Automatic Notifications
Event-based notifications (kitchen, driver, customer) triggered by order status transitions and ETA changes. Delivered via WhatsApp using send_order_data_via_whatsapp_task, get_confirmed_message_to_user, get_on_delivery_message_to_user, and Slack for staff ops.
Solves
- Customers constantly ask for updates in my restaurant.
- Updates are inconsistent and depend on who is working in my restaurant.
- My staff spends too much time sending repetitive messages in my restaurant.
Customer Order Tracking
A simple tracking view for customers showing order status and ETA, reducing "where is my order?" messages. The Order model records customer_last_checked_at for each tracking page visit.
Solves
- I want better transparency for customers in my restaurant.
- Customers don't trust my delivery times in my restaurant.
- I get too many 'where is my order?' messages in my restaurant.
Dine-in Floorplan + Tables
A floorplan editor and table status board to manage dine-in orders and real-time table changes. Built on FloorPlan, FloorPlanConfig, FloorPlanElement (table/wall/bar element types), and Table with FSM status transitions (AVAILABLE → PENDING_ORDER → DINING → ASKED_FOR_CHECK).
Solves
- Dine-in orders get lost when the rush starts in my restaurant.
- I can't quickly see which tables are open or waiting in my restaurant.
- Combining or moving tables becomes confusing in my restaurant.
Driver Android App
A dedicated Android app for delivery drivers that integrates with the platform's Driver, DriverLocation, Route, and Stop models. Drivers receive their assigned orders and optimised routes, share live GPS location (feeding the War Room and customer tracking views via WebSocket), and can mark order statuses from the app. The app also lets drivers log expenses and stock purchases on the go — recording items, amounts, and receipts — which flow directly into the restaurant's cost and expense tracking. Authenticated with a private token scoped to the driver's organization.
Solves
- Drivers report expenses verbally or on paper and I lose track of them in my restaurant.
- I have no live GPS from my drivers unless they manually send their location in my restaurant.
- My drivers rely on WhatsApp messages and paper to know their orders and route in my restaurant.
- Driver stock purchases are not captured in real time and create accounting gaps in my restaurant.
Driver Live Tracking
Live driver location and ETA for operations, plus optional customer visibility. Uses Mapbox markers updated via WebSocket driver location events. Tied to Driver, DriverLocation, Route, and Stop models.
Solves
- I can't reliably estimate delivery times for customers in my restaurant.
- I don't know when drivers are about to become a bottleneck in my restaurant.
- I waste time asking my drivers where they are in my restaurant.
Driver WhatsApp Delivery Integration
A WhatsApp-assisted delivery workflow that eliminates the address lookup step. The customer sends their location pin via WhatsApp — the platform stores it in the database and attaches it to their active order, making it immediately visible in the War Room. Staff then selects the order and assigns a driver, transitioning the order to ON_DELIVERY. The assigned driver receives a WhatsApp message containing the customer's delivery address, order summary, and any special instructions. Built on top of the Conversation and Order models, using incoming message webhooks to detect location messages and surface them via Celery tasks and WebSocket events.
Solves
- Getting the customer's delivery address requires back-and-forth messages in my restaurant.
- Dispatching an order to a driver takes too many manual steps in my restaurant.
- Customer locations shared on WhatsApp are never saved and we ask for them again next time in my restaurant.
Drivers Traffic Light
A green/yellow/red/grey signal system showing driver readiness, risk, and delays at a glance. Calculated by get_driver_traffic_light_color() and OrderStatusTrafficLightV2, using time-in-status thresholds per order stage.
Solves
- Dispatching drivers feels chaotic and stressful in my restaurant.
- Late deliveries catch me by surprise in my restaurant.
- I don't know which driver is available right now in my restaurant.
Event Logs + Digest (What You Missed)
A structured event log and daily/shift digest that captures important operational signals: late orders, risk escalations, driver delays, downtime incidents, customer compliments, complaints, and key state transitions. Provides a "what you missed" feed inside War Room and optional WhatsApp/Slack summaries for owners who are off-site.
Solves
- I have no single timeline to audit what happened during a shift in my restaurant.
- Important events happen and I find out too late in my restaurant.
- Customer compliments get lost and don't reach the team in my restaurant.
Excel / CSV Report Export
One-click export of any key dataset to a formatted Excel (.xlsx) or CSV file — orders, sales summary, product performance, driver activity, loyalty transactions, customer list, and more. Reports support date-range filtering and can be triggered from the admin panel or via API. Designed for owners and managers who need to share data with accountants, run their own analysis in Excel, or keep offline records without requiring technical knowledge.
Solves
- My data is locked inside the platform and I can't analyse it the way I want in my restaurant.
