Key Investor Signals
Raised €680,000 with specialist healthtech investors
Kunsen Ventures led the May 2026 round, joined by radiologists Ana Canga and Luis Cerezal and technology investor Ricardo Moya to support rollout and development.
Secured a €325,000 NEOTEC development grant
CDTI’s December 2025 definitive award allocated €325,000 to Ainovis for multimodal AI that automatically generates radiology reports, with work scheduled for 2026.
Partnered with San Roque on medical-image AI
Hospitales Universitarios San Roque and Ainovis are collaborating on image-analysis AI that combines imaging findings with clinical and patient-history context.
Other Positive Signals
- Built Ainovis One with dictation, structured drafting and clinical consistency checks.
Team
Pablo Menéndez Fernández-Miranda
CEO and Co-founder
- Practiced musculoskeletal radiology at Hospital Universitario Rey Juan Carlos after clinical research at Clínica Universidad de Navarra.
- Completed a medical PhD on applying deep learning to medical images, alongside specialist training in radiology.
- Held associate-professor roles at Universidad San Pablo CEU and Universidad Rey Juan Carlos, teaching alongside clinical practice.
Miguel Herencia García del Castillo
CTO and Co-founder
- Software engineer with specialist expertise in deep learning and the synthesis of medical images for AI development.
- Worked as a back-end developer at HarBest Market in 2023, gaining experience building the server side of software.
- Co-authored a 2025 study using diffusion models to generate pathology-conditioned brain MRI images for clinical AI research.
Manuel Cerezo
COO and Co-founder
- AI engineer specializing in generative models and distributed systems, combining model development with software infrastructure.
- Co-authored a 2025 paper on diffusion models for brain MRI generation, adding hands-on research experience in generative medical imaging.
- Software Engineering and Deep Learning alumnus at U-tad, later invited to share applied generative-AI experience with engineering students.
Product
Ainovis One uses the Carolina assistant to convert dictated or typed findings into editable radiology reports. A separate research model analyzes knee MRI images and drafts findings for specialist review, extending the system from report preparation toward image interpretation.
Multilingual report drafting
Radiologists enter findings by voice or text in their preferred language. Carolina turns those instructions into structured report drafts, helping clinicians document the examination without imposing a rigid input form.
Clinical review and editing
The clinician can review, rewrite and refine every part of the report before approval. The assistant also checks for clinical inconsistencies; responsibility for interpretation and final content stays with the radiologist.
Knee-focused image analysis
The research system combines computer vision with language models to analyze knee MRI series. It identifies anatomical structures and potential lesions, then translates the image findings into a draft for specialist validation.
Market Overview
Ainovis sells into a large diagnostic-imaging ecosystem where hospitals are adding AI to existing radiology workflows rather than replacing them. The global diagnostic-imaging market is projected at $26.5B in 2025, while AI in medical imaging is growing much faster as providers seek productivity and decision-support tools.
European radiology already shows meaningful AI adoption, but deployment is constrained by budget, validation and system integration. Buyers therefore need tools that produce measurable workflow gains while preserving radiologist oversight, fitting Ainovis's review-and-approve approach to reporting and image interpretation.
Projected global diagnostic-imaging market size in 2025, rising to $32.9B by 2030.
Estimated global AI medical-imaging market in 2025, projected to reach $29.95B by 2034.
Share of surveyed European radiology professionals already using AI in clinical practice in 2024.
Share of European survey respondents citing cost or lack of budget as a barrier to clinical AI adoption.
Comparable Outcomes
Quantib
Developed AI and machine-learning software for radiology, including applications for prostate cancer assessment and neurodegeneration. RadNet acquired Quantib in January 2022 and added it to its AI division alongside DeepHealth and Aidence.
Medica Group
Provided remote radiology reporting services that connected hospitals with specialist radiologists. IK Partners completed the acquisition of Medica in July 2023 through its IK IX Fund, taking the radiology reporting provider private.
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Sources
This profile was built from public company materials, ecosystem sources, market references, and professional profiles.