Healthcare AI startup Forithmus has secured $4 million in pre-seed funding to develop a new generation of artificial intelligence systems designed to transform how medical imaging is interpreted globally.
The round was co-led by Point Nine and E2VC, with participation from Tibas Ventures, Reece Chowdhry, and several angel investors.
Founder Edge: Where Medicine Meets Engineering
At the pre-seed stage, team quality is often the defining factor—and Forithmus stands out with a rare combination of expertise.
The company was founded by Ibrahim Ethem Hamamci and Sezgin Er, who bring hybrid backgrounds in medicine and computer science/engineering. Both founders combine medical training with advanced technical education (MD-PhD / double major pathways), positioning them uniquely at the intersection of clinical practice and AI development.
This dual perspective is critical in a field where understanding both clinical workflows and complex data systems is essential to building effective solutions.
Tackling One of Healthcare’s Biggest Bottlenecks
Despite the widespread availability of medical imaging technologies, access to expert interpretation remains a global challenge. A shortage of radiologists and specialists continues to limit timely diagnosis, contributing to millions of preventable deaths each year.
Forithmus is positioning itself at the center of this problem, aiming to extend medical expertise through artificial intelligence.
From Point Solutions to Generalist AI
Rather than building narrow AI tools focused on single diseases or imaging tasks, Forithmus is developing what it calls “generalist medical intelligence.”
The company argues that traditional point solutions fail to scale in real clinical environments, where diagnoses depend on multiple interacting factors and broader context.
Its approach focuses on building AI systems that:
- Interpret medical images holistically
- Incorporate clinical context into analysis
- Support physicians across multiple workflows
- Function as intelligent assistants rather than replacements
These systems are trained on large-scale datasets combining imaging, radiology reports, and clinical data, with the goal of improving both efficiency and diagnostic consistency.
Building the Infrastructure for Medical AI
A key part of Forithmus’ strategy is openness and collaboration. The company plans to contribute to the ecosystem by developing large-scale datasets and foundation models that can be used by researchers and healthcare institutions globally.
This reflects a broader shift in AI toward shared infrastructure models, particularly in high-impact sectors such as healthcare.
A High-Impact Opportunity
If successful, Forithmus’ technology could significantly increase the productivity of physicians while expanding access to high-quality diagnostics in underserved regions.
The potential impact goes beyond efficiency—touching directly on early detection, treatment outcomes, and global health equity.
Looking Ahead
With strong early backing and a differentiated founding team, Forithmus is entering a fast-growing category at the intersection of healthcare and artificial intelligence.
Its focus on building scalable, general-purpose medical AI systems positions the company to play a meaningful role in shaping the future of global healthcare infrastructure.
