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§ Private Profile · Vienna, Austria
Develops deep learning AI software to improve radiology workflows, detecting disease patterns in 3D medical images for radiologists.
contextflow has raised $14.0M across 2 funding rounds.
Key people at contextflow.
contextflow has raised $14.0M in total across 2 funding rounds.
Based in Vienna, Austria, contextflow develops deep learning-based artificial intelligence software that improves radiology workflows by detecting disease patterns in three-dimensional medical images such as CT and MRI scans. The company's core technology is a 3D image-based search engine called SEARCH, which assists hospitals and radiologists with diagnosis and reporting across multiple modalities and organs. The enterprise has secured significant capital to scale its operations, including a €6.7 million Series A investment round in 2021 and a €1.2 million grant from the European Commission in 2020. The firm has participated in the Philips HealthWorks accelerator program and maintains an advisory board featuring leadership from the European Society of Radiology and the International Society of Radiology. Spun out of the Medical University of Vienna, contextflow was founded in 2016 by Markus Holzer, Georg Langs, René Donner, and Allan Hanbury.
Key people at contextflow.
contextflow has raised $14.0M in total across 2 funding rounds.
contextflow's investors include B&C Innovation Investments, Andreas Riegler, Crista Galli Ventures, IST cube, Nina Capital, NovaCapital, Alexander Sommer-Fein, TTIP Beteiligungs.
contextflow is an AI-powered healthcare scale-up based in Vienna, Austria, developing deep learning tools to enhance radiology workflows. Its flagship product, ADVANCE Chest CT, analyzes chest CT scans for conditions like lung cancer, interstitial lung disease (ILD), and COPD, providing quantitative and qualitative insights that integrate into existing PACS systems to reduce reading times by ~30% while improving diagnostic accuracy.[1][2][4][6] The company serves radiologists in hospitals and clinics, addressing workload overload, data volume, and diagnostic complexity by delivering transparent, reference-case-based AI support that empowers rather than replaces clinicians, ultimately aiming to improve patient outcomes through faster, higher-quality reporting.[1][2][3]
As a spin-off from the Medical University of Vienna, contextflow has achieved clinical validation via partnerships across Europe, secured CE certification pursuits, and joined programs like the EIC Scaling Club for growth. It also extends to pharma for data processing in research, showing strong momentum with international POCs, awards (e.g., Best Healthtech Startup Austria), and investor backing from firms like xista Ventures and Crista Galli Ventures.[3][4][5][6][8]
contextflow was founded in July 2016 as a spin-off from the Medical University of Vienna's Computational Imaging Research Lab and the Technical University of Vienna's Institute for Information Systems Engineering, emerging from the Khresmoi European research project.[4][6] The core team—Markus Holzer, René Donner, Georg Langs, and Allan Hanbury—comprises AI and medical imaging experts with over 40 years of combined experience, 250+ peer-reviewed publications, and expertise in machine learning for medical images.[1][4]
The idea stemmed from radiology's mounting challenges: surging data volumes, subtle disease variants, and radiologist shortages leading to delays and errors. Pivotal early moments included winning 'Most Promising Startup' in 2016, the Digital Innovation Award in 2017, selection for Philips HealthWorks accelerator in 2018, and Central European Startup Awards for Best Healthtech Startup Austria. Funding rounds in 2019 accelerated CE certification and POCs with seven clinics in Germany, Austria, Netherlands, and Croatia.[5]
contextflow stands out in AI radiology through these key strengths:
contextflow rides the AI-in-healthcare wave, specifically radiology AI amid global radiologist shortages, exploding imaging data (e.g., CT scans), and precision medicine demands. Timing aligns with regulatory progress like EU AI Act and reimbursement pathways, enabling scale-up from research to clinical deployment.[2][3][5] Market forces favoring it include aging populations driving chronic disease imaging needs, post-COVID diagnostic backlogs, and deep tech maturation from academic labs to CE-marked devices.[1][6]
It influences the ecosystem by pioneering transparent, multi-modal AI that boosts efficiency without replacing experts, supporting non-specialists to expert levels, and partnering with platforms like Alma HEALTH. As an EIC Scaling Club member, it connects investors and policymakers, accelerating AI adoption in European healthcare and setting standards for explainable medtech.[3][6]
contextflow is poised for expansion with international commercialization, leveraging clinical evidence for reimbursements (starting lung cancer), more POCs, and pharma/research extensions. Trends like federated learning for data privacy, multimodal AI (beyond CT), and global hospital digitization will propel it, potentially capturing share in a $10B+ radiology AI market.[2][3][8] Its influence may evolve toward category leadership via acquisitions or broader imaging suites, solidifying Vienna's deep-tech hub status while empowering radiologists worldwide—directly advancing its founding mission to free clinicians for patients.[1][4]
contextflow has raised $14.0M across 2 funding rounds. Most recently, it raised $8.0M Series A in September 2021.
| Date | Round | Lead Investors | Other Investors | Status |
|---|---|---|---|---|
| Sep 7, 2021 | $8M Series A | B&C Innovation Investments | Andreas Riegler, Crista Galli Ventures, IST Cube, Nina Capital, NovaCapital, Alexander Sommer Fein, TTIP Beteiligungs | Announced |
| May 1, 2021 | $6M Series A | — | IST Cube, Nina Capital | Announced |
