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    Home»Startups»Sweden’s Cytely raises €3 million as labs report 75% faster analysis using its smart microscopy platform
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    Sweden’s Cytely raises €3 million as labs report 75% faster analysis using its smart microscopy platform

    Editor Times FeaturedBy Editor Times FeaturedOctober 26, 2025No Comments5 Mins Read
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    Cytely, a Lund-based DeepTech startup, has secured €3 million in a brand new funding spherical to energy the enlargement of Cytely’s sensible microscopy platform, which transforms normal laboratory microscopes into real-time knowledge engines, drastically decreasing the time scientists spend on handbook evaluation.

    The spherical was led by Ugly Duckling Ventures, with continued assist from present investor Icebreaker.vc. Cytely is a part of the portfolio at SmiLe Enterprise Hub and has workforce members primarily based in Lund, San Diego, and Singapore.

    “Scientists have been constrained by workflows constructed for photographs, not knowledge. Cytely transforms any microscope right into a real-time measurement instrument, closing the loop from acquisition to choice on an experiment-day timescale reasonably than a grant cycle,” mentioned Philip Nordenfelt, Cytely Co-founder & CEO. “Our objective is to make each experiment analysis-ready from creation, so discoveries stack and science compounds.”

    The funding introduced for Cytely matches inside a broader European DeepTech and HealthTech sample seen throughout 2025.

    In February 2025, QT Sense (Netherlands) secured €6 million to develop its quantum-sensing expertise for single-cell diagnostics, whereas Pixel Photonics (Germany) acquired €1 million in grant funding to advance multi-mode photon detectors for microscopy and diagnostics.

    Collectively, these raises illustrate a shared concentrate on automation, precision imaging, and data-centric analysis infrastructures. Inside this context, Cytely’s smart-microscopy strategy – enabling real-time, analysis-ready knowledge from normal devices – positions it as a part of a rising European motion in the direction of accessible, scalable scientific innovation.

    “Their imaginative and prescient is actually transformative. We’re thrilled to guide this spherical and assist the mission to make sensible, knowledge‑centric microscopy accessible to each lab,” mentioned Louise Lachmann, Associate at Ugly Duckling Ventures.

    Based in 2023, Cytely builds data-centric instruments for organic discovery. Its core platform permits labs to seize, course of, and analyse complicated mobile knowledge routinely. This makes the historically sluggish and handbook technique of microscopy evaluation not solely sooner but additionally statistically sturdy – unlocking new potentialities for labs that will not have had entry to high-end infrastructure.

    The corporate was co-founded by Philip Nordenfelt, who additionally serves as CEO. With a background in immunology and mechanobiology, Nordenfelt brings each scientific and technical credibility to the desk. His mission is to remodel the present microscopy bottleneck right into a feedback-rich workflow that accelerates speculation testing and discovery.

    The platform has already been adopted by main analysis establishments, together with Lund College, and is being utilized in biomedical analysis fields corresponding to virology, oncology, and metabolic ailments.

    “Cytely’s software program is a democratising power in science. It decouples world‑class discovery from world‑class funding, empowering any researcher with a microscope to deal with the most important challenges in human well being. All microscopy will change into ‘sensible microscopy’; Cytely is popping the ‘wild west’ of chance into a strong, accessible platform that can speed up discovery for researchers in all places,” mentioned Dr Vinay Swaminathan, Head of the Laboratory of Cell & Molecular Mechanobiology at Lund College.

    Historically, microscopy has revolved round static photographs, leaving researchers to manually assess particular person cells – a course of that may take weeks and infrequently fails to supply knowledge with statistical confidence.

    Cytely seems to be to alter that paradigm by making knowledge, not photos, the first end result. Its system automates picture acquisition, quantifies whole samples, and provides outcomes which can be standardised, reproducible, and analysis-ready in actual time. The software program is hardware-agnostic, designed to work with most trendy microscopes, eliminating the necessity for expensive, specialised imaging rigs.

    “Lastly, we really feel like this challenge is definitely working… We’re accumulating massive‑scale knowledge and unraveling mechanisms of viral latency, one thing that simply wasn’t attainable earlier than,” mentioned Prof. Alex Evilevitch.

    A case from Lund College exemplifies the platform’s impression: researchers learning herpesvirus latency have been beforehand unable to course of greater than 0.1% of their pattern knowledge because of handbook limitations. Utilizing Cytely, they reportedly processed practically 100% of samples and recognized a beforehand unobservable cell-line defence mechanism. The change enabled them to revamp their protocol and obtain extra progress in a single month than within the earlier 5 years.

    Past academia, Cytely is delivering sturdy returns in industrial settings. A most cancers analysis lab utilizing the platform diminished handbook evaluation time by 75%, saving roughly €300k yearly – successfully doubling its workforce.

    A nanowire BioTech firm elevated its R&D throughput by 40%, estimating a further $1 million in annual worth. One other lab changed a €400k high-throughput imaging setup fully with Cytely’s pipeline on present microscopes.

    The newly secured funding will assist the event of clever acquisition instruments suitable with all microscope manufacturers, and create one-click workflows for researchers no matter their knowledge evaluation abilities.

    These enhancements intention to show the platform into a completely built-in discovery community, the place validated protocols and datasets may be shared, replayed, and iterated upon—finally laying the muse for predictive evaluation and partially autonomous analysis.





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