Nory builds an AI-driven operations platform for restaurants, combining sales forecasting, labour scheduling, and inventory optimization. The stack—Python, React, FastAPI, Postgres, Snowflake, dbt, Claude—reflects a modern ML-first architecture designed to handle time-series prediction and operational complexity. The hiring mix skews heavily toward engineering and data (22 of 45 roles), with senior-level dominance, suggesting they're scaling the core forecasting engine and data infrastructure to handle multi-region demand.
Notable leadership hires: Engineering Lead
Nory is a London-based restaurant management platform that uses machine learning to forecast sales, optimize labour scheduling, and reduce inventory waste. The product targets independent and small-chain restaurants where thin margins and manual operational friction (spreadsheets, printouts, fragmented scheduling) drive poor cost control. The company runs a data-intensive operation: sales forecasting requires time-series ML, labour planning involves constraint optimization, and inventory tracking demands real-time tracking. Active projects span labour forecasting, intelligent scheduling, payroll integration, and margin-critical ML systems. The platform is expanding internationally across Ireland, the UK, US, and Spain.
Nory's stack includes Python and FastAPI for backend services, React and TypeScript for frontend, PostgreSQL and MongoDB for data storage, Snowflake for analytics, dbt for data transformation, and AWS infrastructure (Fargate, ECS, RDS, SQS, Aurora). The company recently adopted Claude for AI reasoning tasks.
Nory is actively recruiting across the United Kingdom, Ireland, United States, and Spain, reflecting geographic expansion beyond its London headquarters.
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