1. Executive Summary

This document defines the comprehensive scope of work for the design, development, and implementation of the Snac Ecosystem - a unified, scalable, and API-driven food-tech platform serving both B2B restaurant partners and B2C end-users through three integrated product lines, all powered by a single, shared backend.

1.1 Core Components

Component	Description	Development Scope
Snac Workspace	Central B2B SaaS platform providing restaurants with comprehensive operational tools	Frontend & Backend
Plateaway	White-label direct-ordering platform enabling restaurants to launch branded, custom-domain ordering websites	Frontend & Backend
Snac Application	B2C food discovery and ordering application powered by conversational AI	Backend Only
Web Scraping Engine	Data aggregation system for collecting restaurant information from multiple third-party platforms	Backend / Data Pipeline

1.2 Timeline Overview

Component	Duration	Team Size	Status
Snac Workspace (B2B)	18-20 Weeks	14 members	Included
Plateaway (White-Label)	20-22 Weeks	15 members	Included
Snac Backend (B2C)	16 Weeks	11 members	Included
Web Scraping Engine	TBD	TBD	Scope Defined
Parallel Execution	22 Weeks	-	Combined

1.3 Core Architectural Principle

The entire ecosystem is built upon a “headless” architecture, utilizing a microservices-first backend as its central foundation. This shared infrastructure ensures data consistency, scalability, maintainability, and code reusability.

2. Snac Workspace (B2B Platform)

Timeline: 18-20 Weeks

2.1 Overview

Snac Workspace is a comprehensive restaurant management platform designed to function as a virtual CMO, menu analyst, operations team, and growth manager in one unified interface. Every interaction is powered by AI, with modular tools that restaurants can activate based on their needs.

Development Scope: Frontend & Backend Development Required

2.2 Module Development Summary

No.	Module	Duration	Third-Party Integrations	Status
1	Card Builder Tool	3 Weeks	OpenAI / Gemini	Build
2	B2B AI Setup Assistant	4 Weeks	OpenAI / Gemini, Google Places API	Build
3	Ordering Tool Management	6 Weeks	POS APIs	Build
4	Table Booking Tool	3 Weeks	Google Calendar API
Twilio SMS and Email APIs	Build
5	Loyalty Tool Management	4 Weeks	Integrate Pre-Built Tool	Integration Only
6	WiFi Marketing Tool	2 Weeks	Pre-built WiFi Portal Integration
Automated follow-up campaign config module needs to be developed.	Integration + Development
7	Sponsored Listing Tool	4 Weeks	Own Platform
Third Party Platforms - Meta / Google	Build
8	Analytics Tool	6 Weeks	Snowplow -> S3 -> dbt -> Redshift, Looker/Metabase	Build
9	FudoPay Integration	3 Weeks	Payments Integration as Loyalty Wallet
Current Scope - Stripe
Future Scope - Revolut	Build
10	Inventory & Reorder Tool	4 Weeks	Multiple Supplier APIs	Build
11	Review & Feedback Tool	3 Weeks	Google Reviews API
OpenAI / Gemini API for Sentiment Analysis	Build
12	AI Growth Manager	4 Weeks	OpenAI / Gemini LLM + Analytics APIs	Build
13	AI Workers Integration	4 Weeks	OpenAI, Gemini LLM APIs	Build
14	Virtual Bites	6 Weeks	OpenAI, Gemini LLM APIs	Build

2.3 Core Workspace Tools - Detailed Scope

2.3.1 Card Builder Tool

Purpose: Create rich, high-performing restaurant listing cards for discovery

Restaurant profile management (name, logo, tagline, location)
Visual content builder (images, videos, tags)
Menu highlights and CTA configuration
SEO metadata optimization
Real-time visibility scoring and AI suggestions
Public preview and testing modes

2.3.2 B2B AI Setup Assistant

Purpose: Onboard non-restaurant food businesses (suppliers, wholesalers, equipment providers)

AI-guided onboarding interview
Automated business profile and card creation
Product/service upload and categorization
Marketing setup and sponsored listing activation
Performance insights and visibility reports

2.3.3 Ordering Tool Management

Purpose: Configure and manage direct ordering capabilities

Menu management and synchronization
Order processing and fulfillment tracking
Payment integration and transaction management
Customer data and analytics dashboard
AI-driven upselling and cross-selling configuration

2.3.4 Table Booking Tool

Purpose: Manage reservations and table availability

Real-time availability calendar management
Booking rules and constraints configuration
Integration with third-party booking systems
Guest management and history tracking
Automated confirmation and reminder system

2.3.5 Loyalty Tool Management

Third Party Integration, Documentation Needed

2.3.6 WiFi Marketing Tool

Third Party Integration
Automated follow - up campaign config needs to be developed here.

2.3.7 Sponsored Listing Tool

Purpose: Manage paid visibility and advertising campaigns

Keyword and targeting configuration
Budget management and bidding controls
Campaign performance tracking and optimization
Creative asset management
ROI analytics and reporting

2.3.8 Analytics Tool

Purpose: Comprehensive business intelligence and insights

Multi-dimensional performance dashboards
Search visibility and conversion analytics
Customer behavior and demographics analysis
Revenue attribution and forecasting
Competitive benchmarking and market insights

2.3.9 FudoPay Integration

Purpose: Payment processing and financial management

Payment method configuration and management
Transaction tracking and reconciliation
Payout management and reporting
Promotional campaign financial tracking
Revenue analytics and forecasting

2.3.10 Inventory & Reorder Tool

Purpose: Stock management and supplier coordination

Real-time inventory tracking and alerts
Automated reorder suggestions and processing
Supplier management and price comparison
Menu item availability synchronization
Waste tracking and cost optimization

2.3.11 Review & Feedback Tool

Purpose: Reputation management and customer feedback analysis

Multi-channel feedback collection and aggregation
Response management and escalation workflows
Sentiment analysis and trend identification
Review-driven operational improvement suggestions
Public reputation monitoring and management

2.3.12 AI Growth Manager

Purpose: Automated business optimization recommendations

Performance analysis and opportunity identification
Actionable growth recommendation engine
One-click implementation for supported actions
ROI tracking for implemented suggestions
Custom goal setting and progress monitoring

2.3.13 Virtual Bites

Purpose: AI-powered restaurant technology discovery and personalized tech-stack recommendations.

