Moonlight AI AG Raises $3.3M To Transform Haematology Labs With AI-Powered Diagnostics
May 6, 2026 | By Team SR

Moonlight AI, a Swiss startup developing image analysis software for clinical-grade diagnostics, has raised €2.8 million ($3.3 million) in a Seed funding round.
SUMMARY
- Moonlight AI, a Swiss startup developing image analysis software for clinical-grade diagnostics, has raised €2.8 million ($3.3 million) in a Seed funding round.
The round was co-led by Lotus One Investment, VP Venture Partners, and MEDIN Fund, with participation from N&V Capital and existing investor QAI Ventures.
Founded in 2022 Moonlight AI focuses on AI-driven diagnostics aiming to improve access to genomic insights for more accurate cancer detection.
Its technology uses computer vision to extract genomic biomarkers and disease signatures directly from routine medical images, helping clinicians make faster and more precise treatment decisions.
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The company addresses key limitations in precision oncology, where Next-Generation Sequencing (NGS) can be costly and time-consuming. By integrating with existing lab imaging systems its software enables faster turnaround times, automated workflows and more efficient use of diagnostic resources.
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Moonlight AI plans to use the funding to expand its proprietary data library, advance solutions for diseases including myelodysplastic syndrome (MDS), non-small cell lung cancer and chronic lymphocytic leukaemia (CLL) and accelerate commercialisation and regulatory approval.
The company has also transitioned into a Swiss Stock Corporation (Aktiengesellschaft) to support international expansion.
“Our technology enables labs to generate actionable, immediate results from slides they already use in their core workflows. By removing the need for expensive hardware or manual processes, we are empowering labs to scale their diagnostic capacity and deliver faster results to patients,” said Christian Ruiz, CEO and co-founder of Moonlight AI.
About Moonlight AI
Moonlight AI builds a fast AI tool that helps doctors detect cancer more easily. It turns medical images into useful information allowing quicker and more accurate diagnoses and helps doctors choose better treatments for different types of cancer.
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