University of Notre Dame Australia (PANACEA-HF program) · Us2.ai
zero — Imaging failure rates
Vendor-reportedHealthcare · Diagnostics · Computer vision · Pilot
Artificial intelligence, professionally covered
Diagnostics
Vendor-reported. The customer is named and the numbers are quoted from the source page, but the account comes from the vendor. No independent confirmation.
Reported by oodle.ai (vendor self-report). Checked against the source page on 2026-09-06. 1 of 1 figures below appear on that page word for word.
Existing observability tools were expensive, limiting, and lacked unified visibility across a growing multi-service architecture, making it hard to pinpoint failures.
Each row is quoted from the source. Figures we could not find on the page in those words are marked — they are kept, not deleted, so you can judge them.
“Render integration set up within 30 minutes, with metrics and logs flowing immediately.”
Quoted word for word from the source
“Oodle makes telemetry smart, cheap, and accessible. Setup was a breeze. No hours wasted like with many other mainstream platforms or our homegrown setup. That simplicity was a game changer.”
zero — Imaging failure rates
Vendor-reportedHealthcare · Diagnostics · Computer vision · Pilot
Vendor-reportedHealthcare · Diagnostics · Computer vision · In production
five minutes — Time to reconstruct full volume at 1mm resolution on a single GPU
Vendor-reportedHealthcare · Diagnostics · Computer vision · Pilot
about 10 minutes — diagnosis time
Vendor-reportedHealthcare · Diagnostics · Computer vision · Pilot
88% — autonomous IT resolution rate
Independently reportedTechnology & software · Process automation · NLP · Scaled
over 65 billion — Machine learning predictions generated
Independently reportedTechnology & software · Personalization · LLM · Scaled