Hover converts mobile photos into interactive 3D property models, serving homeowners, contractors, and insurers. The stack reveals a company balancing multiple product surfaces: React Native + native iOS/Android for field capture, Three.js + babylon.js + WebGL for 3D visualization, and Salesforce + Braze for customer engagement and workflow automation. Active hiring skews heavily toward engineering (44% of roles), with projects spanning AI-assisted tooling, digital twin scaling, and React Native migration — suggesting investment in both platform depth and developer velocity.
Hover is a property-intelligence platform founded in 2011, headquartered in San Francisco. The company operates across three segments: a homeowner app for renovation design and measurement, a contractor mobile platform for estimates and project planning, and an insurance-sector solution automating inspections and claims workflows. Operationally, Hover has reached meaningful scale—over 300,000 contractors and 500,000 homeowners have used the platform to model billions of square feet of property. The business runs on a hybrid mobile-first architecture (React Native, native iOS/Android) backed by a classical SaaS stack (Salesforce, Snowflake, GCP).
Hover uses Three.js, babylon.js, and WebGL for 3D visualization, with React and Angular for web interfaces. Mobile capture runs on React Native, iOS, and Android, backed by GCP infrastructure, Kubernetes, and Terraform for deployment.
Key projects include scaling 3D reconstruction from sensor data, building digital twin models at commercial scale, human-in-the-loop workflows for claims automation, transitioning from React Native, and rebuilding revenue operations with AI. The company is also expanding contractor-facing experiences and custom integrations using AI coding assistants.
Hover'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.