Every scan today lands on a blank screen, and the clinician builds the read from nothing — one slice at a time, under time they rarely have. OraliqAI changes the starting point.
It works the way a trusted second reader would: quietly, before you sit down. The anatomy is already segmented, the findings already flagged and scored, the measurements already taken. What reaches you is a prepared read to confirm or overrule — never a diagnosis handed down.
Most dental AI is built by engineers who have never signed a report. OraliqAI is the opposite: the people who read these scans for a living decide what it flags, how it says it, and where it must stay silent.
Practicing radiologists and dentists define every finding, threshold and report line — not a data team guessing at clinical intent.
Every model change is signed off against ground truth by licensed readers before it can touch a case. No silent updates.
It hands you a prepared second read to confirm or overrule — built to support the clinician's judgment, never to replace it.
One engine across 3D volumes and surface meshes — nothing changes about how the study is acquired.
Head-and-neck volumes: implant-site planning, inferior alveolar nerve canal proximity, sinus, TMJ and airway.
Surface meshes assessed for occlusion, wear, restoration margins and arch metrics.
2D reads for caries, periapical lesions and bone-loss patterns across the full arch.
Intraoral films scored tooth-by-tooth, reported in FDI notation with per-finding confidence.
Four stages, each recording model version, input hash and slice-level evidence — an audit trail behind every finding.
DICOM and mesh files are checked and de-identified at the door, then graded diagnostic or limited before anything runs.
Anatomy is segmented, pathology detected per site, each finding scored for confidence and localized to its slices.
Volumes, distances and asymmetry are measured; a structured, clinician-readable report is drafted from the findings.
Urgency is triaged and routed to the right queue; the clinician confirms, overrides with a reason, and signs.
A second read shouldn't slow you down. It should be waiting when you arrive.— The design principle behind OraliqAI
Four levels drive routing and alerting — and the same scale colors every finding, overlay and report, by design.
OraliqAI is assistive clinical decision support — not an autonomous diagnostician. It is built around the boundaries a medical device is held to: review before action, a trail behind every claim, and patient data that never leaves its lane.
Nothing is asserted that a clinician has not seen, and nothing is finalized that a clinician has not signed.
No report finalizes and no record writes back without an explicit confirm-then-sign.
Every model output and clinician decision is written to an append-only, hash-chained log.
Patient data is isolated per practice at the database and storage layer — never commingled.
Sign in to the clinician console, or talk to us about bringing OraliqAI to your practice.