E-prescribing and insurance verification platform for healthcare providers
DoseSpot operates a healthcare transaction platform spanning e-prescribing, insurance verification, and revenue cycle management. The tech stack reveals a hybrid Java + .NET backend (Spring, JPA, JDBC) running on AWS with Azure DevOps, complemented by Python and C++ for specialized workloads, all connected via FHIR and HL7 healthcare standards. Recent adopts of OpenAI and LLaMA signal a pivot toward AI-assisted operations—reflected in active projects around AI-driven data platform enhancement and operations automation—while the hiring mix leans senior (4 of 8 roles) across engineering, sales, and support, suggesting both technical depth and go-to-market pressure.
DoseSpot delivers e-prescribing, insurance verification, and revenue cycle management tools to healthcare providers, health plans, pharmacies, and EHR vendors. The platform processes hundreds of millions of healthcare transactions annually, connecting patients, prescribers, payers, and pharmacies to reduce costs and clinician burnout. Headquartered in Boston and founded in 2009, the company operates a 51–200-person organization focused on expanding market reach within tier-1 U.S. health systems and addressing operational pain points around prescription accuracy, medication access, and service reliability. A subsidiary, pVerify, handles additional insurance verification workflows within the same ecosystem.
Java (Spring, Spring Boot, JPA, JDBC), .NET, Python, C++, AWS, Azure, Docker, Terraform, Salesforce, ServiceNow, Zendesk. Healthcare-specific: FHIR, HL7. Monitoring: Datadog. AI: OpenAI, LLaMA, LangChain, LlamaIndex.
Boston, Massachusetts. Founded in 2009, the company is privately held with 51–200 employees and currently hiring only in the United States.
DoseSpot'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.