Industry — Food, Restaurants & Delivery
We build ordering, kitchen and delivery software for restaurants, cloud kitchens and delivery platforms. The real test is never the demo — it is the Friday dinner rush, when a dish sold out ten minutes ago, a courier has gone offline, and the tickets are stacking up at the pass.
Food, Restaurants & Delivery
Most food software problems are the same problem: the system and the kitchen disagree. A dish sold out twenty minutes ago and is still orderable. A price changed on the till but not in the app. A marketplace is serving a menu nobody has touched since spring. Each of those ends as a refund, a bad review, or a customer who does not come back.
Aryavos builds the ordering, kitchen and delivery layers around a single source of truth for menu, price, availability and allergen data, published to every channel you sell through — including the marketplaces you do not control. We design for the rush rather than the average: back-pressure when the queue grows, dispatch that copes with a courier dropping offline mid-route, and kitchen displays that stay readable when tickets stack up. Allergen and food-information data is treated as regulated content, versioned and attributable; which obligations are in scope is agreed per engagement.
What We Build
Work for restaurant groups, cloud kitchens, delivery platforms and food retailers — usually alongside a till you already run, an aggregator integration you did not choose, and a kitchen that cannot stop trading for a migration.
Customer ordering, courier and dispatch apps with live tracking, addresses that resolve to an actual doorway, and payment handling that does not charge twice when the network drops mid-checkout.
Orders, tables, menu control and kitchen display in one system, integrated with the till you already run instead of replacing it on a trading day.
Multi-brand operations out of one kitchen: order routing per brand, throttling when the queue gets long, and reporting that separates brands sharing a hob and a headcount.
Stock that decrements against recipes as orders land, with wastage, par levels and purchase ordering — so taking a dish off updates every channel instead of starting an argument at the pass.
Rewards, offers and one-tap reordering built on real order history, with promotion rules evaluated server-side so a discount cannot be stacked into a loss by anyone reading the app's traffic.
Demand forecasting for prep and rota planning, delivery estimates trained on your own history rather than a vendor default, and recommendations that respect live stock and allergen filters.
Engineering Stack
Swift
Kotlin
JavaScript
Python
Flutter
React Native
Laravel
Node.js
MySQL
MongoDB
Firebase
Redis
How We Work
The things that tend to decide whether a food platform survives its first proper rush — and the second service after something went wrong in the first.
Customer, kitchen, courier and back office are one system seen from four angles. We build them against one set of order states, so a driver, a chef and a support agent are never reading three different versions of the same order.
Price, availability, modifiers and allergens live in one catalogue and publish outward — to your app, your site, the in-store screens and the marketplaces. Without that, the menu drifts, and the first person to notice is a customer with an allergy.
Ordering flows that survive a distracted thumb on a bus, and kitchen screens legible from two metres away in a hot room with wet hands. Different problems, so they get different designs.
Traffic is not spread evenly. It arrives at lunch, again at dinner, and climbs when it rains. We design for that shape with queueing, back-pressure and caching, then load-test against your projected peak before you meet it live.
Tokenised card handling through your gateway, encryption in transit and at rest, and least-privilege access for staff accounts that turn over quickly. Which obligations apply — PCI-DSS scope, data protection, local food-information rules — is agreed at the start and designed in.
Incidents in this business happen at dinner, not at ten on a Tuesday morning. Cover, escalation and rollback steps are agreed against when you actually trade, and handover includes runbooks, documentation and infrastructure as code so a menu change never waits on us.
Key Features
Ordinary features. What makes them difficult is doing them alongside three hundred other people, against stock that is changing while the customer is still reading the menu.
Search that copes with misspellings and local dish names, filters that respect allergens and dietary needs, and results that stop offering what the kitchen has already run out of.
Cards, wallets and cash on delivery, with idempotent handling so a retried payment does not charge twice, and refunds — including partial ones — that reconcile against both the order and the day's takings.
Honest status through accepted, cooking, collected and delivered, with an ETA based on your kitchen's real prep times and the courier's actual position rather than a countdown that quietly resets.
Feedback separated by restaurant, dish and courier, so a slow delivery does not sink a kitchen's rating — with moderation and a response path for the operator.
Promotions with the rules evaluated server-side — eligibility, stacking limits, expiry and per-customer caps — because a discount bug at peak gets expensive in the time it takes anyone to notice.
Order updates, delivery alerts and marketing kept on separate consent tracks with rate limits, so someone who wants to know their food is close is not signed up to daily promotions.
Frequently Asked Questions
The problem, who it's for, and where you are now. That's enough for us to come back with something useful.
hello@aryavos.com
HQ
Noida, India & New York, USA
What happens after you send it
A developer reads it, not an auto-responder. Expect questions about scope and constraints first, then a suggested way to start.