Centralized marketplace for restaurant technology solutions
Product pages with descriptions, pricing, and enquiry options
Sponsored listings and PPC-based provider promotion
AI engine that recommends the ideal tech stack for each restaurant
Provider analytics for views, clicks, and engagement

2.4 AI Workers Integration

Backend Automation Engine providing embedded AI services:

Menu enhancement and optimization
Automated upselling/cross-selling logic
Smart marketing suggestions based on trends/weather
Content and copy generation
Review analysis and improvement recommendations
Personalized customer engagement

Operation Modes:

Automatic Push: AI implementations happen automatically
Manual Approval: AI suggestions require restaurant owner approval

2.5 Team Structure - Snac Workspace

Role	Count	Notes
Project Manager	1	Requirements, timelines, UAT
Frontend Developers	4	UI for 13+ modules
Backend Developers	4	Workflows, APIs, integrations
UI/UX Designer	1	Design system and module interfaces
AI Integration Developer	1	OpenAI/Gemini orchestration
QA Engineers	2	End-to-end testing
DevOps Engineer	1	Deployments, infra, staging

Total Team Size: 14 members Total Timeline: 18-20 Weeks

2.6 Completion Status

Module	Status	% Complete	Notes
Card Builder Tool	Not Started	0%	-
B2B AI Setup Assistant	Not Started	0%	-
Ordering Tool Management	Not Started	0%	-
Table Booking Tool	Not Started	0%	-
Loyalty Tool Management	Not Started	0%	-
WiFi Marketing Tool	In Progress	0%	Done, needs integration
Sponsored Listing Tool	Not Started	0%	-
Analytics Tool	Not Started	0%	-
FudoPay Integration	Not Started	0%	-
Inventory & Reorder Tool	Not Started	0%	-
Review & Feedback Tool	Not Started	0%	-
AI Growth Manager	Not Started	0%	-
AI Workers Integration	Not Started	0%	-
Social Media Marketing Tool	Complete	100%	Done

3. Plateaway (White-Label Platform)

Timeline: 20-22 Weeks

3.1 Overview

Plateaway is a white-label direct ordering platform that enables restaurants to create fully branded online ordering websites hosted on their own custom domains. It provides complete control over customer experience, branding, customer data, and profit margins.

Development Scope: Frontend & Backend Development Required

3.2 Module Development Summary

No	Module	Duration	Third-Party Integrations	Status
1	Branded Website Setup (Multi-tenant)	4 Weeks	CloudFront, S3, Domain Registrar APIs	Build
2	Menu Management System	4 Weeks	POS APIs, Google Places	Build
3	Advanced Ordering & Checkout	5 Weeks		Build
4	Social Media Ordering Integration	3 Weeks	Instagram API, WhatsApp Cloud API, FB Graph API	Integration
5	Advanced Upselling & Cross-Selling (AI)	3 Weeks	OpenAI / Gemini, Recommendation Engine	Build
6	Integrated Marketing & CRM	-		Done
7	Real-Time Order & Delivery Tracking	4 Weeks	Google Maps API, Delivery partner APIs	Build
8	Multi-Outlet Management	3 Weeks	Google Maps, POS APIs	Build
9	Dynamic Menu Management	3 Weeks	POS Sync APIs	Build
10	POS System Integration	6 Weeks	Toast, Square, Clover, custom POS APIs	Build
11	QR Code Ordering & Payment	2 Weeks	Current Scope - Stripe
Extended Scope - Revolut	Build
12	Comprehensive Analytics & Reporting	5 Weeks	Snowplow, dbt, Metabase/Looker	Build
13	Flexible Payment Options	2 Weeks	Stripe, Razorpay, PayPal, Apple Pay	Build
14	Customer Feedback Mechanism	3 Weeks	Google Reviews API, WhatsApp API	Build
15	Automated Promotion Management	3 Weeks	Mailchimp, Firebase, OpenAI (AI copy)	Build
16	Multi-Language & Currency Support	3 Weeks	i18n libraries, CurrencyAPI.com	Build
17	Customer Support Integration	3 Weeks	Zendesk API, Twilio Chat	Build
18	Last Mile Delivery Partner Integrations	4 Weeks	UberDirect, Deliveroo Signature, etc	Build
19	AI Workers Integration	3 Weeks	Python FastAPI workers, LLM APIs	Build

3.3 Core Features - Detailed Scope

3.3.1 Branded Website Setup

Multi-tenant Architecture: Custom domains/subdomains per restaurant
Brand Customization: Colors, logos, fonts, layout options
Responsive Design: Mobile-first, cross-platform compatibility
SEO Optimization: Schema markup, metadata management, sitemap generation
About Restaurant Page + Story: Additional page they should be allowed to add where they can their story or about page

