Clinical trial platform connecting sponsors and research sites globally
Florence operates a clinical trial management platform serving 600+ sponsors and 65,000+ connected research sites across 90+ countries. The tech stack—Salesforce, Snowflake, dbt, Kafka, PostgreSQL—reflects a data-first architecture for managing distributed trial workflows at scale. Current hiring velocity is accelerating with a senior-heavy mix across engineering and product, while the project roadmap shows heavy investment in AI-powered features and internal operations automation, paired with explicit work on AI safety (hallucination prevention, prompt injection guards), suggesting a controlled rollout of AI rather than broad experimentation.
Florence provides a cloud-based platform designed to streamline clinical trial management from sponsor and site perspectives. The product handles workflows across study execution, regulatory compliance (21 CFR Part 11, eTMF), remote monitoring, and real-time trial visibility. The customer base includes academic medical centers, cancer centers, and large CRO sponsors running trials globally. The platform is data-heavy, processing trial data across multiple geographies and regulatory jurisdictions, which aligns with the engineering emphasis on Kafka-based streaming, Snowflake data warehousing, and dbt transformation. Founded in 2014 and headquartered in Atlanta, the company operates as a privately held firm with 201–500 employees.
Salesforce, Snowflake, dbt, Kafka, PostgreSQL, MongoDB, Tableau, Python, AWS (Lambda, API Gateway, Step Functions), New Relic, Zendesk, Postman, and Terraform. The stack reflects a cloud-native, data-pipeline-heavy architecture.
More than 65,000 connected study sites across 600+ sponsors in 90+ countries, per the company's stated network.
Florence Healthcare'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.