Every day, restaurant operators make dozens of constrained decisions: how much to produce, how many people to staff, what to order, how to prevent stockouts without creating waste, and how to absorb demand peaks without degrading service.
The problem is not a lack of data. Restaurants already have information coming from POS systems, inventory tools, schedules, recipes, delivery platforms and finance systems.
The problem is that this data remains fragmented and underused for operational decisions. Praedixa was created to turn that data into concrete decisions.
Praedixa helps restaurant networks anticipate activity and improve operations with artificial intelligence.
Praedixa uses historical data, weather, events, seasonality, calendars and other operational signals to produce forecasts that field teams can actually use.
The goal is simple: reduce waste, limit stockouts, improve margins and save time for operations teams.
Most analytics tools produce dashboards. Praedixa is designed as an operational decision layer.
We do not only want to display data. We want to help teams arbitrate between food cost, team availability, service level, operational capacity, kitchen load and stockout or overproduction risk.
Our long-term vision is to build an AI operating system for restaurant networks, while keeping a concrete market entry point today: better demand and labor forecasting.
Praedixa starts with a precise, high-ROI problem: forecasting demand and labor needs.
The platform anticipates sales volumes across different horizons, from intraday to D+14 depending on available data, then turns those forecasts into operational recommendations.
Praedixa works on real problems faced by restaurants: demand peaks, limited visibility on volumes, overstaffing or understaffing, food waste, rush pressure and too many specialized tools.
Our ambition is to create a unified, AI-first platform that centralizes and uses the operational data of a restaurant network without replacing field expertise.
Praedixa combines machine learning, econometrics, time-series forecasting, constrained optimization and generative AI for analysis and operational assistance.
The architecture integrates with tools restaurants already use: POS, inventory, planning, ERP and delivery tools.
Praedixa is built in France with a strong focus on data sovereignty, AI transparency and decision traceability.
Praedixa was founded by a team combining data, engineering and go-to-market expertise.
Steven Poivre leads product vision and data science, Maël leads software engineering, and Baptiste Fondanèche supports go-to-market and business development.
Praedixa is supported by EuraTechnologies within the AI/Data ecosystem.