Synchronization: Real-time sync with restaurant portal or POS systems
Content Management: Item names, prices, images, tags, allergens, gifs and videos for the products as well.
Availability Control: Stock-based and time-based item availability
Multi-Menu Support: Delivery, pickup, dine-in, catering menus

3.3.3 Advanced Ordering & Checkout

Shopping Cart: Full cart management with modifications
Customization: Item modifiers, special instructions, dietary preferences
Payment Integration: Multiple payment methods including FudoPay wallet
Order Tracking: Real-time status updates and delivery tracking

Multi-Platform Ordering: Instagram, WhatsApp, Facebook Messenger integration
Social Commerce: Direct ordering through social media platforms
Content Sharing: Order sharing and social proof features

3.3.5 Advanced Upselling & Cross-Selling

AI-powered intelligent product suggestions
Dynamic bundling with automatic combo and package creation
Contextual offers based on time and behavior

3.3.6 Integrated Marketing & CRM

Customer Segmentation: Advanced audience targeting
Multi-Channel Campaigns: Email, SMS, WhatsApp marketing
Automation: Re-engagement and retention workflows
Performance Tracking: Campaign analytics and ROI measurement

3.3.7 Real-Time Order & Delivery Tracking

Live Updates: Order status from preparation to delivery
Delivery Integration: Third-party delivery partner coordination
Customer Communication: Automated notifications and updates

3.3.8 Multi-Outlet Management

Centralized Control: Unified management across multiple locations
Location-Specific: Customized menus and pricing per outlet
Consolidated Analytics: Cross-location performance insights

Multi-Menu Types: Service-specific menu configurations
Scheduling: Time-based menu switching and availability
Event Management: Special occasion and promotional menus

3.3.10 POS System Integration

Bidirectional Sync: Order and inventory synchronization
Real-Time Updates: Live menu and pricing updates
Consolidated Reporting: Unified sales and operational data
Integration of multiple platforms including aggregators (Uber Eats, Deliveroo)

3.3.11 QR Code Ordering & Payment

Contactless Ordering: In-venue QR code functionality
Self-Service: Direct device ordering and payment
Table Management: Integration with table service workflows

3.3.12 Comprehensive Analytics & Reporting

Performance Dashboards: Sales, customer behavior, operational metrics
Custom Reports: Configurable reporting and data export
Predictive Analytics: Forecasting and trend analysis

3.3.13 Flexible Payment Options

Multi-Method Support: Cards, digital wallets, cash options
Regional Adaptation: Local payment method integration
Security Compliance: PCI-DSS and regional payment standards

3.3.14 Customer Feedback Mechanism

Review Collection: Post-purchase feedback automation
Sentiment Analysis: AI-powered feedback categorization
Response Management: Automated and manual response workflows

3.3.15 Automated Promotion Management

Campaign Creation: Discount codes, limited-time offers, bundle deals
Dynamic Pricing: Time-based and demand-driven pricing
Performance Optimization: AI-driven promotion effectiveness analysis

3.3.16 Multi-Language & Currency Support

Localization: Multiple language interface support
Currency Management: Multi-currency pricing and payment processing
Regional Compliance: Local tax and regulatory requirements

3.3.17 Customer Support Integration

Live Support: Real-time chat and help center integration
Self-Service: FAQ and knowledge base functionality
Escalation Management: Support ticket routing and resolution

3.3.18 Last Mile Delivery Partners Integrations

Stuart, Orkestro, Uber Direct, Deliveroo Signature and so on.
Integrate Multiple Delivery Options for Restaurants to Choose from.

3.4 AI Workers Integration (Backend Automation)

Automated Restaurant Operations:

Menu enhancement and optimization
Intelligent upselling and cross-selling
Smart marketing campaign suggestions
Automated content and copy generation
Loyalty campaign optimization
Review analysis and operational insights
Personalized customer engagement
Data synchronization and trigger management

3.5 Team Structure - Plateaway

Role	Count	Notes
Project Manager	1	Requirements, timelines, UAT
Frontend Developers	4	17 modules, multi-tenant website builder
Backend Developers	4	Ordering, menus, payments, POS integrations
UI/UX Designer	1	Design system and templates
AI Integration Developer	1	Prompt engineering & orchestration
QA Engineers	3	Complex flows (ordering, payments, POS)
DevOps Engineer	1	Multi-tenant hosting, CI/CD, load testing

Total Team Size: 15 members Total Timeline: 20-22 Weeks

3.6 Completion Status

Module	Status	% Complete	Notes
Branded Website Setup (Multi-tenant)	Not Started	0%	-
Menu Management System	Not Started	0%	-
Advanced Ordering & Checkout	Not Started	0%	-
Social Media Ordering Integration	Not Started	0%	-
Advanced Upselling & Cross-Selling (AI)	Not Started	0%	-
Integrated Marketing & CRM	Complete	100%	Done
Real-Time Order & Delivery Tracking	Not Started	0%	-
Multi-Outlet Management	Not Started	0%	-
Dynamic Menu Management	Not Started	0%	-
POS System Integration	Not Started	0%	-
QR Code Ordering & Payment	Not Started	0%	-
Comprehensive Analytics & Reporting	Not Started	0%	-
Flexible Payment Options	Not Started	0%	-
Customer Feedback Mechanism	Not Started	0%	-
Automated Promotion Management	Not Started	0%	-
Multi-Language & Currency Support	Not Started	0%	-
Customer Support Integration	Not Started	0%	-
AI Workers Integration	Not Started	0%	-

Overall Plateaway Progress: 0%

4. Snac Ordering App Backend (B2C Platform)

Timeline: 16 Weeks

4.1 Overview

Nouri (Snac) is an AI-powered conversational food operating system that unifies customer discovery and ordering experiences, restaurant operations, marketing and loyalty programs, intelligent recommendations, and multi-channel ordering (dine-in, delivery, takeout).