- I build reports manually every week by copying data from different screens in my restaurant.
- I can't get my sales and order data out of the system to share with my accountant in my restaurant.
- I have no offline backup of my historical data in my restaurant.
Text-to-Speech Alerts for Kitchen
Automatic spoken announcements in the kitchen when a new order arrives or its status changes. Uses browser Web Speech API (or a TTS service) to read order summaries aloud so kitchen staff never miss an incoming order even when their eyes are off the screen.
Solves
- Kitchen staff miss incoming orders because they are not watching the screen in my restaurant.
- The kitchen is too noisy for visual-only notifications in my restaurant.
- Orders are delayed because kitchen prep doesn't start on time in my restaurant.
Linux Desktop Ops App (Printers + TTS + Audio Ducking)
A lightweight Linux desktop companion app for on-premise operations: manages thermal/network printers and kitchen text-to-speech alerts from a stable local process. Staff can play music from the app (or keep music in the browser), and when an important alert arrives the app automatically ducks/pauses audio, speaks the order/status update aloud, then resumes audio. Pairs with the platform via Public Token API + WebSocket for real-time events and supports per-station configuration (kitchen/bar/front desk).
Solves
- Kitchen alerts get missed when music or noise is louder than screen notifications in my restaurant.
- Setting up printers and alerts for multiple stations is too technical in my restaurant.
- Printing depends on a browser tab and sometimes fails during rush in my restaurant.
Live Cost Breakdown
Real-time cost and margin breakdown per product and per order. The CostReturn schema (ingredients_cost, profit_margin_percent, total_cost) is computed from Recipe.get_possible_cost() and reflected live on operating orders.
Solves
- My costs change and I can't keep pricing updated in my restaurant.
- I don't have live visibility into costs and waste in my restaurant.
- I don't know my true margins per order in my restaurant.
Loyalty Points Management
A fully customisable loyalty programme tied to customers' phone numbers — no app or account required. Points are earned automatically on every order (configurable exchange rate, e.g. 1 point per 15 MXN) and redeemed as a discount on future orders (configurable redemption value, e.g. 0.30 MXN per point). Owners can personalise the coin name and branding ("Sillys", "Estrellas", "Fichas"), set their own earn and redeem rates, and grant or deduct points manually. Customers check their balance and redeem points entirely via WhatsApp — no login needed. Built on LoyaltyCard + LoyaltyCardTransaction with transaction kinds: EARN_ORDER, REDEEM_ORDER, EARN/REDEEM_TRANSFER, EARN/REDEEM_ADMIN. Cards are linked to Lead by phone number and can be merged when duplicates are detected.
Solves
- I track loyalty points manually on paper or spreadsheets in my restaurant.
- My customers won't download another app just to collect loyalty points in my restaurant.
- Generic loyalty programmes don't match my brand or pricing in my restaurant.
- I have no way to reward repeat customers and keep them coming back in my restaurant.
Multi-Restaurant (Shared Recipes + Menu Variants)
Multi-restaurant management with shared base recipes and products across locations, while allowing each restaurant to publish different menus, prices, availability, and promos. Central recipe changes can propagate (optionally) to all restaurants, while each location keeps its own stock, vendors, and local overrides.
Solves
- Opening a new location requires copying recipes and setup manually in my restaurant.
- My locations drift apart and menus/costs become inconsistent in my restaurant.
- Each location needs small menu differences but I can't manage variants cleanly in my restaurant.
Multi-Stop Route Planner (Live ETA + One-Click Driver Dispatch)
A route planning workflow to assign a driver to one or more delivery stops with a live total travel-time estimate. The system optimizes stop order, shows total ETA impact in real time, and dispatches a single WhatsApp message to the driver containing every stop: customer name, pinned location/address, order summary, and special instructions. Supports batching and re-optimization when a new stop is added mid-route.
Solves
- Drivers miss customer details when there are multiple stops in my restaurant.
- Planning multiple deliveries for one driver is manual and error-prone in my restaurant.
- I can't see the real total ETA impact when adding another stop in my restaurant.
Orders Kanban Board
A drag-and-drop Kanban board that organises all active orders by status column (e.g. Received → Preparing → Ready → Delivered). Each card shows order summary, items, elapsed time, and channel (dine-in, delivery, takeaway). Status transitions update in real time via WebSocket events so every screen in the restaurant stays in sync without a refresh.
Solves
- I have no visual overview of order flow across my entire restaurant in my restaurant.
- Orders get forgotten between stations during busy service in my restaurant.
- I can't tell at a glance which orders are ready and which are still being prepared in my restaurant.
