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Deployed on AWS
connecthealth.ai is an AI-first EHR integration platform and interface engine for EMR data exchange. Securely connect Epic, Cerner, wearables, and MedTech IoT using Agentic AI, FHIR, and HL7 in your own AWS VPC.
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Overview
connecthealth.ai: AI First Healthcare Interoperability Platform (formerly EHRConnect)
connecthealth.ai is a secure AI first healthcare interoperability platform and EHR integration engine designed to accelerate connectivity across diverse healthcare ecosystems. It simplifies EHR integration with systems including Epic Cerner Athena Allscripts and custom EMRs, as well as wearables, MedTech devices, medical IoT, laboratories, payers, and claims systems without requiring custom code.
The platform deploys as a containerized solution entirely within the customers AWS environment ensuring data sovereignty. Protected health information (PHI) remains isolated within the customers virtual private cloud (VPC) supporting HIPAA compliance with no external data sharing.
AI First and Agentic Capabilities
connecthealth.ai includes built in Agentic AI features that support:
Automated routing transformation enrichment and anomaly detection for Interface Engine workflows AI assisted data mapping and validation for HL7 v2, FHIR, C-CDA, and X12 Deduplication and normalization across clinical, MedTech, and device datasets Automated remediation workflows for failed messages and real time alerts Real time streaming and webhook based integrations Connect Anything in Healthcare
connecthealth.ai supports integration across a wide wide range of healthcare data sources including:
EHRs and EMRs such as Epic Cerner Athena Allscripts and legacy hospital systems Wearables, RPM hubs, and MedTech sensors (Digital Health IoT) Laboratories (LIS), radiology (RIS/PACS), pharmacies, and Health Information Exchanges (HIE) Payers and third party administrators (TPA) using X12 and API based integrations Core Capabilities
Visual No-Code workflow builder with more than 150 healthcare specific components Unified Authentication that handles OAuth and SMART on FHIR flows for major EHRs Built in transformations for FHIR, HL7 v2, C-CDA, X12, and DICOM Real time dashboards alerts retries and webhook triggers Rapid deployment via AWS CloudFormation templates (Infrastructure as Code) Why Teams Choose connecthealth.ai
Runs fully inside the customers AWS VPC for maximum security Reduces integration effort compared to traditional legacy interface engines Enables teams to configure workflows without deep HL7 or integration expertise Scales efficiently from small Digital Health pilots to enterprise level data volumes Security and Compliance
Deployed entirely within the customers AWS VPC (Single Tenant) HIPAA aligned architecture with encryption in transit and at rest Comprehensive audit logging of PHI access and data lineage Role based access control (RBAC) and least privilege design Data sovereignty where health data never leaves the customers control Pricing and Deployment
Plans are tiered based on the number of active integration connections ranging from Starter to Enterprise. All plans include access to all workflow components and standard support. Deployment is automated via AWS CloudFormation allowing customers to launch the solution in minutes.
Highlights
- Visual Zero-Code Healthcare Integration Platform connecthealth.ai provides a visual interoperability platform with pre-built connectors for systems like Epic, Cerner, and Athenahealth. Teams build workflows using a drag and drop interface with over 150 healthcare specific components. The platform runs entirely within the customers AWS account and supports HIPAA ready architectures without requiring custom code or external data sharing.
- Secure AWS Native Deployment connecthealth.ai deploys fully within the customer's AWS environment via CloudFormation. It is designed for HIPAA-aligned deployment, including encryption in transit and at rest, audit logging, and role-based access controls. This architecture enables organizations to meet security and compliance requirements while retaining full ownership and sovereignty of their data.
- Reduce Integration Effort and Complexity: connecthealth.ai reduces integration effort compared to traditional custom development. Pre-built healthcare workflow components and reusable templates accelerate implementation for common use cases, such as appointments, patient records, and clinical data exchange. Visual debugging and monitoring simplify troubleshooting, allowing a single platform to replace multiple point-to-point integrations.
