered-quantum-computing","status":"publish","type":"post","link":"https:\/\/www.newsbeep.com\/uk\/193108\/","title":{"rendered":"Stockholm Quantum Tech Firm FirstQFM AB Secures \u20ac1.2 Million For AI-Powered Quantum Computing"},"content":{"rendered":"

Quantum technology firm FirstQFM AB, based in Stockholm, secured \u20ac1.2\u202fmillion in pre\u2011seed funding on 10\u202fOctober\u202f2025 to accelerate the commercialisation of its proprietary AI foundation models<\/a>. BSV Ventures led the round and saw participation from Almi Invest, Further than Capital and Luminar Ventures. The capital will drive the development of FirstQFM\u2019s patent\u2011pending models, which the company claims can boost the reliability and scalability of near\u2011term quantum machines, making them more useful for industry applications.<\/p>\n

How FirstQFM\u2019s AI Models Slash Quantum Costs<\/p>\n

FirstQFM\u2019s core offering is a set of machine\u2011learning foundation models that sit beneath the quantum software stack, analysing and optimising the behaviour of qubits before and during computation. By feeding real\u2011time telemetry from superconducting or photonic hardware<\/a> into its models, FirstQFM can predict calibration drifts, detect anomalous error patterns and suggest corrective pulse sequences. The result is a dramatic reduction in the time and money spent on device tuning and error mitigation. In pilot tests on a 53\u2011qubit superconducting processor, the company reported a 40\u202f% drop in calibration overhead and a 30\u202f% increase in the yield of useful computation per run.<\/p>\n

The models are designed to be agnostic to the underlying hardware, allowing a single framework to serve IBM\u2019s Eagle, Rigetti\u2019s Aspen\u201123 or IonQ\u2019s trapped\u2011ion machines. \u201cOur technology improves device performance<\/a>, scalability, and availability,\u201d said Isaiah Hull, CTO and co\u2011founder. \u201cBy massively reducing the costs and time it takes to get outcomes and run workloads, eventually from any quantum hardware, it makes the powerful capabilities of quantum available to more industries.\u201d The foundation models also integrate with existing quantum programming languages, enabling developers to write code that automatically benefits from the optimisation layer without learning new tools.<\/p>\n

\u20ac1.2 Million to Tame NISQ Era Challenges<\/p>\n

The funding will finance the next phase of FirstQFM\u2019s research, which focuses on the NISQ (Noisy Intermediate\u2011Scale Quantum) era where error rates remain high and fault\u2011tolerant architectures are still out of reach. Vish Ramakrishnan, CEO, explained that the capital will support the execution of ongoing pilot projects and enable the usefulness of NISQ\u2011era quantum machines. \u201cThe funding will help support the further development of FirstQFM\u2019s proprietary patent\u2011pending technology, execution of ongoing pilot projects and enable the usefulness of NISQ era quantum machines<\/a>,\u201d he said.<\/p>\n

FirstQFM\u2019s approach tackles the two most pressing NISQ bottlenecks: device calibration and error correction. Traditional calibration routines require manual intervention and can take hours for a single device. FirstQFM\u2019s AI models automate this process, continuously learning from device telemetry and reducing calibration time from days to minutes. For error correction, the models analyse error syndromes in real time, suggesting adaptive pulse sequences that suppress decoherence without the need for additional qubits. In early trials, this adaptive strategy yielded a 25\u202f% improvement in logical qubit lifetime on a 20\u2011qubit device, a significant stride toward practical quantum advantage.<\/p>\n

Partnering With Hardware Developers for Fault Tolerance<\/p>\n

FirstQFM is forging close partnerships with quantum hardware manufacturers to embed its optimisation layer directly into the control firmware. By working with companies such as IBM, Rigetti and IonQ, the firm hopes to influence the design of future processors, ensuring that the hardware is more amenable to AI\u2011driven calibration and error mitigation<\/a>. \u201cWe are partnering directly with quantum hardware developers and will work with them on the path to fault tolerance,\u201d Hull added.<\/p>\n

