Clinical communication, provider scheduling and patient engagement software
PerfectServe sells cloud software that routes clinical messages and builds provider schedules for hospitals and medical practices. Job posts show a from-scratch data platform build, with ingestion from production systems and PHI-safe access controls. The stack pairs .NET/C# and SQL Server with Kubernetes, ArgoCD and Terraform, plus OpenAI, Anthropic and AWS Bedrock behind an AI-native answering service effort. Engineering and data roles lead an accelerating hiring push.
PerfectServe is a privately held healthcare technology company founded in 1997 and headquartered in Miami, Florida, with 201–500 employees. Its cloud-based platform covers clinical communication, provider and physician scheduling, answering services, and patient and family engagement. Messages are routed dynamically to the appropriate caregiver. The company serves more than 500 hospitals and 30,000 medical practices in the United States. Its product integrates with EHR systems including Epic, Cerner, Athenahealth and eClinicalWorks via FHIR.
PerfectServe runs .NET, C#, Python, SQL Server and React/React Native on AWS, with Terraform, Docker, Kubernetes, Helm and ArgoCD for infrastructure, and Salesforce, Pardot and Zendesk for go-to-market and support.
Yes. Its stack includes OpenAI, Anthropic and AWS Bedrock, and job posts describe adding AI to new and existing products, including an AI-native answering service platform.
PerfectServe's stack lists Epic Systems, Cerner, Athenahealth, eClinicalWorks and FHIR. Its job posts cover integrating hospital clinical systems and upgrading interface engines with failover.
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PerfectServe's technology stack, projects, and hiring signals are inferred from public hiring and company data — career pages, public listings, and company web presence — then clustered and de-duplicated. Figures are estimates that refresh over time. Read our full methodology →
This is not an official vendor or customer list. It is a technology-adoption signal inferred from public data, intended for B2B research.