Home insurance platform for agents, backed by strong reinsurance partnerships
Orion180 is a homeowners insurance provider built to serve agents rather than direct consumers. The tech stack—Python, Power BI, Xactimate, GIS, plus cloud across AWS/Azure/GCP—reflects a data-and-modeling-driven operation; active projects in catastrophe modeling, predictive time-series models, and pricing tools confirm they're building quantitative depth. Hiring is accelerating across product, engineering, and data (22 roles combined), while pain points around claims processing, catastrophe response, and model-to-production integration signal they're scaling internal automation and risk infrastructure.
Notable leadership hires: Creative Director, Technology Director
Orion180 sells homeowners and specialty insurance (including flood) to licensed agents, who then distribute policies to homeowners. Founded in 2017 and based in Melbourne, Florida, the company operates in the 201–500 employee range with over $285 million in revenue. The reinsurance model relies on partners rated A- or better by A.M. Best, providing claims-paying stability across catastrophe events. The product and technology roadmap centers on modernizing agency onboarding, improving pricing and reserving accuracy, and scaling claims-processing capability—areas where manual processes and legacy systems remain pain points.
Orion180's stack includes Python, Power BI, AWS, Azure, GCP, Xactimate (claims), GIS (catastrophe modeling), HubSpot (CRM), Zendesk (support), and SQL Server / Azure Cosmos DB for data. They use ASP.NET Core and Vue/React for application layers.
Orion180 is developing reproducible data pipelines, predictive and time-series models, next-generation pricing tools, catastrophe modeling integration, and an SEC reporting function. Pain points in claims processing and catastrophe response suggest infrastructure modernization is a priority.
Orion180'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.