The Snac Ordering App functions as a search engine meets personal assistant. Users interact through natural language, voice, camera scanning, and visual feeds to discover and order food.

Development Scope: Backend Development Only (AI Integration & API Services)

4.2 Technical Architecture

Component	Technology
Architecture	Microservices-first with 15-20 independent services
Data Model	Database-per-service for isolation and scalability
API Layer	API Gateway orchestration
Primary Stack	NestJS/TypeScript
API Design	OpenAPI-first contract definition
Deployment	Containerized with Docker/ECS
AI System	RAG-based using Claude/Mistral via AWS Bedrock

4.3 Development Phases

Phase 1: Foundation (Weeks 1-2)

Deliverable	Description
NestJS Starter Template	Authentication, logging, error handling
Shared Utils Package	Database, cloud, and integration logic
API Gateway Setup	Deployment pipeline configuration
AI Integration Gateway	Contracts defined with RichBrains
Core Service Contracts	User, Restaurant, Menu, Order, Payment finalized
Environment Setup	Development and staging environments ready

Phase 2: Core Development (Weeks 3-8)

Core Services (Must-Have):

Service	Purpose	Key Responsibilities
User Service	Authentication & profiles	Authentication, profiles, preferences
Restaurant Management	Restaurant operations	Restaurant setup, configuration, staff
Menu & Inventory	Menu operations	Menu management, inventory tracking
Order Management	Order processing	Order processing, delivery management
Payment & Wallet	Financial operations	Payment processing, wallet management
AI Integration Gateway	AI coordination	Data feeds, intent processing, AI support

Weekly Milestones:

Week	Milestone
Week 3	Database schemas complete, AI data export endpoints operational
Week 4	Core business logic implemented, AI intent processing functional
Week 5	Service integration complete, AI validation endpoints ready
Week 6	Authentication system operational, AI-backend integration tested
Week 7	Cross-service communication established
Week 8	All core services feature-complete and AI-integrated

Phase 3: Feature Expansion (Weeks 9-12)

Priority Services (Should-Have):

Service	Purpose	Key Responsibilities
Search & Discovery	Content search	Search algorithm, recommendations
Table Booking	Reservations	Reservation management, availability
Loyalty & Rewards	Customer retention	Customer retention programs, points
Review & Rating	Feedback	Customer feedback system
Notification	Messaging	Multi-channel messaging

Contract Delivery:

Week 9: Priority service contracts delivered to RichBrains
Week 11: Enhanced service contracts (if in scope)

Phase 4: Polish & Optimization (Weeks 13-14)

Feature completion and bug resolution
Performance optimization and scalability testing
Security audit and compliance verification
Documentation completion
Final integration testing with RichBrains

Phase 5: Testing & Buffer (Weeks 15-16)

End-to-end testing with complete user journeys
Load testing and performance validation (target: 200ms API responses)
Security testing and vulnerability assessment
AI integration stress testing
User acceptance testing support

4.4 Enhanced Services (Could-Have - If Time Permits)

Service	Purpose
Admin Dashboard	Platform management, analytics
Analytics & Insights	Reporting, business intelligence
Media Management	Content and video management
Integration Management	Third-party system connections

4.5 Core Backend Services - Detailed Scope

Backend Service	Core Purpose	Key Responsibilities
AI Integration Gateway	Process multi-modal user inputs	Natural language understanding, visual recognition, geo-context, prompt routing
Conversational Ordering	Facilitate AI-driven ordering	Intent processing, menu discovery, order construction, preference learning
Restaurant Discovery Engine	Power search and recommendations	Search algorithm, recommendation system, availability processing, ranking
Table Booking Backend	Manage reservation workflows	Availability processing, booking management, preference matching, confirmation
Loyalty & Rewards Backend	Handle loyalty programs	Points calculation, reward processing, cross-restaurant loyalty, personalization
Payment Processing	Securely process transactions	FudoPay integration, multiple payment methods, fraud detection, split payments
User Profile & Preferences	Manage user data	Profile management, preference learning, history tracking, privacy controls
Real-Time Notifications	Keep users informed	Order tracking, personalized alerts, multi-channel delivery
Analytics & Learning	Enable continuous improvement	User behavior tracking, recommendation optimization, A/B testing
Content & Media Management	Handle all media assets	Image processing, content syndication, search indexing, caching

4.6 Backend Service Functional Details

4.6.1 AI Integration Gateway

Natural Language Understanding: Process typed, voice, and image queries
Visual Recognition Engine: Detect food, text, ingredients from camera input
Geo-Context Engine: Location and time-based personalization
Prompt Router Engine: Route queries to appropriate tools (ordering, booking)
Memory System: Contextual conversation history and user preferences

4.6.2 Conversational Ordering Backend

Intent Processing: Parse user food requests and preferences
Menu Discovery: Search and filter restaurant offerings
Order Construction: Build orders through conversational flow
Preference Learning: Adapt recommendations based on user behavior
Cart Management: Handle complex order modifications and customizations

4.6.3 Restaurant Discovery Engine

Search Algorithm: Location, cuisine, dietary, and preference-based search
Recommendation System: AI-powered restaurant and dish suggestions
Availability Processing: Real-time menu and delivery availability
Ranking Algorithm: Personalized restaurant ranking and scoring
Sponsored Content: Integrated promoted listing management

