cysto.ai is a plug-and-play AI system for real-time detection of carcinoma in situ during white light cystoscopy. No hardware modification. No workflow disruption.
Carcinoma in situ of the bladder is the most aggressive non-muscle-invasive bladder cancer. It is flat, non-papillary, and visually subtle, easily mistaken for benign inflammation or normal bladder tissue under standard white light cystoscopy.
White light is used in the vast majority of cystoscopies globally. Enhanced imaging modalities require significant infrastructure investment and are unavailable at most practices where bladder cancer surveillance occurs.
Missed CIS has serious consequences. Left undetected, CIS advances to muscle-invasive disease in 40–83% of cases, requiring radical surgery. Bladder cancer has the highest lifetime treatment cost of any solid tumor in the United States, up to $200,000 per patient, driven by the relentless surveillance burden and high recurrence rates that follow a missed or delayed diagnosis.
cysto.ai is an AI system designed to understand a cystoscopy procedure the way an experienced urologist does, as a continuous event with spatial memory, not a sequence of isolated frames.
A real-time heatmap highlights regions of interest associated with CIS during the live procedure. The overlay appears on a secondary monitor adjacent to the physician's primary display. No interruption to clinical workflow. Runs on an edge device in the procedure room at 30fps.
After each procedure, the system automatically generates a spatially reconstructed map from the cystoscopy video, showing scope coverage, AI detection locations, physician-flagged moments, and biopsy sites pinned to anatomical coordinates. Currently in active development as part of the clinical trial.
On our development roadmap: the system will compare bladder maps across surveillance visits to detect change over time, giving urologists an objective spatial record of how each region has evolved between procedures. That capability does not exist today. Building it is the goal.
Generated automatically from procedure video. No additional steps required from the physician or coordinator. Currently under active development as part of our clinical trial program.
Compatible with all major cystoscopy towers, including Storz, Olympus, and Ambu. No modification to existing equipment. The device operates in a pass-through configuration — your existing display and workflow are completely unaffected. Installation takes approximately two hours with no equipment downtime.
cysto.ai has established a multi-site clinical network spanning the United States, Europe, the Middle East, and Asia-Pacific, building the only pathology-correlated, spatially-annotated cystoscopy dataset in the world.
North America · Europe · Middle East · Asia-Pacific
We are actively enrolling investigational sites and building strategic partnerships. If you are a urologist, hospital administrator, or potential collaborator, we would like to speak with you.
Participating sites receive the full hardware kit, installation support, and early access to each new capability as the platform develops. There is no cost to the site.