Demand forecasting
Estimate customer traffic, dish demand and preparation quantities to support purchasing and menu planning.
Industry AI Agents
AI for everyday operating decisions
Our agents are practical food-service capabilities, not digital personalities. They combine field data, operating rules and domain knowledge to produce explainable, traceable recommendations.
RAG
Grounded in domain knowledge
Human review
People approve consequential actions
Audit trail
Trace recommendations and decisions
Star Kitchen AI
SK Group AI Operating Layer
Agent capabilities
From a forecast to an assigned action
Every agent should answer three questions: what changed, why it matters, and who should act next.
Inventory and waste
Flag unusual stock levels, approaching expiry and waste deviations so teams can act.
Food-safety checks
Combine operating procedures, inspection records and corrective-action status to highlight priority risks.
Performance reviews
Turn site performance, exceptions and meeting records into operational performance review actions.
Governance
Explainable. Reviewable. Under human control.
Food safety, cost and customer commitments require oversight. Product evaluation should cover confidence, evidence, permissions and human approval.
01
Data inputs
Work with menus, purchases, inventory, inspections, transactions and site procedures.
02
Model reasoning
Combine models with domain knowledge to generate forecasts, alerts and recommendations.
03
Human approval
Keep human judgment in decisions affecting payments, suppliers, food safety and customer commitments.
04
Traceability
Retain a record of recommendations, approvals, execution and review for the project.
Bring one real operating question.
Choose forecasting, inventory and waste, food-safety checks or performance reviews. We will prepare a scenario-based demonstration.