4.6.4 Table Booking Backend

Availability Processing: Real-time restaurant capacity and booking slots
Booking Management: Reservation creation, modification, and confirmation
Preference Matching: Dietary restrictions, ambiance, and occasion matching
Integration Layer: Third-party booking system coordination
Confirmation System: Automated booking confirmation and reminders

4.6.5 Loyalty & Rewards Backend

Points Calculation: Real-time loyalty point accrual and redemption
Reward Processing: Cashback, discounts, and promotional reward application
Cross-Restaurant Loyalty: Unified loyalty across multiple venues
Personalization Engine: Tailored reward offers and incentives
Gamification: Achievement tracking and milestone rewards

4.6.6 Payment Processing Backend

FudoPay Integration: Unified wallet and payment processing
Multiple Payment Methods: Cards, digital wallets, loyalty redemption
Transaction Security: Encrypted payment processing and fraud detection
Split Payments: Group ordering and bill splitting functionality
Receipt Management: Digital receipt generation and storage

4.6.7 User Profile & Preferences Backend

Profile Management: User account creation and management
Preference Learning: Dietary restrictions, cuisine preferences, behavior analysis
History Tracking: Order history, favorite restaurants, and repeat patterns
Social Features: Friend connections, sharing, and recommendations
Privacy Controls: Data permissions and privacy preference management

4.6.8 Real-Time Notification System

Order Tracking: Live order status and delivery updates
Personalized Alerts: Relevant promotions, reminders, and suggestions
Multi-Channel Delivery: App push, SMS, email, WhatsApp notifications
Contextual Messaging: Location and time-based relevant communications
Preference-Based Filtering: User-controlled notification preferences

4.6.9 Analytics & Learning Backend

User Behavior Tracking: Interaction patterns and preference analysis
Recommendation Optimization: Continuous learning and algorithm improvement
Performance Analytics: System performance and user satisfaction metrics
A/B Testing Framework: Feature testing and optimization infrastructure
Privacy-Compliant Tracking: Anonymized analytics and user consent management

4.6.10 Content & Media Management

Image Processing: Food image recognition and categorization
Content Syndication: Restaurant content aggregation and normalization
Media Optimization: Image compression and delivery optimization
Search Indexing: Full-text search across menus, restaurants, and content
Caching Strategy: High-performance content delivery and caching

4.7 AI-Powered Features

4.7.1 Conversational Interface Backend

Multi-modal input processing (text, voice, image, gesture)
Context management and conversation state maintenance
Intent classification and accurate user intent detection
Entity extraction (food items, locations, preferences, constraints)
Natural language response generation

4.7.2 Visual Recognition Backend

Food detection and dish identification from camera input
Menu scanning and digital menu extraction from images
QR code processing for restaurant and menu interpretation
Logo recognition for restaurant brand identification
Nutritional analysis and ingredient extraction

4.7.3 Personalization Engine

Behavioral learning and user pattern recognition
Contextual recommendations (time, location, situation-aware)
Dietary accommodation (allergies, diets, health preferences)
Social influence and community-based recommendations
Feedback integration for recommendation tuning

4.7.4 Smart Search & Discovery

Semantic search with natural language query understanding
Fuzzy matching for approximate and partial queries
Trend detection for popular and trending food discovery
Local optimization for neighborhood preferences
Real-time adaptation and dynamic search optimization

4.8 External Integration Requirements

4.8.1 RichBrains AI Integration

RAG System: Claude/Mistral via AWS Bedrock integration
Structured API Communication: No raw query processing required
Real-time Data Feeds: Restaurant, menu, and availability information
Intent Processing: Booking and ordering workflow integration
Seamless LLM Handoff: Business logic execution coordination

4.8.2 Third-Party Service Integration

Aggregator Data: Uber Eats, Deliveroo menu and availability sync
Maps Integration: Google Places, location services
Review Aggregation: Yelp, TripAdvisor review integration
Social Media: Instagram, Facebook ordering integration
Payment Gateways: Multiple payment processor coordination

4.9 Team Structure - Snac Backend

Role	Count	Duration	Notes
JavaScript/NestJS Developers	8	Full-time, 16 weeks	Core development team
Technical Lead	1	Full-time, 16 weeks	Architecture oversight
DevOps Support	1	Part-time	Infrastructure and deployment
QA Resource	1	Final phases	Testing and validation

Total Team Size: 11 members Total Timeline: 16 Weeks

4.10 Performance Targets

Metric	Target
API Response Time	200ms
Core Services	6 must-have services
Priority Services	5 should-have services
Enhanced Services	4 could-have services (if time permits)

4.11 Completion Status

Phase 1: Foundation (Weeks 1-2)

Deliverable	Status	% Complete	Notes
NestJS Starter Template	Not Started	0%	-
Shared Utils Package	Not Started	0%	-
API Gateway Setup	Not Started	0%	-
AI Integration Gateway Contracts	Not Started	0%	-
Core Service Contracts	Not Started	0%	-
Environment Setup	Not Started	0%	-

Phase 2: Core Development (Weeks 3-8)

Service	Status	% Complete	Notes
User Service	Not Started	0%	-
Restaurant Management	Not Started	0%	-
Menu & Inventory	Not Started	0%	-
Order Management	Not Started	0%	-
Payment & Wallet	Not Started	0%	-
AI Integration Gateway	Not Started	0%	-

Phase 3: Feature Expansion (Weeks 9-12)

Service	Status	% Complete	Notes
Search & Discovery	Not Started	0%	-
Table Booking	Not Started	0%	-
Loyalty & Rewards	Not Started	0%	-
Review & Rating	Not Started	0%	-
Notification	Not Started	0%	-

