Overjet Brings AI Into the Dental Front Office With Ivy
Overjet has introduced Ivy, an AI insurance coordinator built to help dental practices verify benefits, estimate patient costs, and reduce the administrative grind that often surrounds treatment planning. The product is designed to gather eligibility information, check coverage limits and exclusions, and surface payer responses in time for staff to explain likely out-of-pocket costs before care begins.
In dental offices, the financial conversation frequently lands before the clinical one is complete. A patient may understand the need for treatment but still hesitate when the estimate is unclear, incomplete, or built on outdated benefit data. Ivy is meant to narrow that gap by pulling together insurer responses, practice fee schedules, and the fine print that can alter what a family owes at checkout.
The workflow matters because front-desk and insurance teams spend large portions of the day chasing answers that should ideally be available earlier. When benefits are verified late, surprises tend to show up late as well: a missed frequency limit, an exclusion buried in the plan, or a deductible that changes the final bill. In that setting, the billing conversation stops being administrative and becomes a direct driver of patient trust.
Benefit Verification Moves Earlier in the Care Path
Ivy is built to gather eligibility and benefits ahead of appointments and on demand, then translate that data into a treatment estimate the team can use in real time. The system also checks remaining benefits, deductibles, and frequency limits, which are often the numbers that decide whether a quoted total is close to reality or far off base.
For dental practices, that kind of pre-treatment clarity has a practical effect. If a team can tell a patient what insurance is expected to cover before the procedure starts, the office is less likely to face awkward collection conversations after the fact. It also gives clinicians and staff a more stable foundation for discussing next steps, especially when patients are comparing treatment options or staging care over several visits.
Ivy’s payer-calling feature is intended to fill in the gaps when digital insurance sources do not provide enough detail. If a coverage question cannot be resolved through automated channels, the system can call insurers and document the findings for the team. In a field where missing information can change whether an estimate is usable, that fallback is not cosmetic; it is the difference between a number that guides care and one that forces another round of manual checking.
Administrative Time Reclaimed at the Practice Level
At Carolina Pines Dentistry, the insurance coordinator said Ivy saves a full week of work, or 32 hours, by replacing the old routine of logging into multiple payer websites one by one. The office described a shift from scattered verification tasks to a workflow that can cover both the current week and the next in a single day, freeing time for claims and patient statements.
That kind of time recovery is clinically relevant even though it sits outside the operatory. Dental practices operate on thin operational margins, and a jammed insurance queue can slow treatment starts, delay follow-up, and leave patients waiting for answers that should have been available much earlier. When the verification process becomes more efficient, staff can spend more time on the parts of care that are visible to patients: explanation, coordination, and follow-through.
A single sentence captures the operational consequence: fewer evenings spent on hold, fewer lunch breaks lost to insurer websites, and fewer estimates assembled under pressure.
Payment Clarity Before the Drill Starts
Overjet says Ivy combines benefit information with the practice’s fee schedule to create patient estimates before treatment begins. The estimate is accompanied by the details behind it, including remaining benefits and deductible information, so teams can explain the basis of the number instead of handing patients a blank or overly generic figure.
That structure matters because dental costs are often judged not just by the absolute price but by the uncertainty around it. Patients are more likely to accept a recommended procedure when they understand what insurance is expected to cover and what portion they are likely to pay themselves. For offices, better estimates can reduce the mismatch between expected and collected revenue at the time of service.
Signature Periodontics said it is collecting $100 to $200 more per day at each of its three locations with Ivy. The practice framed the gain as money that would otherwise need to be chased after the patient had already left the office. Even without broader utilization data, that detail signals the basic financial logic behind the product: clearer estimates can improve collection at the point of care and reduce the back-end scramble.
ReviewPASS Adds a Separate Payer Signal
Ivy also connects with participating payers through Overjet’s ReviewPASS. For eligible procedures, ReviewPASS provides real-time feedback on whether a claim can bypass manual clinical review. When that information is layered onto benefit data and fee information, the practice has a more complete picture of what to tell the patient before treatment.
The mechanism is straightforward but important. Manual review delays can make a treatment estimate feel provisional even when the underlying clinical plan is already set. If a payer signal suggests a procedure may move through without that extra step, the office can explain the likely financial path more confidently. ReviewPASS availability still varies by payer and procedure, and estimates or review results do not guarantee coverage or payment.
AI in Dentistry Is Expanding Beyond Imaging
Overjet has built its business around artificial intelligence for dental providers and insurers, with technology spanning dental imaging, clinical documentation, and insurance workflows. Ivy extends that footprint into the front office, where coverage verification and estimate generation are often as important to the patient experience as the clinical procedure itself.
The timing reflects a broader shift in dental operations. Practices are being asked to do more financial counseling, more documentation, and more insurance follow-up with limited staff. AI tools that can consistently gather payer data, document the missing pieces, and translate those findings into patient-facing estimates are likely to attract attention precisely because they work at a bottleneck that has long resisted cleaner workflow design.
At the same time, the limits remain explicit. A faster estimate is not a guarantee of payment, and a real-time payer response does not eliminate denials, benefit exclusions, or plan-specific quirks. The launch is built around reducing friction in the insurance process, not replacing the coverage rules that still govern the final bill. For dental teams, the immediate question is whether that friction can be cut enough to change the way treatment discussions begin and the way collections end.