Data platform unifying health plan data for analytics and AI
Abacus Insights builds a payer-focused data platform that ingests healthcare data via HL7 v2 and FHIR and models it on Databricks, Snowflake, Spark, Airflow and dbt across AWS, Azure and GCP. MCP and RAG in the stack point to AI-agent workloads on top of clean payer data. Hiring leans heavily toward data roles at manager-and-above levels, matching active work on client implementations and CMS interoperability.
Abacus Insights, founded in 2017 and headquartered in Boston, Massachusetts, provides a data platform for health insurers and payers. The platform consolidates fragmented payer data into infrastructure for analytics, reporting and AI use cases. Focus areas include risk adjustment, CMS interoperability, clinical data, payment integrity and HEDIS/Stars quality improvement. The privately held company has 201–500 employees and hires in the United States and Nepal.
Abacus Insights uses AWS, Azure and GCP with Databricks, Snowflake, Apache Spark, Airflow, dbt, Airbyte and Kubernetes, plus HL7 and FHIR for healthcare data and MCP and RAG for AI work.
Yes, hiring is accelerating, concentrated in data roles with some sales coverage, mostly at manager, director and senior levels, in the United States and Nepal.
Current work includes client implementations, migrating data onto a new platform, regulatory compliance, CMS interoperability workflows, clinical data integration and broader analytics reporting.
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Abacus Insights'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.