Gesund.ai orchestrates the AI as-a-Medical Device lifecycle, providing privacy-centered access to diverse yet standardized medical data sources, and a unique analytical toolbox that fosters clinical validation, regulatory clearance and effective marketing
Model owner shares clinical study with Gesund for curation of appropriate dataset(s), and uploads their model onto Gesunds federated validation platform, which resides on hospital premise or private cloud.
Model runs against a previously unseen validation data set that has been curated on the hospital side.
Model accuracy metrics are produced and displayed on the Gesund platform for further examination with respect to patient characteristics, scenario analyses and stress testing.
The model insights are exported into a report for the model owner to supplement their regulatory submission.
No-hassle model exploration
and validation running models against
real-world data in a secure environment
No more dependency
on software engineers to
containerize or deploy models
Share models
and insights out of the
box with collaborators
Dataset matching
according to case-specific
regulatory demands
Annotation
as-a-service
Assessment of demographic
characteristics for explanatory
purposes
Post-market validation
and evaluation
Update model via
re-training with prospective
studies against standard of care
Identify gaps
in algorithms
To tap proprietary data sources and reader expertise through our platform
Enes Hoşgör, Ph.D., CEO at Gesund: AI Is on the Road to Improving Healthcare: It’s Time to Build a Superhighway
A startup provides medical data for testing AI health solutions
‘I need evidence yesterday’: Gesund raises $2 million to provide algorithm-validating data
Gesund.ai Exits Stealth with $2M in Funding to Build the Highway of Clinical-Grade AI for Safe and Effective Medical Applications
We are building a privacy-first MLOps platform for data-driven organizations in healthcare and life sciences. The platform is designed to support the entire lifecycle of machine learning (ML) efforts to accelerate breakthrough medical research and bring clinical-grade ML solutions to market. Our fast-expanding strategic network includes early clinical and technology partners and organizations in the US, Israel and Europe.
We are building a privacy-first MLOps platform for data-driven organizations in healthcare and life sciences. The platform is designed to support the entire lifecycle of machine learning (ML) efforts to accelerate breakthrough medical research and bring clinical-grade ML solutions to market. Our fast-expanding strategic network includes early clinical and technology partners and organizations in the US, Israel and Europe.