Build Custom AI Automation for Your Clinic's Intake and Scheduling

Small clinics often rely on their EMR's built-in tools or services like Phreesia or SimplePractice. These platforms work for standard text-based online forms but fail with scanned documents or PDFs from referrals. An admin still has to manually transcribe data from a faxed patient history or a PDF attached to an email. The automation stops the moment a non-standard document arrives.

Consider a 5-person pediatric clinic that receives 10 new patient referrals a day via fax and secure email. The office manager prints each 4-page packet, manually types patient demographics, insurance info, and medical history into their EMR. This 15-minute process per patient consumes over 2 hours of admin time daily and is prone to data entry errors that cause billing denials later.

The structural problem is that off-the-shelf tools are built for structured data from web forms. They lack the Optical Character Recognition (OCR) and Natural Language Processing (NLP) capabilities to understand a scanned PDF. Their scheduling logic is often rigid, unable to handle complex rules like "Dr. Smith only sees new immunology patients on Tuesdays after 1 PM." They are designed for one workflow, not the messy reality of a multi-source intake process.

The first step is an audit of your current intake sources and EMR. Syntora would map every document type you receive (faxes, PDFs, online forms) and analyze your EMR's integration capabilities, whether it is a modern API or requires a different connection method. You receive a technical plan detailing the data extraction logic and scheduling rules before any code is written.

The system would be a HIPAA-compliant pipeline on AWS Lambda. Scanned documents would be processed by an OCR engine, and the extracted text would be parsed by the Claude API to structure information like name, date of birth, and insurance provider ID. This structured JSON data is then passed to a FastAPI service that validates the information and connects to your EMR to create the patient record. A 3-week build cycle is typical for this phase.

The delivered system exposes a secure email address or folder where your staff can drop new patient files. Within 60 seconds, a new patient record appears in the EMR and an appointment is scheduled. The system includes a human-in-the-loop review queue for low-confidence extractions, ensuring 100% accuracy. You receive the full source code, a runbook, and a Business Associate Agreement (BAA) for HIPAA compliance.