Phase 4: Polish & Optimization (Weeks 13-14)

Task	Status	% Complete	Notes
Feature Completion	Not Started	0%	-
Performance Optimization	Not Started	0%	-
Security Audit	Not Started	0%	-
Documentation	Not Started	0%	-
RichBrains Integration Testing	Not Started	0%	-

Phase 5: Testing & Buffer (Weeks 15-16)

Task	Status	% Complete	Notes
End-to-End Testing	Not Started	0%	-
Load Testing	Not Started	0%	-
Security Testing	Not Started	0%	-
AI Stress Testing	Not Started	0%	-
UAT Support	Not Started	0%	-

Overall Snac Backend Progress: 0%

5. Web Scraping Engine (Data Aggregation)

Timeline: TBD

5.1 Overview

The Web Scraping Engine is a data aggregation system designed to collect, normalize, and maintain restaurant information from multiple third-party platforms. This data powers the AI-driven discovery, recommendations, and analytics across the Snac ecosystem.

Development Scope: Backend / Data Pipeline Development

5.2 Platform Coverage

Platform Category	Platforms	Primary Data
Food Delivery	Deliveroo, Uber Eats, Just Eat	Menus, pricing, delivery info, ratings
Reservations	OpenTable, Resy, Quandoo, TheFork	Table availability, booking policies, reviews
Discovery & Maps	Google Places, Google Maps	Location, hours, ratings, popular times
Reviews	Tripadvisor, SquareMeal	Reviews, ratings, awards, critic notes
Social Media	Instagram, Facebook, TikTok	Content, engagement, promotions

5.3 Data Points by Platform

5.3.1 Deliveroo / Uber Eats / Just Eat (Public Storefronts)

A. Restaurant Information

Data Point	Refresh Frequency
Restaurant name	Quarterly
Logo/image	Monthly
Cuisine type	Quarterly
Tags (Halal, Vegetarian, Gluten-Free, etc.)	Monthly
Address	Quarterly
Postcode / area / locality	Quarterly
Delivery radius	Monthly
Opening hours (day-wise)	Quarterly
Estimated prep time	Monthly
Estimated delivery time	Monthly
Restaurant rating (average)	Monthly
Total number of reviews	Monthly
Hygiene rating	Quarterly
Delivery fee	Monthly
Minimum order value	Quarterly
Offers / promos	Daily

B. Menu Information

Data Point	Refresh Frequency
Section/category names	Monthly
Item names	Monthly
Item descriptions	Monthly
Item prices	Daily
Add-ons/modifiers	Monthly
Dietary tags per item	Monthly
Popularity indicators (“Best Seller”, “Popular”)	Monthly
Menu images	Monthly
Customisation options (size, etc.)	Monthly
Calories	Quarterly
Special badges (“Top Rated”, “New”, “Local Favourite”)	Monthly

C. Delivery / Pickup Options

Data Point	Refresh Frequency
Delivery vs Pickup availability	Monthly
Estimated time for delivery/pickup	Monthly
Live status (“Currently Closed”)	Daily
Tracking support visible or not	Quarterly
Platform-specific exclusivity badge	Quarterly

5.3.2 OpenTable / Resy / Quandoo (Reservation Platforms)

A. Venue Information

Data Point	Refresh Frequency
Restaurant name	Quarterly
Cuisine type	Quarterly
Address and postcode	Quarterly
Contact phone number	Quarterly
Google Map location	Quarterly
Price level (?, ??, ???, etc.)	Quarterly
Tags (Romantic, Group Dining, Dog Friendly)	Monthly
Restaurant images (interior, food, etc.)	Monthly
Description/about section	Quarterly

B. Reservation Details

Data Point	Refresh Frequency
Table availability by date/time	Monthly
Average dining duration	Quarterly
Seating areas (Bar, Outdoor, Window)	Quarterly
Party size options	Quarterly
Booking policy (no-shows, pre-payments)	Quarterly
Special experience bookings (Tasting Menu, Chef’s Table)	Monthly
Integration with Google Reserve	Quarterly

C. Ratings & Reviews

Data Point	Refresh Frequency
Overall rating (average)	Monthly
Total number of reviews	Monthly
Ratings breakdown (food, service, ambience, value)	Quarterly
Review snippets	Monthly
Reviewer name (first name or alias)	Monthly
Date of review	Monthly
Star rating per review	Monthly
Tags from reviews (“good for dates”, “lively”, “quiet”)	Quarterly

5.3.3 Google Places / Google Maps

A. Restaurant Identity

Data Point	Refresh Frequency
Business name	Quarterly
Address (including geo-coordinates)	Quarterly
Website link	Quarterly
Phone number	Quarterly
Google Maps pin location	Quarterly
Business category (“Indian Restaurant”, etc.)	Quarterly
Opening hours (day-wise)	Quarterly
Special hours/holiday hours	Monthly
Whether dine-in / delivery / takeaway is available	Quarterly
Business description (from owner or website)	Quarterly
“Claimed” status	Quarterly

B. Media

Data Point	Refresh Frequency
Photos (interior, exterior, food, ambience)	Monthly
User-uploaded images	Monthly
360?/Street View images	Quarterly

C. Ratings & Reviews

Data Point	Refresh Frequency
Overall rating	Monthly
Total number of reviews	Monthly
Individual review text	Monthly
Reviewer name/profile	Monthly
Date posted	Monthly
Star rating	Monthly
Number of photos by reviewer	Quarterly
Thumbs up (likes) on reviews	Quarterly
Popular keywords (“Great service”, “Romantic”)	Quarterly
Questions and answers section (FAQs)	Quarterly
Review language	Quarterly

