Labor and inventory management software for restaurant chains
Altametrics builds back-office software for multi-unit restaurant operators, with deployments across major chains managing food and labor costs — typically 60%+ of operator margin. The tech stack reveals a sharp pivot: heavy investment in AI/ML (LangChain, RAG, Whisper, PyTorch, TensorFlow, Hugging Face) alongside mobile and enterprise systems (Kotlin, Java, Android SDK, Docker, Kubernetes), but no adopting or replacing signals suggest integration is still in progress. Active hiring across marketing, engineering, product, and executive roles (7 open) at an accelerating velocity indicates scaling beyond core back-office into new product lines.
Altametrics is a privately held enterprise software company founded in 1997, headquartered in Costa Mesa, CA, with 201–500 employees. The flagship product, Altametrics Enterprise Back Office (eRestaurant), consolidates labor management, inventory tracking, food cost control, and supply chain visibility for restaurant operators. The product suite also includes Xformity (business intelligence and reporting), Clock (time and attendance), and HubWorks (an app marketplace for smaller operators with 200 or fewer locations). The company sells to quick-service and casual-dining chains and generates value through labor and food cost reductions in the 2–6% range per operator.
Altametrics runs Python, Java, Kotlin on backend; Android SDK and web frontends; Docker and Kubernetes for orchestration; PostgreSQL-compatible databases (SQLite, Room); and integrates Payoneer, PayPal, QuickBooks, and NetSuite. Recent stack includes LangChain, RAG, PyTorch, TensorFlow, and OpenAI API for AI/ML features.
Active projects include POS equipment installation, inventory tracking implementation, mobile and web application development, MVP launches, B2B SaaS product expansion in restaurant tech, and production process management. The company is also running webinars and podcasts and leading restaurant industry initiatives.
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Altametrics'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.