Mawaid · Pitch Deck
Hajj & Umrah · CATERING OPERATIONS
Mawaidموائد
The right meal, the right count, forecasted rather than guessed.
neuriya.ai — Sovereign, Arabic-first enterprise AI
Problem
Group catering kitchens still guess portions and average out allergies
- Kitchens serving pilgrim groups plan meal counts off a fixed per-package estimate, not the group's actual size, season, or past consumption pattern, so over-preparation is the default.
- Allergen and special-diet requests — nut, gluten, diabetic-friendly — are matched to menu items by hand on the day of service, with no systematic check before food goes out.
- Food waste is tracked, if at all, as a single end-of-season number, not per kitchen or per meal, so no one can see where the over-preparation is actually happening.
- Breakfast, lunch, dinner, and special-diet menus are managed on separate spreadsheets, so a supplier delay on one ingredient isn't visible until it's already a shortfall.
Solution
Meal counts and menus planned to a forecast, not a guess
Product
Mawaid in action
How it works
From first touch to outcome
Forecast
Each kitchen’s next meal demand is predicted from group size, history, and season.
Match diets
Allergen and special-diet requests are matched to available menu items automatically.
Prepare
Kitchens prepare to the forecast, not to a fixed estimate that’s usually wrong.
Measure waste
Actual consumption versus forecast feeds directly into next season’s planning.
Market
Sizing the opportunity
- TAM — $900M. MENA hospitality food-service & catering-tech market
- SAM — $95M. Saudi Hajj & Umrah hotel and group-catering technology market
- SOM — $7M. 3-year obtainable share via design-partner hotel and catering-operator pilots
Saudi Arabia serves tens of millions of meals across hotel and group kitchens each Hajj and Umrah season, and Vision 2030's hospitality-capacity expansion is pushing operators to cut food waste and cost per meal without cutting quality.
Business model
How Mawaid makes money
Per-kitchen forecasting subscription
Priced per active kitchen or catering site under forecast, tiered by meal volume.
Implementation & data-onboarding fee
One-time fee to bring existing consumption history into the forecast model.
Multi-site waste-analytics add-on
Premium reporting tier for multi-site operators comparing waste performance across kitchens.
Revenue streams
Where the revenue actually comes from
Competition
Where we win
Our edge
- Forecasts to the pilgrim season's own demand curve, not a generic restaurant seasonality model.
- Dietary and allergen matching is built into the forecast, not a manual checklist layered on top.
- Sovereign, PDPL-aligned hosting for operational and supplier data, built for Saudi hospitality operators from day one.
- Founding team combines Saudi hospitality-operations experience with applied-AI engineering.
Traction
Early validation, built for pilot readiness
- Full catering-operations product experience built end-to-end: demand forecast, dietary matching, waste tracking, and menu planning.
- Architecture pre-aligned to PDPL, NDMO Classification, and ISO 27001.
- Actively selecting design-partner hotels and catering operators for a first pilot cohort.
Go-to-market
Hotel kitchens first, then group-catering networks
- 1Land with 2-3 design-partner hotels or catering operators in Makkah and Madinah, starting with their highest-volume kitchens.
- 2Prove forecast accuracy and waste reduction over a single Hajj or Umrah season cycle.
- 3Expand through hotel-group and catering-association relationships to additional properties and seasons.
Team
Built by operators, not just builders
The ask
Raising a seed round to reach first hotel and catering pilots
We're raising to fund pilot deployments with design-partner hotels and catering operators, forecast-model tuning against real seasonal data, and the core team through first-revenue.