D. Real-Time Info

Data Point	Refresh Frequency
“Popular Times” graph (hour-by-hour)	Quarterly
“Live busyness” indicator	Monthly
Average visit duration	Quarterly

E. Miscellaneous

Data Point	Refresh Frequency
Accessibility info (wheelchair access, etc.)	Quarterly
Amenities (Wi-Fi, outdoor seating, bar on site)	Quarterly
Menu link (if listed)	Quarterly
Reservations link (e.g. via OpenTable)	Quarterly
Social media links (if present)	Quarterly

5.3.4 Tripadvisor

A. Restaurant Info

Data Point	Refresh Frequency
Name, address, contact info	Quarterly
Map location	Quarterly
Cuisine types	Quarterly
Price range	Quarterly
Website & booking links	Quarterly
Open hours	Quarterly
Description / About	Quarterly
Awards & recognitions (e.g. Travellers’ Choice)	Quarterly

B. Reviews

Data Point	Refresh Frequency
Total number of reviews	Monthly
Star rating	Monthly
Ratings breakdown (food, service, value, atmosphere)	Quarterly
Review titles	Monthly
Review text	Monthly
Date of review	Monthly
Reviewer location and profile	Quarterly
Review language	Quarterly
Images uploaded by reviewers	Monthly
Popular keywords (auto-tagged)	Quarterly

C. Booking / Features

Data Point	Refresh Frequency
Reserve a table (links to OpenTable/others)	Quarterly
Menu PDF link	Quarterly
Dietary restrictions (Vegetarian Friendly, Vegan Options)	Quarterly
Meals served (Lunch, Dinner, Brunch)	Quarterly
Dining style (Casual Dining, Fine Dining)	Quarterly

5.3.5 TheFork

A. Restaurant Identity & Listing

Data Point	Refresh Frequency
Restaurant name	Quarterly
Address, postcode, geo-coordinates	Quarterly
Cuisine types	Quarterly
Business category (e.g., Italian, Teppanyaki)	Quarterly
Price level (e.g., ?, ???)	Quarterly
Opening hours, special/holiday hours	Quarterly
Website URL & contact phone number	Quarterly
Reservation availability, real-time table slots	Monthly

B. Promotions & Rewards

Data Point	Refresh Frequency
Exclusive discounts (e.g., up to 50% off)	Daily
Loyalty offers (“Yums” rewards)	Monthly

C. Reviews & Ratings

Data Point	Refresh Frequency
Overall average rating & total number of reviews	Monthly
Individual review entries (reviewer, date, rating, text)	Monthly
Verified review flags	Quarterly

D. Media & Presentation

Data Point	Refresh Frequency
Restaurant logo & cover image	Monthly
User-submitted photos	Monthly
Virtual tours or embedded media (if visible)	Quarterly

E. Availability & Booking Info

Data Point	Refresh Frequency
Live availability data (next available slot, calendar)	Monthly
Seating/tables categories (indoor/outdoor/bar)	Quarterly
Booking policy: cancellation rules, no-show rules	Quarterly

5.3.6 SquareMeal

A. Restaurant & Venue Directory Data

Data Point	Refresh Frequency
Name, address, postcode, map location	Quarterly
Cuisine styles & categories (e.g., Afternoon Tea, Late-night)	Quarterly
Price range (?, ??, ???)	Quarterly
Tags/attributes (“Dog Friendly”, “Private Dining”, “Group Dining”)	Monthly
Awards info (e.g., Gold Award status)	Quarterly

B. Images & Promotions

Data Point	Refresh Frequency
Hero images (venue interior/exterior)	Monthly
Event collages (e.g., Wimbledon screenings)	Monthly
Offers: rewards points, set menus, promotions	Daily

C. Reviews & Critic Notes

Data Point	Refresh Frequency
SquareMeal critic reviews or editorial write-ups	Quarterly
Aggregate ratings (if present)	Monthly
Count of reviews from users or critic	Monthly

D. Booking & Event Data

Data Point	Refresh Frequency
Reservation links or embedded booking widgets	Quarterly
Events and experiential listings with date/time	Monthly
Venue features: private dining rooms, wedding spaces, conference facilities	Quarterly

E. Awards & Rankings

Data Point	Refresh Frequency
SquareMeal Gold Awards listings, descriptions, award dates	Quarterly
Top-n awards lists (Top 100 restaurants, regionally ranked)	Quarterly

F. Metadata & Trade Data

Data Point	Refresh Frequency
Critic editorial notes, cuisine descriptions	Quarterly
Listing creation/last-updated dates (when shown)	Quarterly
Rewards programme structure (points per ? spent)	Quarterly
Venue type tags (wedding venue, private dining, pub, etc.)	Quarterly

A. Profile Scraping

Data Point	Refresh Frequency
Bio text (often mentions cuisine, delivery, hours)	Quarterly
Location tag / map pin	Quarterly
Link in bio (ordering site, reservation)	Quarterly
Number of followers/posts	Monthly
Story highlights (e.g., Menu, Offers, Reviews)	Monthly

B. Post Content

Data Point	Refresh Frequency
Image/video of dishes, ambience, events	Monthly
Captions (menu info, events, offers)	Daily
Hashtags (e.g., #LondonEats)	Monthly
Comments & engagement level	Monthly
Tagged people (e.g., influencers)	Monthly