Orders Traffic Light (Risk + Delay Signals)
A red/yellow/green order risk indicator that flags which orders are late (red), at risk of becoming late (yellow), or on track (green). Uses time-in-status thresholds and ETA comparisons per order stage to proactively trigger staff actions (e.g., notify customer, prioritize kitchen, assign driver). Can feed War Room highlighting and automatic WhatsApp notifications.
Solves
- I only notice late orders when the customer complains in my restaurant.
- I can't tell which orders are at risk before they become late in my restaurant.
- My team doesn't know what to prioritize when everything is busy in my restaurant.
Organization Ops Configuration (Flows + Alert Priorities)
A high-control configuration center per organization to define how the restaurant operates: customer flows (WhatsApp → order → confirmation → delivery/dine-in), station responsibilities (kitchen/bar/front desk), and rules that drive automation. Owners can set alert priorities (critical/high/normal/low), escalation timers, and per-channel routing (screen, TTS, WhatsApp, Slack). Includes per-flow templates (confirmation, ETA, delay apology), thresholds for traffic-light risk, and role-based settings so each team member sees only what matters.
Solves
- We get too many alerts and can't tell what's urgent in my restaurant.
- When something is going wrong, there's no escalation rule and issues slip through in my restaurant.
- My restaurant workflow is unique but the system forces a generic flow in my restaurant.
- Alerts go to the wrong people or station and slow us down in my restaurant.
Public Token API + WebSocket
A token-based public API surface that lets external systems and customer-facing integrations interact with the platform without exposing private data or admin capabilities. Public tokens (Token.is_public=True) enforce scoped permissions — create-only, read-only, or create-or-read — via PublicTokenHasCreateOnly, PublicTokenHasReadOnly, and PublicTokenHasCreateOrReadOnly permission classes. Private operations remain protected by PrivateTokenOnly. WebSocket connections use the same token-based auth, enabling real-time event subscriptions (order status updates, driver location, loyalty balance) for customer-facing apps, digital menu boards, kiosks, or third-party integrations — all scoped strictly to the owning organization.
Solves
- I have no safe way to expose order status or menu data to my own customer app in my restaurant.
- I can't connect my platform to external apps or delivery aggregators in my restaurant.
- My kiosk or digital menu board can't receive live updates without polling in my restaurant.
Public Site Pinger (Uptime + Instant Alerts)
Automated uptime monitoring for the restaurant's public ordering site and key endpoints (menu, checkout, tracking). Runs periodic health checks and triggers instant alerts (WhatsApp/Slack) when downtime or high error rates are detected, with incident timestamps stored for reporting.
Solves
- I can't track incident history to see patterns and fix reliability in my restaurant.
- I have no instant alerts when critical systems fail in my restaurant.
- My ordering site can go down and I only find out after lost sales in my restaurant.
Recipe Graph Editor (Nested Recipes + Cost/Stock Precision)
A graph-based UI to edit recipes as nodes and ingredient links as edges. Supports nested recipes (a recipe can be used as an ingredient inside another recipe), with unit conversions, yield/merma, and per-edge cost attribution so owners can audit cost, stock impact, and budgeting at a granular level. Designed to prevent "mystery costs" by making every dependency visible and reusable.
Solves
- I reuse sauces and prep items but can't model nested recipes cleanly in my restaurant.
- Recipe costs are too complex to understand and I don't know where margins go in my restaurant.
- Stock and recipes drift apart and I can't trust inventory impact per menu item in my restaurant.
Mirror Sandbox Environment
A fully isolated mirror of a production organization used for demos, onboarding, and safe testing without touching real data. A sandbox org is created by cloning an existing organization via the clone-organization pipeline (CloneOrganizationSerializer + PipelineRun), which deep-copies menu, products, settings, and configuration. Sandbox orgs carry the is_sandbox flag (Organization.is_sandbox=True) and get their own dedicated WhatsApp channel (SourceOrDestinationType.SANDBOX) with an AI-powered auto-responder (SandboxAutoResponseHandler) that simulates customer, driver, and staff conversations using GPT prompts — letting teams explore every feature in a safe, realistic environment before going live.
Solves
- I can't demo the platform to new clients without risking real production data in my restaurant.
- I can't safely test new configurations or workflows before applying them in my restaurant.
- Training new staff on a live environment causes mistakes and confusion in my restaurant.
Tables Traffic Light (Dine-in Risk Signals)
A red/yellow/green signal system for table service: highlights tables that are waiting too long to order, waiting too long for food, or have asked for the check and are being delayed. Uses table FSM timestamps and station events to surface risk and keep dining room flow smooth.
Solves
- Dining room flow feels chaotic and hard to manage in my restaurant.
