Jeremy Stueven, Chief Executive Officer (CEO) of Vitazi.ai, tells CB Insights how they view the market, customer needs, and their company.
How do you define your market and where does your company fit into that space?
Vitazi AI operates in the emerging retinal intelligence market at the intersection of ophthalmic imaging, healthcare data infrastructure, and AI-enabled clinical workflows. Our conservative core TAM is approximately $600M today or more, based on global ophthalmology image management and picture archiving and communication system (PACS) markets within the ophthalmology and optometry space. This market is projected to grow to exceed $1.5B by 2034. The estimate excludes adjacent opportunities in AI diagnostics, population health screening, life sciences research, and systemic disease detection, making the longer-term addressable market substantially larger.
The number one problem we solve today is fragmentation. Retinal images are trapped across disconnected devices, multiple different vendors, proprietary software, providers, and locations. This prevents clinicians in the eye care industry from seeing complete longitudinal patient records, and it makes collaboration and comparison quite difficult, limiting administrators’ operational visibility and leaving valuable data largely unavailable for research in AI.
Vitazi AI provides a vendor-neutral orchestration layer for retinal intelligence. We are, in essence, the retinal infrastructure. We connect ophthalmic devices, from optical coherence tomography (OCT) to fundoscopic imaging, scanning laser ophthalmoscopy (SLO) technology, and others, across care settings, organizing them for the patient and their providers, and enabling truly coordinated workflows, longitudinal insights, research, and future analytical applications. Rather than competing as other imaging devices or isolated diagnostic algorithms have done in this space, Vitazi AI is building the connected infrastructure through the retinal data that can become a reusable clinical and research asset.
When you win business, why do you win? What differentiates you from competitors?
When we win, it’s because customers want more than another image archive. They want a vendor-neutral foundation for turning fragmented retinal data into longitudinal clinical and research intelligence. We compete most often with ophthalmic data management platforms such as Topcon Harmony, ZEISS FORUM, Heidelberg, HEYEX, as well as PACS Solutions. Our closest competitor is Topcon Harmony. However, our largest competitor is often the status quo: images remaining siloed inside individual devices, local servers, and proprietary applications, with teams relying on manual exports and incomplete patient records.
Vitazi AI is differentiated in three ways. First, we are vendor-neutral and not built to drive sales of a particular imaging device. Second, we organize retinal imaging and information longitudinally around patients and across device locations and care settings, not simply around an individual exam. Third, our platform is designed to activate that connected data for multiple uses, including clinical collaboration, operational insight, patient engagement, research, and future AI applications.
We most often take business away from fragmented device-specific workflows and legacy image management environments rather than through a simple one-for-one software replacement. Customers choose Vitazi because they want an independent, scalable infrastructure partner that can make their existing image management systems work together while preparing their data for the future of retinal intelligence.
What do you believe about your market that no one else believes?
We believe the retinal image will become a new longitudinal vital sign, thus the name Vitazi, rooted in “vital”, and that the most valuable company in this market will not be the one that builds a single diagnostic algorithm or an imaging device. It will be the company that builds the infrastructure connecting retinal data across time, devices, providers, and diseases.
Conventional wisdom treats each retinal image as an episodic artifact. Capture it, evaluate it for one disease, document your result, and leave the image inside the device or local system. The market is therefore focused heavily on better cameras and individual AI models for a specific disease. We believe that is a missed larger opportunity.
The retina provides a direct, non-invasive view of neural and vascular health. Its greatest value emerges when images become longitudinal, interoperable, and connected with other clinical and molecular data. In that form, retinal imaging can support not only eye care, but also earlier insight into systemic and neurodegenerative disease.
Vitazi AI is positioned to capture this opportunity because we are building the vendor-neutral retinal intelligence layer, not another closed ecosystem or single-purpose algorithm. Our platform connects and organizes imaging around the patient, creating the permissioned longitudinal data foundation needed for clinical collaboration, research, and many future AI applications. Our core insight is that algorithms will proliferate, but the connected data infrastructure on which those algorithms depend will be scarce. Vitazi AI intends to become that data infrastructure, the system through which the retina data becomes a reusable health asset rather than a one-time image for one-time disease management.
