Build Custom AI to Analyze Your Dental Patient Data
A small dental practice can hire a solo AI consultant to build custom algorithms for patient data analysis. Syntora provides this service, delivering production-grade AI systems built by a hands-on engineer.
The complexity depends on your existing Practice Management Software (PMS) and the quality of your patient records. A practice with clean data in a modern system like Open Dental is a 2-week project. Integrating with older, on-premise systems with inconsistent charting requires a 4-week build.
We built a patient recall system for a 7-person dental office processing 500 charts a month. They were manually reviewing records to find candidates for hygiene appointments. We deployed an AI model that scans charts and flags high-priority patients, which went live in 3 weeks and reduced manual review time by 90%.
What Problem Does This Solve?
Most practices rely on the built-in reporting of their Practice Management Software, like Dentrix or Eaglesoft. These systems can generate static lists of patients overdue for a cleaning, but they cannot predict behavior. They cannot combine appointment history, proposed treatments, and insurance data to score a patient's likelihood to accept a high-value crown procedure.
A tech-savvy office manager might export data to a business intelligence tool like Tableau. This is useful for creating dashboards that show no-show rates over time, but it is a reactive analysis tool. It cannot actively flag a specific patient with an 85% no-show probability 48 hours before their appointment or write that risk score back into the patient's chart in Dentrix.
Off-the-shelf dental AI software often focuses on analyzing X-rays or providing generic patient communication bots. These tools do not offer custom algorithm development based on your practice's unique patient data and operational needs. They lock you into a predefined workflow that cannot adapt to how your specific practice identifies treatment opportunities or manages patient recall.
How Does It Work?
We start by establishing a secure, read-only connection to your Practice Management Software database, whether it's a cloud-based system like Open Dental or an on-premise SQL server. We extract 24 months of de-identified data: appointment history, completed treatments, and insurance records. For a typical practice, this is 10,000 to 50,000 patient records, which we process using Python with the pandas library for data structuring.
Next, we build a classification model using Python's scikit-learn library to predict key outcomes like no-show probability. We test several algorithms, but gradient-boosted trees (XGBoost) consistently perform best, identifying non-obvious patterns in patient behavior. The final model typically achieves over 90% accuracy in identifying patients who are most likely to miss an appointment, allowing for targeted follow-up.
The trained model is packaged into a FastAPI web service and deployed on AWS Lambda for efficient, serverless execution. This API connects to your PMS. A scheduled task runs nightly, scoring every patient with an appointment in the next 7 days. This entire process takes less than 5 minutes to run for a 15,000-patient database. The resulting score (e.g., 'No-Show Risk: 87%') is written back to a custom notes field in the patient's chart.
Your front-desk team sees this risk score directly inside the PMS interface they already use, requiring no new software. A daily summary is sent via a Slack alert listing the top 10 highest-risk appointments. This changes the confirmation call process from a 2-hour daily task of calling everyone to a targeted 20-minute effort. The ongoing AWS Lambda cost is typically under $15 per month.
What Are the Key Benefits?
Your Custom Model, Live in 4 Weeks
Go from initial data audit to a production-ready system integrated with your PMS in under one month. No lengthy enterprise sales cycles.
No Per-Seat SaaS Fees, Ever
A single fixed-price build and you own the code. After launch, you only pay for the underlying cloud hosting, typically under $20/month.
You Receive the Full Source Code
We deliver the complete Python codebase to your private GitHub repository. You are never locked into a vendor and can have any developer maintain it.
Runs Inside Your Existing Software
Scores and insights appear directly in your PMS (Dentrix, Open Dental, Eaglesoft). Your staff doesn't need to learn a new dashboard or login.
Proactive Alerts, Not Static Reports
The system automatically flags high-risk patients daily via a Slack or email alert. Your team acts on real-time insights, not stale monthly reports.
What Does the Process Look Like?
PMS Data Audit & Scoping (Week 1)
You provide secure, read-only access to your Practice Management Software database. We analyze 36 months of data history to confirm viability and deliver a fixed-price proposal.
Algorithm Development (Week 2)
We build and train the predictive model using your de-identified data. You receive a mid-project report showing the key predictive factors the model discovered.
Integration & Deployment (Week 3)
We deploy the AI model on AWS Lambda and build the integration to write data back into your PMS. Your team sees the first live scores in a test environment.
Monitoring & Handoff (Week 4+)
After a 2-week live monitoring period, we deliver the complete source code, system documentation, and a runbook. We then transition to an optional monthly support plan.
Frequently Asked Questions
- How much does a custom AI algorithm cost?
- A fixed-price build depends on the complexity of your PMS integration and the number of outcomes you want to predict (e.g., no-shows, treatment acceptance). Most projects for a single-location practice are completed in 3-4 weeks. After a 1-hour discovery call where we review your systems, we provide a detailed proposal with a firm price.
- What happens if the algorithm's predictions are wrong or it stops working?
- The system has built-in monitoring that alerts us via structlog if the API fails or if prediction accuracy drops. For the first 30 days post-launch, all fixes are included. Afterward, our flat monthly maintenance plan covers break-fix support with a 4-hour response time. The API is designed to fail silently, so it will never corrupt your core PMS data.
- How is this different from using an analyst on Upwork?
- An Upwork analyst can build a model in a Jupyter Notebook, but they rarely build and deploy production-grade software. We deliver a fully operational system: a version-controlled FastAPI application on AWS Lambda with structured logging, automated testing, and direct PMS integration. You get a maintainable asset, not a one-off analysis script.
- Is our patient data secure?
- Yes. We operate under a Business Associate Agreement (BAA) to ensure HIPAA compliance. All analysis is done on de-identified data where possible. The final system is deployed on your own cloud infrastructure (AWS account), meaning you retain full control over patient data access and storage. Syntora does not store your patient data after the build is complete.
- What if we switch our Practice Management Software later?
- Because you own the source code, the core prediction model is portable. Migrating to a new PMS would require a small, scoped project to rewrite the data extraction and write-back connectors. This is far simpler than starting from scratch. The Python model itself, trained on your patient behavior, remains valuable and can be plugged into the new system.
- Does our staff need technical skills to use this?
- No. The system is designed to be invisible. The outputs, like a 'No-Show Risk' score, appear as a simple note or custom field within the patient chart in the PMS software your team already uses every day. There are no new dashboards, logins, or applications for them to learn. The only new element is the daily summary alert they receive.
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