Details
Delivery method
Supported services
Delivery option
ConnectHealth: Agentic AI & EHR Integration Platform
EHRConnect - Secure No-Code EHR Integration (Container Image)
Latest version
Operating system
Linux
Deployed on AWS
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Pricing
Pricing is based on the duration and terms of your contract with the vendor. This entitles you to a specified quantity of use for the contract duration. If you choose not to renew or replace your contract before it ends, access to these entitlements will expire.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Description | Cost/month |
|---|---|---|
One-Time Setup Fee | Required one-time fee for platform provisioning, AWS infrastructure deployment, and initial configuration. Purchase once before activating any monthly subscription tier. Available through private offer only. | $25,000.00 |
ConnectHealth - Up to 3 Active Integrations | Connect Up to 3 healthcare organizations (hospitals, clinics, or health systems) with your application. Full platform access with workflow engine, SMART on FHIR, HL7v2, and HIPAA-compliant infrastructure. | $6,000.00 |
ConnectHealth - 1 Active Integration | Connect 1 healthcare organization (hospital, clinic, or health system) with your application. Full platform access with workflow engine, SMART on FHIR, HL7v2, and HIPAA-compliant infrastructure. | $2,000.00 |
ConnectHealth - Up to 5 Active Integrations | Connect Up to 5 healthcare organizations (hospitals, clinics, or health systems) with your application. Full platform access with workflow engine, SMART on FHIR, HL7v2, and HIPAA-compliant infrastructure. | $8,000.00 |
ConnectHealth - Up to 10 Active Integrations | Connect Up to 10 healthcare organizations (hospitals, clinics, or health systems) with your application. Full platform access with workflow engine, SMART on FHIR, HL7v2, and HIPAA-compliant infrastructure. | $12,000.00 |
ConnectHealth - Up to 100 Active Integrations | Connect Up to 100 healthcare organizations (hospitals, clinics, or health systems) with your application. Full platform access with workflow engine, SMART on FHIR, HL7v2, and HIPAA-compliant infrastructure. | $90,000.00 |
Vendor refund policy
No refunds, except where required by law.
Custom pricing options
Request a private offer to receive a custom quote.
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Delivery details
ConnectHealth: Agentic AI & EHR Integration Platform
Supported services: Learn more
- Amazon ECS
- Amazon ECS Anywhere
Container image
Containers are lightweight, portable execution environments that wrap server application software in a filesystem that includes everything it needs to run. Container applications run on supported container runtimes and orchestration services, such as Amazon Elastic Container Service (Amazon ECS) or Amazon Elastic Kubernetes Service (Amazon EKS). Both eliminate the need for you to install and operate your own container orchestration software by managing and scheduling containers on a scalable cluster of virtual machines.
Version release notes
The Agentic Intelligence Update Release Date: December 8, 2024 Version: 0.3.5
We are proud to announce the release of ConnectHealth v0.3.5, a transformative update that brings true Agentic AI capabilities to healthcare interoperability. This release fundamentally changes how integration engineers build data pipelines, moving beyond static mapping to intelligent, adaptive workflows capable of reasoning, decision-making, and autonomous error remediation.
Headline Feature: Enterprise Agentic AI Engine ConnectHealth v0.3.5 introduces a suite of native AI nodes designed specifically for clinical data workflows. These are not simple wrappers; they are fully integrated agents capable of executing tools, maintaining state, and strictly adhering to HIPAA-compliant guardrails.
- Multi-Provider AI Model Support We have decoupled the AI engine from specific providers, giving you the flexibility to choose the best model for your clinical use case.
