

Step 1 — Discovery Call (Day 0)
We spend 30 minutes understanding your practice — call volume, scheduling patterns, existing software, and which problems cost you the most time and money. We identify your highest ROI starting point and build a custom deployment plan before the call ends.
Step 2 — Custom Build (Days 1-3)
We build your AI system inside our HIPAA-compliant platform. We train it on your specific FAQs, services, insurance accepted, hours, and how you want calls handled. Nothing goes live until it performs the way you'd want your best employee to perform.
Step 3 — Review and Approval (Days 3-4)
We walk you through the complete system before anything goes live. You test it as a patient would. We adjust until every scenario feels right. You have final approval on every word the AI says.
Step 4 — Go Live (Days 4-5)
Your AI goes live on your existing phone number or a new dedicated number — your choice. We monitor the first 48 hours in real time and make adjustments based on actual call patterns.
Step 5 — Monthly Optimization
Every month you receive a performance report: calls handled, appointments booked, patients reactivated, hours saved, revenue recovered. Most practices see meaningful improvement between months 1 and 3 as the AI learns your patient population's patterns.
A patient who just received a difficult diagnosis. A family dealing with a medical emergency. An upset patient who has been wronged. The AI detects emotional escalation and transfers immediately to your team with a full call summary. We don't attempt to handle these with AI, and we never will.
Anything requiring clinical judgment goes to your clinical staff. The AI handles administrative functions only. It never discusses treatment, diagnosis, or clinical recommendations.
If a patient asks specifically for Dr. Martinez or the person who helped them last time, the AI recognizes the request and routes accordingly. Personal relationships stay personal.
Your AI gets better over time. The first week is good. Month three is significantly better. Month six is where most practices say they can't imagine going back. We set this expectation clearly because practices that understand the learning curve stay.
Your AI agent sounds natural and professional. Many practices choose transparency — "You've reached the automated scheduling line for "[Your Practice Name]" — which patients increasingly expect and appreciate. Others use a branded AI persona with a name. We build it either way.
The AI transfers immediately with a full summary of the call already prepared for your team member. Your staff member picks up knowing exactly who they're talking to, why they called, and what was discussed. They never start from zero.
No. We integrate with your existing practice management system — Dentrix, Eaglesoft, Athenahealth, eClinicalWorks, and others. You keep everything you already use.
Starter and Growth are month-to-month. Cancel with 30 days notice. No penalty, no pressure. We keep clients by delivering results, not by trapping them in contracts.
Most practices recover their setup fee within 30 days through recovered appointments and reactivated patients. The Starter package typically generates $1,200-$1,800 per week in recovered revenue for a practice missing 35% of its inbound calls.
There isn't one. The tiers exist because different practices have different starting points and risk tolerances. The upgrade path is yours to drive based on results you can see. We don't pressure upgrades. Our monthly performance reports make the ROI case better than any sales conversation could.
Because it doesn't exist honestly. Any company telling you their AI handles 100% of cases is either lying or hasn't deployed in a real practice yet. We tell you exactly what the AI handles, what it transfers, and why — so you can make a decision based on reality. The 3-5% of calls that require human judgment are exactly the calls your team should be taking. We give them back the time to take them well.
Helping dental and medical practices across Arizona recover missed revenue and give their teams back their time — with AI.
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