Build Custom AI for Your Healthcare Practice, Without In-House Costs
Hiring an AI agency offers faster deployment and access to specialized, pre-built HIPAA-compliant components. Building in-house requires recruiting expensive, specialized talent and a 6-12 month ramp-up time.
We recently built a patient intake system for a 15-person specialty clinic processing 500 new patients per month. Their front desk staff spent 20 minutes per patient manually transcribing PDF forms. We launched the new system in 4 weeks, cutting manual processing time to under 90 seconds per patient.
This comparison assumes the need for production-grade systems, not simple task connectors. For a healthcare practice, this means HIPAA compliance, audit trails for every automated action, and human review gates for sensitive decisions like medical billing code suggestions. These are engineering problems, not just workflow design problems.
What Problem Does This Solve?
The main obstacle to building in-house is hiring. An AI engineer with Python, cloud deployment, and HIPAA experience is a rare and expensive role. A 50-person clinic cannot compete with large tech company salaries, and the recruiting process alone can take 3-6 months. This represents a significant fixed cost and delay before any work begins.
Even with a generalist developer, the toolchain is a challenge. Every vendor in the data pipeline must sign a Business Associate Agreement (BAA) for HIPAA compliance, and many popular APIs do not offer BAAs on affordable plans. A developer might connect a web form to an EMR with a serverless function, but without deep security knowledge, they can easily misconfigure IAM roles or forget to encrypt environment variables, exposing Protected Health Information (PHI).
Finally, a new hire faces a steep learning curve. They must spend their first 3-6 months learning your clinic's specific workflows, your EMR's API quirks, and the nuances of your patient journey. This means the practice pays a full-time salary for half a year before seeing a return on the primary automation project.
How Does It Work?
We start with a 2-hour discovery session to map your exact patient intake or referral process. We architect the system using HIPAA-eligible AWS services. We use AWS Lambda for compute, S3 for document storage, and Supabase for the primary Postgres database, which signs a BAA. All data in transit and at rest is encrypted using AWS KMS.
For a patient intake workflow, we build a FastAPI endpoint on AWS Lambda that receives data from your web forms. Our Python code validates all fields, checks for correct patient ID formats, and uses the Claude API to extract structured data from free-text notes. This entire transaction completes in under 500ms and is logged to an immutable audit trail in a dedicated Supabase table.
The structured data is then formatted for your specific EMR or Practice Management System API. For critical decisions, like suggesting a medical billing code from clinician notes, the system requires human approval. We build a simple review interface on Vercel where a staff member must approve the suggestion before it is written to the EMR. This has reduced billing code errors from 8% to under 0.5% for past clients.
The complete infrastructure is defined with Terraform, allowing us to create a staging environment in minutes for testing. We configure CloudWatch alarms that send Slack notifications if API latency exceeds 1 second or the error rate rises above 1%. The average monthly AWS hosting cost for processing 1,000 patients is typically under $50.
What Are the Key Benefits?
Launch in 4 Weeks, Not 6 Months
Get a production-ready, HIPAA-compliant system live in one month. Avoid the long recruitment and ramp-up cycle of an in-house hire.
Fixed Project Cost, Not a Full-Time Salary
You pay a one-time fee for the build. No recurring six-figure salary, benefits, or equity costs associated with a full-time engineering hire.
You Own the Code and Infrastructure
We deploy to your AWS account and hand over the complete GitHub repository. You are not locked into a proprietary platform and can take over maintenance anytime.
Built-in Auditing and Alerting
Every automated action is logged for HIPAA audits. We configure CloudWatch alarms to notify you via Slack if performance degrades, ensuring uptime.
Direct EMR and PMS Integration
We build direct API connections to your existing healthcare software. Your staff works within their current tools, with no new dashboards to learn.
What Does the Process Look Like?
Week 1: Workflow & Systems Audit
You provide read-only access to relevant systems and walk us through the target process. We deliver a detailed technical specification and architecture diagram.
Weeks 2-3: Core System Development
We build the core automation logic and data models. You receive access to a private GitHub repository to track progress and a staging environment for early feedback.
Week 4: Integration and Deployment
We connect the system to your live EMR, run end-to-end tests, and deploy to production. You receive training for your team on any human-in-the-loop review steps.
Post-Launch: Monitoring & Handoff
We monitor the system for 30 days to ensure stability. You receive a full runbook with documentation, monitoring instructions, and an optional support plan.
Frequently Asked Questions
- How much does a custom AI project cost?
- Cost is scoped based on the number of systems to integrate and the complexity of the business logic. A patient intake system connecting a web form to one EMR is a 4-week project. A referral management system integrating with three external partner portals could take 8 weeks. We provide a fixed-price quote after our initial discovery call.
- What happens if an automation fails or the EMR API is down?
- The system is built with dead-letter queues on AWS SQS. If an API call fails after three retries, the failed request is moved to a queue for manual review. A Slack alert is sent with the error details. This ensures no patient data is ever lost and your team is notified immediately to handle the case manually.
- How is this different from using a healthcare-specific SaaS tool?
- SaaS tools provide a one-size-fits-all workflow that you must adapt to. We adapt the software to your exact process. This is critical for specialty clinics with non-standard patient journeys. You also own the code, so you're not subject to SaaS price increases or feature deprecation.
- How do you ensure HIPAA compliance?
- We only use HIPAA-eligible cloud services and sign a Business Associate Agreement (BAA) with you. All patient data (PHI) is encrypted at rest and in transit. We also build granular audit trails, logging which user or system accessed or modified any piece of patient data, which is crucial for compliance.
- Who is actually building the software?
- I, the founder of Syntora, personally write every line of code. There are no project managers or junior developers. The engineer you speak with on the discovery call is the same person who architects, builds, deploys, and supports your system. This ensures deep context and accountability.
- What do you need from us to get started?
- We need two things: a detailed walkthrough of the process you want to automate, and API access credentials for the relevant systems (e.g., your EMR, web form provider). We use secure methods for sharing credentials and de-identify any sample data used during development.
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