In 2019, Jordan Avi Ogman was diagnosed with TECPR2 — a fatal neurodegenerative genetic disease. But getting that diagnosis took nearly four years. His family visited doctor after doctor across South Florida, only to be told everything looked fine. Take him home. Every kid develops at their own pace.
Those lost years weren’t just frustrating. They were fatal. Jordan’s father, David Ogman, put it plainly: “We’re four years behind in developing the gene therapy. I think by the time the gene therapy is developed, Jordan might not be with us because we lost those four years.”
Now, a Boca Raton company says those lost years don’t have to happen anymore.
GENA: A Geneticist’s Mind in Algorithms
GENA is an AI platform developed by Sivotec that does something deceptively simple: it performs genetic diagnosis in 10 seconds instead of the 3-4 days a human geneticist requires, and the 5-7 years the average rare disease patient actually waits in the real world.
“We actually took the mind of a geneticist and put it into algorithms, and then accelerated the 3 to 4 days that it would take to diagnose one case, and we got it down to 10 seconds,” said Pete Martinez, CEO of Sivotec.
The company reports it has already helped diagnose 160,000 cases involving rare diseases. Its goal is to expand beyond geneticists to pediatricians and primary care doctors — putting diagnostic AI at the front line of medicine where families first show up with unexplained symptoms.
The Rare Disease Diagnosis Gap
The numbers behind rare disease diagnosis are staggering:
- 300 million people worldwide live with rare diseases
- 5-7 years is the average time to an accurate diagnosis
- 6-8 doctors is the typical number of specialists a patient sees before getting answers
- 7,000+ rare diseases exist, most with genetic origins
- Many are treatable if caught early — the time lost isn’t just painful, it’s medically consequential
The bottleneck isn’t a lack of genomic data. It’s a lack of geneticists. There simply aren’t enough specialists to interpret the growing volume of genetic test results. AI that can replicate — and accelerate — that expertise fills a structural gap in the medical system.
Why This Matters Beyond Medicine
GENA represents a category of AI application that gets less attention than chatbots and coding assistants but arguably has more immediate human impact: diagnostic AI for specialized medical domains where human expertise is scarce.
The pattern is replicable. Any field where:
- Expert knowledge can be codified into algorithms
- Demand for expertise vastly exceeds supply
- Delays have real human consequences
…is a candidate for this kind of AI augmentation. Genetic diagnosis is the proof of concept. Radiology, pathology, and ophthalmology are already seeing similar approaches.
The Human Cost of Slow Diagnosis
Jordan Ogman’s story isn’t unique — it’s typical. His family’s experience illustrates why speed matters in rare disease diagnosis:
- Without a diagnosis, there’s no treatment plan
- Without a diagnosis, families can’t connect with research trials
- Without a diagnosis, the disease progresses unchecked
- And for genetic conditions where gene therapy is in development, lost time isn’t just painful — it’s the difference between being eligible for treatment or not
“If we had AI at our fingertips at any of these hospitals, Jordan would have been diagnosed immediately, and his cure would have already been developed,” David Ogman said.
What Comes Next
GENA’s expansion from geneticists to primary care doctors is the critical next step. If AI diagnostic tools can be deployed at the point of first contact — the pediatrician’s office, the GP’s clinic — the 5-7 year diagnosis timeline could collapse dramatically.
The technical capability exists. The regulatory framework for AI-assisted medical diagnosis is still evolving, but the FDA has been increasingly open to AI diagnostic tools that augment rather than replace clinical judgment.
For the 300 million people living with rare diseases worldwide, the question isn’t whether AI will transform diagnosis — it’s how fast the healthcare system will let it.
