
Madison, Wisconsin, United States
US-based healthcare technology company that provides an interoperability platform for healthcare organizations
- Revenue
- $181M
- Customers
- 200
- Year founded
- 2014
- Funding
- $147M
- Team size
- 224
- Growth
- 11.52%
As of May 2026, there are 24 SaaS companies in Healthcare Integration Engines. They have combined revenues of $464M and employ 2.2K people. They have raised $428.8M and serve 40M customers combined.
Healthcare Integration Engines are specialized software solutions designed to facilitate the seamless exchange, integration, and management of healthcare data across various systems and platforms. They serve critical functions in enhancing interoperability among diverse healthcare applications, enabling secure communication, data sharing, and efficient processing. These engines play a vital role in ensuring that different healthcare IT systems, such as Electronic Health Records (EHRs) and laboratory information systems, can communicate effectively, ultimately improving patient care and operational efficiency. Use cases for Healthcare Integration Engines include the integration of billing and scheduling systems, clinical decision support, and the processing of health data from multiple sources. Typical features of these engines may include support for health data standards (e.g., HL7, FHIR), data transformation, real-time monitoring, and user-friendly interfaces for configuration. Common buyer personas for these solutions often include IT professionals within healthcare organizations, data analysts, and clinical operations managers who need to ensure that key health information flows smoothly across systems while maintaining compliance with regulatory requirements.
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Showing 10 of 2 companies ranked by annual revenue.

Madison, Wisconsin, United States
US-based healthcare technology company that provides an interoperability platform for healthcare organizations

Beijing, China
LinkDoc Technology Limited is a leading oncology big data company, providing healthcare big data and AI solutions in oncology and precision medicine, including medical big data integration and continuous patient care.
- Must facilitate data integration and interoperability between multiple healthcare systems - Should support industry-standard protocols such as HL7 and FHIR - Must enable real-time data processing and communication - Should include data transformation and mapping capabilities - Must offer robust user interfaces for system configuration and monitoring - Not just for data storage; must also ensure data accessibility and flow across platforms
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