How to Evaluate Dental AI Vendors Without Wasting Six Months

I've watched practices spend six months evaluating dental AI vendors and end up exactly where they started — paralyzed by options, skeptical of every claim, and no closer to a decision. It doesn't have to work that way.

Here's how to run a vendor evaluation that produces an actual answer in 30 days.

Start With the Problem, Not the Vendor

The biggest mistake in dental AI evaluation is starting with a vendor demo before you've defined the problem you're solving. Demos are designed to impress. If you walk in without a specific gap you're trying to close, you'll walk out impressed by everything and no closer to a decision.

Write down one sentence: *The specific problem I'm trying to solve is _____.* It might be "we're missing findings on radiographs that affect treatment acceptance," or "our front desk is overwhelmed and patients can't get through," or "our collections per visit are flat despite growing production." Each of those problems maps to a different category of tool.

Don't try to solve everything at once. Start with your highest-impact gap.

Filter by PMS Integration First

Before you evaluate anything else, ask every vendor one question: *What version of [your PMS] do you currently integrate with, and what does the integration actually do?*

Not "do you integrate with Dentrix" — that question gets a yes from everyone. The specific version and the specific data flow matters. A bidirectional integration that writes back to the patient record is fundamentally different from a read-only connection that just pulls appointment data.

If a vendor can't answer this question specifically and quickly, that's a flag.

Talk to Three References, Not Testimonials

Every vendor will send you a case study. Ask for three references instead — practices similar to yours in size and PMS — and actually call them. Ask one question: *What would you do differently if you were implementing this again?*

That question surfaces the real friction: what the onboarding actually looked like, what the support response time is when something breaks, how long it took the team to actually adopt it. Testimonials don't contain that information. References do.

Run a Paid Pilot, Not a Free Trial

Free trials are almost always too short and too shallow to tell you anything useful. A 14-day free trial of diagnostic AI will show you what the interface looks like. It won't tell you whether your hygienists will actually use it in six months.

Ask vendors for a 60–90 day paid pilot with a defined success metric. Something like: "We'll measure case acceptance rate at 90 days against our 90-day baseline." Two things happen when you frame it this way: vendors who aren't confident in their ROI will push back, which is useful information, and you get real data instead of a demo environment.

The Contract Questions That Matter

Before you sign anything:

Data ownership: Who owns your patient data? What happens to it when you cancel? Can the vendor use your data to train their models?

Integration SLA: What's the contractual uptime commitment for the integration? What's the remedy if it breaks?

Exit terms: How long is the contract? What's the cancellation process? Month-to-month vs. annual matters a lot if the tool doesn't work.

Price lock: Is the pricing fixed for the contract term, or can they raise rates on renewal?

These aren't adversarial questions. Any vendor worth working with will answer them directly.

30 Days Is Enough

Week one: define the problem, shortlist three vendors by category and PMS fit. Week two: demos with pre-written questions, reference calls. Week three: pilot terms negotiated with top choice. Week four: contract signed, implementation scheduled.

The practices that run tight evaluations don't just move faster — they end up with better implementations, because they went in knowing exactly what they needed.