Heidelberg Engineering and RetinAI (Ikerian AG) have announced that their product RetinAI Discovery for Clinics will soon be available through Heidelberg Engineering’s direct global sales organisation. This expands on the collaboration between Heidelberg Engineering and RetinAI after EssilorLuxottica’s acquisition of RetinAI in October 2025.
This collaboration will integrate Heidelberg Engineering’s diagnostic imaging technologies with RetinAI’s ophthalmic data management, AI-supported analyses and connectivity for clinical practices.
RetinAI Discovery provides a centralised platform for managing ophthalmic patient data, such as optical coherence tomography (OCT), fundus and other images. Its AI models can also provide AI-supported retinal image anaylsis and quantitative insights including retinal layer and fluid segmentation and quantification, and longitudinal assessment of imaging data. It also supports secure case sharing and connected workflows, including tele-ophthalmology applications. A key benefit will be the integration of the Heidelberg SPECTRALIS imaging with RetinAI’s data and AI environment.
The RetinAI Discovery for Clinics collaboration builds on an established relationship between the two companies. “Our existing relationship with Heidelberg Engineering provides a strong foundation for expanding access to RetinAI Discovery for clinics,” said Dr Carlos Ciller, co-founder and CEO of RetinAI. “Combining Heidelberg Engineering’s imaging expertise and global customer relationships with RetinAI’s data-management and AI capabilities can make advanced digital workflows more accessible to eye care professionals.”
“Heideberg Engineering has always focused on providing clinicians with high-quality imaging and meaningful information for confident clinical decision-making,” said Kfir Azoulay, Managing Director of Heidelberg Engineering. “Making RetinAI Discovery for Clinics available through Heidelberg Engineering is a natural extension of this approach. By bringing advanced imaging, data, and AI-supported analysis closer together, we see significant potential to support more connected and efficient clinical workflows.”