Which growth stage best describes your company today?
<$1M ARR
What has been your approximate Year-over-Year growth trend?
100%+
Where do you see your market headed in the next 6 months?
Over the next 6 months, we expect retinal imaging to move from isolated devices and AI pilots toward connected, enterprise-scale clinical infrastructure. Health systems increasingly recognize that deploying more algorithms doesn’t solve the underlying problem if the image remains fragmented and longitudinal records are incomplete. And AI tools can’t even integrate into existing workflows anyway.
There are three trends that will accelerate the market. First, healthcare organizations will demand vendor-neutral platforms to connect their devices, sites, and clinical systems. Second, autonomous and assistive retinal AI will continue moving from research into routine care, increasing the need for governed, AI-ready data. Third, and finally, retinal imaging will expand beyond ophthalmology and diabetic eye screening toward broader population health research and multimodal disease detection.
The principal tailwinds are value-based care incentives, persistent diabetic eye exam quality requirements, rapid growth in AI-enabled medical devices, and greater industry emphasis on interoperability. Each increases the value of connected retinal infrastructure. The headwinds are enterprise healthcare’s long purchasing and integration cycles, cybersecurity and privacy requirements, proprietary device formats, and evolving regulatory oversight for clinical AI. Health systems will also demand stronger real-world validation and clear economic returns before adopting new tools at scale.
These forces do favor Vitazi AI. As algorithms multiply and regulatory expectations mature, the market will increasingly need an independent orchestration layer that can connect existing systems to preserve the longitudinal data value and support multiple clinical and analytical applications without locking customers into one device or algorithm vendor.
What function are you investing most heavily in over the next 12 months?
Over the next 12 months, we’re investing heavily in product and engineering, specifically the infrastructure required to connect ophthalmic imaging systems, create longitudinal records, and make that data usable for clinical workflows, research, and future AI applications. This includes software engineering, device and clinical system integrations, data architecture, security, and image analytics. Our priority is not to build one isolated algorithm, it’s to build a scalable, vendor-neutral foundation that allows many devices, workflows, and analytical tools to operate together.
Our major investment is in commercial development, through strategic partnerships and focused sales capacity. Healthcare distribution depends on trusted relationships within the eye care space and with health organizations, technology vendors, researchers, and life sciences partners. Those partnerships also strengthen the platform by adding data, use cases, and routes to market. In short, we’re investing in making the platform enterprise-ready and differentiated, and then in the partnerships, scale, and sales capacity required to deploy that at scale.
What partnerships or ecosystem relationships have become increasingly strategic to your growth?
Three types of partnerships have become increasingly important. First, eye care delivery and clinical data partnerships. Our relationship with Eye Associates in New Mexico, one of the largest ophthalmology organizations in the state, provides access to specialist expertise and a large, diverse retinal imaging environment. This supports clinical validation, product development, and creation of more useful long-term data sets.
Second, deployment with optometrists. We’re increasingly developing multiple different optometry-related partnerships that have an opportunity for sizable scale to deploy the technology, solicit feedback from early beta testers and users, solicit feature feedback, and demonstrate how retinal imaging embedded at the point of care and connected to an imaging hub can truly expand the productivity and workflow of eye care providers.
And next, most important, is the cross-sector biomarker and life science partnership. Recently, we announced an alliance with Circular Genomics. This combines retinal imaging with circular RNA blood biomarkers and viewing Vitazi AI as at the forefront of retinal imaging to determine where there are risks for more targeted, differentiated tools downstream, both in the neurology and precision neurology space as well as in the cardiovascular space. This opens up the door for real clinical trial recruitment, risk stratification, and real evidence to help use the retina as a way to determine further differentiation for patients.
Together, these relationships create a reinforcing ecosystem of eye care partners creating high-quality imaging and clinical insight, healthcare partners enabling deployment at scale, and diagnostic and life science partners extending retinal intelligence into disease markets and beyond.
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