Property management OS for multifamily apartment communities
Entrata operates a single-login platform for apartment complex management across 20,000+ communities. The tech stack reveals active AI/ML adoption (SageMaker, Bedrock, RAG, LangGraph) layered atop a mature backend (TypeScript, Java, Python, AWS), while hiring velocity is heavily weighted toward VP-level sales roles (17 of 32 open positions) — indicating aggressive expansion into new regional markets. Pain points center on support efficiency, compliance scaling, and customer acquisition, which align with the sales and operations focus.
Entrata provides comprehensive property management software for multifamily residential operators. The platform consolidates resident portals, online rent payments, lease signing, accounting, and community management into a single interface, with an open API enabling third-party integrations. Operating since 2003, the company serves more than 20,000 apartment communities across the United States and is headquartered in Lehi, UT. Current organizational priorities reflect both growth (regional account expansion, cross-selling initiatives) and operational maturity (SOC 2, PCI DSS 4.0, ISO 27001 compliance; vendor risk reviews; internal process documentation).
Entrata runs on TypeScript, Java, Python, and NestJS on AWS infrastructure (ECS, Lambda, SageMaker). The stack includes machine learning tools (Bedrock, RAG, LangGraph), enterprise resource planning (NetSuite), and data processing (Hadoop, Apache Spark).
Entrata is headquartered in Lehi, UT and currently hiring in the United States and Netherlands across sales, support, operations, legal, and executive functions.
Entrata'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.