The collaboration also involves co\u2011developing benchmark suites that measure the impact of AI\u2011enhanced calibration on algorithmic performance. Early results show that a simple variational quantum eigensolver run on a 32\u2011qubit device achieved a 15\u202f% higher fidelity after applying FirstQFM\u2019s optimisation layer, translating to more accurate molecular simulations in chemistry. By integrating the models into the hardware control loop, FirstQFM aims to create a virtuous cycle where hardware improvements feed back into better AI models, which in turn drive further hardware optimisation.<\/p>\n

BSV Ventures Bets on Superconducting Performance Gains<\/p>\n

BSV Ventures, the lead investor, expressed enthusiasm about the tangible performance gains FirstQFM has demonstrated on superconducting hardware<\/a>. \u201cWe were impressed by the performance gains FirstQFM achieved on superconducting hardware. Excited to see this developed further and rolled out across the various quantum modalities. The value is apparent,\u201d said Peter Gullander, fund manager at Almi Invest.<\/p>\n

BSV\u2019s general partner Erik Bhullar echoed this sentiment, noting that the company\u2019s solution \u201cmassively reduces the costs and time it takes to get outcomes and run workloads.\u201d Bhullar added that such reductions could accelerate the adoption of quantum solutions in finance, where latency and reliability are paramount. Meanwhile, Luminar Ventures\u2019 partner Reid Jackson highlighted the broad applicability of FirstQFM\u2019s technology across major verticals, from life sciences to mobility. \u201cFirstQFM\u2019s technology, intellectual property, and global partnerships position it to have a strong impact on the emerging quantum computing sector,\u201d said Stefan Lindeberg of Further Than Capital.<\/p>\n

The investment also underscores a broader industry trend: early\u2011stage quantum startups are increasingly turning to AI to bridge the gap between noisy hardware and real\u2011world applications. FirstQFM\u2019s focus on foundational models that can be deployed across multiple hardware platforms positions it as a key player in this space, potentially reshaping how quantum computers are calibrated, operated and integrated into existing workflows.<\/p>\n

FirstQFM\u2019s \u20ac1.2\u202fmillion raise marks a decisive step toward making quantum computing more accessible and reliable. By marrying advanced machine learning with the intricacies of quantum hardware, the Stockholm\u2011based company is tackling the twin challenges of calibration and error correction that have long hampered the field. Its partnerships with leading hardware developers promise a future where AI\u2011enhanced optimisation becomes a standard part of quantum control, bringing the promise of quantum advantage closer to industries that stand to benefit most, from drug discovery to financial modelling. As the NISQ era evolves, FirstQFM\u2019s foundation models could become the invisible layer that turns tomorrow\u2019s experimental machines into tomorrow\u2019s production systems.<\/p>\n","protected":false},"excerpt":{"rendered":"Quantum technology firm FirstQFM AB, based in Stockholm, secured \u20ac1.2\u202fmillion in pre\u2011seed funding on 10\u202fOctober\u202f2025 to accelerate the…\n","protected":false},"author":2,"featured_media":193109,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[21],"tags":[4323,86,56,54,55],"class_list":{"0":"post-193108","1":"post","2":"type-post","3":"status-publish","4":"format-standard","5":"has-post-thumbnail","7":"category-computing","8":"tag-computing","9":"tag-technology","10":"tag-uk","11":"tag-united-kingdom","12":"tag-unitedkingdom"},"_links":{"self":[{"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/posts\/193108","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/comments?post=193108"}],"version-history":[{"count":0,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/posts\/193108\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/media\/193109"}],"wp:attachment":[{"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/media?parent=193108"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/categories?post=193108"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.newsbeep.com\/uk\/wp-json\/wp\/v2\/tags?post=193108"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}