AWS Bedrock Native: Full support for Anthropic Claude (3.5 Sonnet, 3 Opus), Amazon Nova, and Meta Llama 3 via secure IAM role-based authentication. Google Cloud Vertex AI: Enterprise-grade access to Gemini 1.5 Pro and Flash models using service account integration. OpenRouter Integration: Access to a broad spectrum of models (GPT-4o, Mistral, DeepSeek) via a unified API for rapid prototyping. 2. The New Agentic Node Suite Your palette now includes powerful new tools for building intelligent systems:
AI Agent Node (ai-agent): The central brain that orchestrates reasoning, tool selection, and natural language processing. AI Tool Adapter (ai-tool-adapter): Turn any subflow into an executable tool. The Agent can now "call" your custom logic -- whether it is a database lookup, a FHIR query, or a specialized transformation -- on demand. Contextual Memory (ai-memory): Stateful conversation management (File-based or In-Memory) allows agents to "remember" context across multi-turn interactions, crucial for complex clinical reasoning. Guardrails & Termination (ai-tool-output): Built-in PII redaction and content filtering ensure that AI-generated outputs meet strict compliance standards before leaving the workflow. Architectural Improvements Unified Service Architecture We have refactored the underlying service layer to implement a robust AIProviderFactory pattern. This ensures:
Consistent Behavior: Uniform error handling and token management across all AI providers. Rapid Extensibility: New models and providers can be added without core system updates. Centralized Credential Management: Secure, encrypted storage for all API keys and service tokens. Enhanced Function Calling Full support for "Tool Use" (Function Calling) on AWS Bedrock and Vertex AI allows the AI to output structured JSON commands instead of just text, enabling deterministic automation of healthcare tasks.
Technical Changes & Upgrades Package Updates Upgraded @aws-sdk/client-bedrock-runtime to v3.700.0 for latest model support. Upgraded @google-cloud/vertexai to v1.7.0. New Administrative Endpoints GET /bedrock-models: A new centralized endpoint that dynamically lists available Bedrock models based on your region, simplifying configuration. Impact on Workflows With v0.3.5, you can now build workflows that were previously impossible:
Intelligent Routing: An agent analyzes incoming HL7 messages and determines the correct destination based on clinical content, not just header data. Automated Remediation: If a message fails validation, an agent can analyze the error, call a "Code Lookup" tool, correct the segment, and retry automatically. Clinical Summarization: securely pass patient context to a Gemini or Claude model to generate longitudinal summaries for care coordination. ConnectHealth (formerly EHRConnect) continues to lead the industry in secure, zero-code healthcare integration. Update your container images today to access these powerful new capabilities.
Additional details
Usage instructions
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SUBSCRIBE Subscribe to ConnectHealth from AWS Marketplace and review the terms.
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DEPLOY Launch the CloudFormation stack using the Quick Launch option. Stack creation typically takes 15 to 20 minutes to provision all ECS and networking resources.
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ACCESS APPLICATION After deployment open the AWS CloudFormation console: Select your new stack and go to the Outputs tab. Note the following values: ServiceUrlHttps : This is your application URL DefaultUsername : Your initial admin username DefaultPassword : Your initial admin password
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LOG IN Open the ServiceUrlHttps link in your web browser. Log in with the DefaultUsername and DefaultPassword. IMPORTANT: You must change the default password immediately from the Admin Portal details page.
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CONFIGURE INTEGRATIONS In the Admin Portal go to Settings then Integrations. Select Add New Integration. Choose your EHR system (Epic, Cerner, Athena or Sandbox). Enter the Client ID and Client Secret provided by your EHR vendor. Select Sandbox or Production environment. Test and save the connection.
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CREATE WORKFLOWS Navigate to the Workflows section. Click Create New Workflow and enter a name. Select the integration you configured. Choose a trigger: schedule, webhook or manual. Use the drag and drop builder to add logic and healthcare components. Save and deploy the workflow.
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TEST WORKFLOWS Run in test mode to validate workflow behavior. Check logs in CloudWatch to confirm successful execution. Enable production mode once validated.
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MONITORING CloudWatch Logs: Check /ecs/ehrconnect-TaskLogs for container logs. Health Check Endpoint: https://[your-domain]/api/healthCheck SNS Alerts: Subscribe your email to the SNSTopicArn found in CloudFormation Outputs to receive notifications for errors and system events.
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TROUBLESHOOTING If you cannot access the application verify the stack status shows CREATE_COMPLETE in CloudFormation and check security group rules allow port 443. If an integration fails confirm your Client ID and Secret are correct and verify EHR vendor network access. If a workflow does not execute confirm it is active and the integration is healthy.
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NEXT STEPS Change the default admin password. Configure at least one Health System integration. Create and test a workflow with sandbox data. Subscribe to SNS alerts for ongoing monitoring. Review CloudWatch logs to understand system behavior.
