Overjet

Computer vision on radiographs is the entire product. The platform analyzes bitewing and periapical images in real time to detect caries including early interproximal and incipient lesions, quantify periodontal bone level in millimeters, and identify calculus and periapical radiolucency, overlaying findings directly on the image. The company states its models are trained on millions of clinically annotated radiographs, and the separate payer side claims product runs the same analysis against submitted claims.

Positioned as chairside decision support with the dentist retaining diagnosis: findings are presented as visual overlays on the radiograph the clinician is already reading, providing objective measurable data to support rather than replace the final diagnosis. The design strength is that the output is inherently reviewable, since a highlighted lesion on an image can be immediately accepted or rejected against the clinician's own read. The company also markets patient communication as a use case, which is where buyers should think carefully: an AI overlay shown to a patient during a treatment conversation carries persuasive weight, and the payer side product creates a parallel incentive question.

The FDA pathway supplies the transparency floor, since each cleared claim required performance data against a predicate, and the company reports multiple clearances across distinct detection and measurement functions. It states its models were trained on millions of expertly annotated radiographs and publishes commentary on accuracy varying across pathology types, imaging modalities, and real world practice conditions, which is an unusually candid framing. Model architecture and per claim performance figures are not published in full.

Regulatory clearance plus published validation, with the caveat that most accessible evidence is company authored. The company reports validation studies demonstrating accuracy that meets or exceeds general dentist performance, cites clinical study accuracy rates above 90 percent for detection of caries, bone loss, and periapical lesions, and reports its platform and claims product in use by large dental groups and insurers covering more than 75 million Americans, which is substantial deployment scale. What is thinner is independent peer reviewed evaluation of the deployed product measuring effect on treatment decisions or patient outcomes rather than detection accuracy.

No published PHI handling or data governance disclosure was located. The platform processes dental radiographs, which are identifiable patient records, across both provider practices and insurer claims review, and data flowing between those two contexts is exactly the boundary a buyer should map before deployment.

No HIPAA or BAA statement was located in public materials. Business associate arrangements are structurally required for both the practice and payer product lines and certainly exist contractually, but nothing is published.

No SOC 2, HITRUST, or ISO 27001 attestation was located, and no trust center was found. As with other cleared device vendors in this index, FDA clearance addresses safety and effectiveness of the software as a medical device and says nothing about the vendor's information security posture.

Among the strongest regulatory positions in the index and the deepest in dentistry. The company received clearance in 2021 for bone level measurement in radiographs with periodontal disease, described as the first clearance of its kind, followed by a second clearance for caries detection and outlining, and it reports a total of seven FDA clearances spanning caries, calculus, bone level, and image enhancement. The company describes the platform explicitly as software as a medical device operating chairside. Buyers should still confirm which specific cleared claims their deployment covers, since clearances here are function by function rather than platform wide.

No formal governance program was located, but the company publishes unusually frank commentary acknowledging that dental AI accuracy varies significantly across pathology types, imaging modalities, and real world practice conditions, which is the substance a governance disclosure would be expected to address. What is absent is any published analysis of performance variation across patient demographics, sensor and imaging equipment types, or practice settings, all of which are plausible sources of drift for radiographic models.

Designed to sit inside existing dental workflow, connecting with existing imaging systems and dental practice management software so analysis appears on the radiograph during the exam rather than in a separate application. The company also operates on the payer side against submitted claims, which is a second and distinct integration surface. Named practice management integrations and standards support were not located, though the presence of the product as an embedded option inside third party dental practice management platforms indicates a working partner integration model.

No hosting, tenancy, or data residency disclosure was located. Real time chairside analysis implies cloud inference with practice side capture, but no infrastructure terms are published.

No published pricing for either the practice platform or the payer claims product. The dual sided commercial model, selling detection to providers and claims review to insurers, is disclosed in outline but the economics of neither side are public, and the potential tension in that arrangement is not addressed in published materials.

Single specialty by design, which is dentistry, and within it focused on two dimensional intraoral radiography, specifically bitewing and periapical images, covering caries, periodontal bone level, calculus, and periapical radiolucency. Buyer types span individual practices, large dental groups and DSOs, and dental insurers, with reported reach across more than 75 million covered Americans. Three dimensional imaging such as cone beam CT and non radiographic diagnosis are outside the described scope.