Diagnostics & imaging AI · Dental X-ray AI for practices and insurers
Overjet
Overjet is a dental AI company based in Boston, Massachusetts, whose FDA-cleared software reads and measures dental X-rays, with tools for imaging, visit notes, insurance checks and payer claim review.
Strong fit
- Dental service organizations that want one AI vendor for X-rays, notes and insurance work
- Practices that want FDA-cleared measurements of bone loss and decay to show patients
- Dental insurers that want AI to review claims against the X-rays
Weak fit
- Medical imaging teams, since Overjet reads only dental images
- Single dentists who want a low-cost X-ray add-on and nothing else
- Buyers who need a posted price
Bottom line
Overjet is a strong choice for dental groups that want FDA-cleared X-ray AI tied to charting, insurance checks and practice analytics. Its work with large insurers is a real advantage when claims slow down cash. Small offices should price it against simpler tools, and every buyer will need a quote.
Score breakdown
Weights: Outcomes 35% · Product 30% · Implementation 20% · Pricing clarity 15%.
Wardah Inam and Alexander Jelicich, both MIT graduates, founded Overjet in 2018. Inam is chief executive. The company is based in Boston and has raised about $133 million through its 2024 Series C, with the American Dental Association among its investors.
Overjet reads dental X-rays as they come into the practice and marks decay, bone loss, calculus and other findings, with bone levels measured in millimeters. It holds 10 FDA clearances, the latest in December 2025 for CBCT Assist, which labels and measures structures in 3D cone beam scans for implant and wisdom tooth planning.
Around the X-ray AI it has built IRIS, imaging software that can replace a practice's existing X-ray software, Voice, an ambient tool that writes visit notes and perio charts as the clinician talks, and Ivy, an AI insurance coordinator that checks benefits before visits and estimates what the patient will owe.
Overjet started by helping insurers review dental claims, and it still sells to payers. In 2024 it said its payer partners covered more than 120 million members, including most of the 10 largest US dental insurers. For a practice, that means the same AI is reading its X-rays on both sides of a claim.
Overjet does not post prices, and the full suite is more than a small office may need. Groups that want only X-ray detection should compare the price of that one module.
Pearl fits practices that want FDA-cleared AI for both 2D X-rays and 3D scans with insurance tools of its own. Videa fits dental groups that want detection, voice notes and claims tools from one vendor.
Competitor landscape
| Vendor | Overall | Ease of implementation |
|---|---|---|
| Overjet | 8.4 | 8.2 |
| Pearl | 8.1 | 7.9 |
| Videa | 7.8 | 8.1 |
Pricing
| Item | Detail |
|---|---|
| Model | Overjet sells its software by subscription to practices, dental groups and insurers, with modules priced by contract. |
| What usually drives cost | For Overjet, cost depends on the number of locations and providers, and on which modules you add, such as IRIS imaging, Voice or Ivy. |
| What to ask before you buy | Ask Overjet for a per-location price for each module, what moving from your current imaging software involves, and which practice management systems it connects to in your offices. |
| Published pricing | Overjet does not publish a price list. |
Leadership
Methodology
| Weight | Factor | What it measures |
|---|---|---|
| 35% | Customer outcomes | Whether buyers get measurable operational or clinical-workflow results after go-live |
| 30% | Product | Capability depth, reliability, and fit for the job the category buys |
| 20% | Implementation | How hard it is to stand up, integrate, train, and stabilize |
| 15% | Pricing clarity | Whether a buyer can model total cost without a mystery quote |
| Label | Meaning |
|---|---|
| Highly recommend | Strong outcomes and product with manageable caveats |
| Recommend | Solid fit for the right buyer; know the tradeoffs |
| Conditional | Only with a specific use case or heavy caveats |
| Not recommended | Avoid for most buyers in this category |
Read our full methodology for how we weight scores and assign recommend labels.