SUPPORT For deployment issues review the CloudFormation Events tab. For runtime issues review CloudWatch logs and metrics. For product help contact support through the AWS Marketplace support link.
Support
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Customer reviews
reviewer2767398
Has reduced integration time significantly and allows faster onboarding through visual workflows and pre-built templates
Reviewed on Oct 17, 2025
Review from a verified AWS customer
What is our primary use case?
I am using EHRConnect to integrate our healthcare application with multiple EHR systems.
How has it helped my organization?
EHRConnect cut our EHR integration development time from six months to two weeks per hospital. Our small development team can now handle multiple hospital integrations simultaneously using the pre-built workflow templates. This accelerated our go-to-market significantly.
What is most valuable?
The most valuable features include the visual workflow builder, which allows non-developers to understand and modify integrations. The agentic workflow library provides pre-built templates for common scenarios such as patient data synchronization, which saved weeks of development. Smart on FHIR and HL7 support enables compatibility with both modern and legacy EHR systems.
What needs improvement?
There could be more documentation for advanced customization scenarios. Additional pre-built workflows for specialty-specific use cases such as cardiology and oncology would be helpful. Better real-time debugging tools for troubleshooting live integrations would be beneficial. In the next release, features like a built-in HL7 message simulator for testing, more granular audit logging, and workflow version control with rollback capability are expected.
Which solution did I use previously and why did I switch?
We evaluated building custom integrations in-house. We switched because maintaining separate codebases for Epic, Cerner, and athenahealth was unsustainable. EHRConnect's unified platform reduced our technical debt.
What's my experience with pricing, setup cost, and licensing?
It is important to factor in the setup fee upfront. The monthly tier pricing is fair. We are on the $8,000/month tier, which allows up to five integrations and is still 60% cheaper than maintaining custom integrations with dedicated engineers. I calculate ROI based on developer time saved.
Which other solutions did I evaluate?
We evaluated building custom integrations in-house. EHRConnect's unified platform reduced our technical debt. We also looked at Redox and Mirth Connect. We chose EHRConnect for its better AWS integration, as we are already on AWS , a more modern visual workflow builder, and ready-made templates instead of starting from scratch.
What other advice do I have?
EHRConnect is great for healthtech startups or hospitals needing multi-EHR connectivity. The support team is responsive. Setup took two weeks, including AWS infrastructure provisioning. I recommend starting with one to two hospital pilots before scaling up.
Which deployment model are you using for this solution?
Public Cloud
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Amazon Web Services (AWS)
reviewer2765211
Has streamlined Epic integrations and accelerated patient data exchange
Reviewed on Oct 15, 2025
Review from a verified AWS customer
What is our primary use case?
I use EHRConnect to integrate our healthtech platform with Epic using the SMART on FHIR framework. It handles secure authentication, patient data exchange, and clinical workflow automation.
How has it helped my organization?
EHRConnect helped us connect with Epic faster and with less engineering effort. What used to take weeks for setup and testing now takes just a few days. It has made our Epic integrations smoother and more reliable.
What is most valuable?
The built-in SMART on FHIR and OAuth support for Epic, ready-to-use FHIR APIs for patient, observation, and encounter data, and the easy-to-deploy sandbox environment for quick validation are highly valuable. The complex HL7v2 transformers built in have also simplified interoperability for our healthtech applications.
What needs improvement?
A visual dashboard for API monitoring and better error handling during data syncs would make it even more developer-friendly.
For how long have I used the solution?
I have used the solution for 6 months.
Which solution did I use previously and why did I switch?
We previously used custom Epic FHIR integrations but moved to EHRConnect for its ready architecture, scalability, and faster go-live process.
What's my experience with pricing, setup cost, and licensing?
The setup cost was fair considering the time saved on Epic certification and integration maintenance. It is ideal for healthtech companies building Epic-connected apps. Other competitors were five times more expensive and also charged a huge amount for custom implementation.
Which other solutions did I evaluate?
We considered Redox but found EHRConnect simpler, more cost-effective, more flexible, and better suited for our cloud-native setup.
What other advice do I have?
EHRConnect has been a great enabler for our interoperability needs with Epic. It has helped our product team focus more on care workflows rather than complex integrations.