- Servers miss steps (order, follow-up, check) during rush in my restaurant.
- I don't notice tables waiting too long until they get upset in my restaurant.
Talk to Your Restaurant (AI Staff Assistant)
An AI-powered WhatsApp interface that lets staff query live restaurant data using natural language messages from their personal number. The system identifies the sender as staff based on their registered phone number and answers operational questions in real time by querying the platform: order counts and statuses, delayed or at-risk orders, open tables at a given time, daily expenses and purchases, driver locations, and more. Examples:
"How are the orders today?" → summary of active/completed/pending counts
"Do we have any delayed orders?" → list of orders past ETA with driver status
"Any open tables at 3pm?" → available tables from the floorplan
"How many expenses do we have today?" → total purchases and expenses for the day
No app required — staff just message the restaurant's WhatsApp number.
Solves
- Checking order or table status requires opening multiple screens in my restaurant.
- I can't check how my restaurant is doing when I'm not on site in my restaurant.
- My staff have to call me for basic operational information in my restaurant.
Ticket Printing (Customer, Kitchen, Bar)
Print formatted tickets to one or more destinations — customer receipt, kitchen prep ticket, or bar ticket — triggered automatically on order confirmation or manually on demand. Supports thermal printers via ESC/POS and network printing, with per-destination templates and item filtering (e.g. only drinks go to the bar printer).
Solves
- Customers ask for a receipt and I can't provide one quickly in my restaurant.
- My kitchen and bar rely on shouted orders and handwritten notes in my restaurant.
- Wrong items get prepared because the order details aren't in front of staff in my restaurant.
Unit Conversion Profiles (g↔ml, yield, density presets)
Configurable conversion profiles to standardize how ingredients convert across units (grams ↔ milliliters, pieces ↔ grams, tablespoons ↔ grams) using density presets and per-ingredient overrides. Profiles can be applied by supplier, recipe type, or prep station, ensuring consistent costing and inventory math across the whole restaurant.
Solves
- I don't know the correct density or conversion for key ingredients in my restaurant.
- Recipe math and conversions waste too much time in my restaurant.
- Everyone converts units differently and my costs come out inconsistent in my restaurant.
War Room (Live Ops Dashboard)
A real-time operations hub with a Kanban-style board and live status signals for kitchen and delivery. Powered by WebSocket events and the orders map view.
Solves
- I don't have a single live overview of what is happening in my restaurant.
- Orders fall through the cracks when things get busy in my restaurant.
- My team gets confused about what to do next in my restaurant.
WhatsApp AI Message Rewrite
AI-powered rewrite layer for outgoing WhatsApp messages. Staff type a quick informal draft — including shorthand directives like "yes | list menu categories" — and the AI reformulates it into a polished, on-brand reply addressed to the customer by name. Supports intent directives (e.g. "list menu categories", "confirm order", "give eta") that expand into context-aware structured responses pulling live data (menu categories, order status, ETA) from the system. Examples:
"hey broo, ys you order is rdy" → "Hello [Name], yes your order is ready! 🎉"
"yes | list menu categories" → "Yes [Name], here are our menu categories: Tacos · Drinks · Desserts"
Solves
- Every staff member replies differently and we have no consistent brand voice in my restaurant.
- Staff waste time looking up menu details to paste into WhatsApp replies in my restaurant.
- Writing proper replies takes too long when we are busy in my restaurant.
- My staff sends informal or typo-filled messages that look unprofessional in my restaurant.
WhatsApp Inbox (Customers + Staff)
A single place to manage WhatsApp conversations for customers and internal coordination, tied to orders. Built on WhatsappNumber and Conversation models with SourceOrDestinationType.WHATSAPP channel routing.
Solves
- Messages come in without order context and slow us down in my restaurant.
- I answer the same questions over and over on WhatsApp in my restaurant.
- My WhatsApp is a mess and I lose important messages in my restaurant.
WhatsApp Intent Analyzer
Every incoming WhatsApp message is automatically classified by intent in real time — complaint, compliment, order inquiry, cancellation request, menu question, etc. Intent data feeds a live dashboard with customer experience metrics (complaint rate, sentiment trend, top intent categories) and triggers instant alerts to staff when a complaint or urgent message is detected, so no negative experience goes unnoticed. Compliments are surfaced as positive signals and can be forwarded to the team as morale boosts 🎉. All classifications are stored per conversation for longitudinal CX reporting.
Solves
- I can't tell what customers complain about most in my restaurant.
- Customer complaints get buried in WhatsApp and I only find out too late in my restaurant.
- Positive feedback from customers disappears and never reaches my team in my restaurant.
- I have no data on how satisfied my customers are in my restaurant.
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