5.3.8 Facebook Pages (Business and Public Profiles)

A. Page Identity & Meta

Data Point	Refresh Frequency
Page name, vanity URL, page ID	Quarterly
Category/subcategory (e.g., Restaurant, Caf?, Baker)	Quarterly
About/Bio text	Quarterly
Profile and cover images	Monthly
Contact info: phone, email (if listed)	Quarterly
Address, geo-coordinates, map link	Quarterly
Website, external links (e.g., booking, delivery)	Quarterly
Store opening hours	Quarterly
Price range (EUR, $, etc.)	Quarterly
Business status (Open, Permanently Closed)	Quarterly

B. Audience & Engagement Metrics

Data Point	Refresh Frequency
Number of page followers & likes	Monthly
Check-ins (if visible)	Quarterly
Recommendations and star rating	Monthly
Ratings breakdown (number of 5?, 4? etc.)	Quarterly
Response rate/time (if public)	Quarterly

C. Posts & Content

Data Point	Refresh Frequency
Post ID, timestamp	Monthly
Text content (captions, messages)	Daily
Media: images/videos (URLs, alt text)	Monthly
Reaction counts (Like, Love, Wow, Sad, etc.)	Monthly
Comment count, share count	Monthly
Public comments (with commenter alias, date, text, likes)	Monthly
Post type (photo, video, status, shared link)	Quarterly
Links/URLs in posts (e.g., reservation links)	Monthly

D. Events

Data Point	Refresh Frequency
Event name, description	Monthly
Start/end date & time	Monthly
Location (venue name, address)	Quarterly
Cover image	Monthly
RSVPs (Going, Interested count)	Monthly

E. Reviews / Recommendations

Data Point	Refresh Frequency
Individual review entries: user name, date, star rating, text	Monthly
Recommend system (“Yes/No”) with reasons	Quarterly
Review comment count & reactions	Monthly

F. Miscellaneous

Data Point	Refresh Frequency
Services section (“Home delivery”, “Outdoor seating”)	Quarterly
Menu link (if linked to external site)	Quarterly
Story highlights (if public)	Monthly
Community posts (user-generated content)	Monthly

5.3.9 TikTok Profiles (Public Accounts)

A. Profile Identity

Data Point	Refresh Frequency
Username, display name, user ID	Quarterly
Profile picture	Monthly
Bio text	Quarterly
External link in bio (e.g., website, ordering link)	Quarterly
Verified badge status	Quarterly

B. Follower Stats

Data Point	Refresh Frequency
Number of followers	Monthly
Number of followings	Quarterly
Total likes received	Monthly
Number of videos posted	Monthly

C. Videos & Content Metadata

Data Point	Refresh Frequency
Video ID & URL	Monthly
Upload timestamp	Monthly
Caption text	Daily
Hashtags used	Monthly
Mentioned users	Monthly
Music/sound info (title, author)	Quarterly
Video duration	Quarterly
Thumbnail URL	Monthly

D. Engagement Metrics

Data Point	Refresh Frequency
Play views	Monthly
Likes	Monthly
Comments	Monthly
Shares	Monthly
Saves/bookmarks (if visible)	Monthly

E. Hashtag & Trend Metrics

Data Point	Refresh Frequency
List of hashtags used by the profile	Quarterly
Video-level metadata for trending/search scraping	Monthly

5.4 Data Refresh Frequency Summary

Frequency	Data Types	Examples
Daily	High-volatility data	Prices, offers/promos, live status, captions
Monthly	Moderate-change data	Ratings, reviews, images, follower counts, menu items
Quarterly	Low-change data	Business info, addresses, hours, policies, categories

5.5 Technical Considerations

Data Pipeline Requirements:

Scalable web scraping infrastructure
Rate limiting and respectful crawling
Data normalization and deduplication
Entity matching across platforms
Change detection and delta updates
Error handling and retry mechanisms
Compliance with platform terms of service

Integration Points:

Restaurant Discovery Engine (search & recommendations)
Menu Service (menu data aggregation)
Review & Rating Service (sentiment aggregation)
Analytics Service (competitive intelligence)
AI Integration Gateway (data feeds for LLM)

5.6 Team Structure - Web Scraping Engine

Role	Count	Duration	Notes
Backend/Data Engineer	TBD	TBD	-
Scraping Specialist	TBD	TBD	-
DevOps Engineer	TBD	TBD	-
QA Engineer	TBD	TBD	-

Total Team Size: TBD Total Timeline: TBD

5.7 Development Phases (TBD)

Phase	Weeks	Key Deliverables	Status
Phase 1: Infrastructure Setup	TBD	Scraping framework, proxies, scheduling	Not Started
Phase 2: Platform Scrapers	TBD	Individual platform scrapers	Not Started
Phase 3: Data Pipeline	TBD	Normalization, deduplication, storage	Not Started
Phase 4: Integration	TBD	API endpoints, service integration	Not Started
Phase 5: Testing & Optimization	TBD	Performance, accuracy, compliance	Not Started

5.8 Completion Status

Platform Scrapers

Platform	Status	% Complete	Notes
Deliveroo	Not Started	0%	-
Uber Eats	Not Started	0%	-
Just Eat	Not Started	0%	-
OpenTable	Not Started	0%	-
Resy	Not Started	0%	-
Quandoo	Not Started	0%	-
Google Places / Maps	Not Started	0%	-
Tripadvisor	Not Started	0%	-
TheFork	Not Started	0%	-
SquareMeal	Not Started	0%	-
Instagram	Not Started	0%	-
Facebook Pages	Not Started	0%	-
TikTok	Not Started	0%	-

Infrastructure & Pipeline

Component	Status	% Complete	Notes
Scraping Framework	Not Started	0%	-
Proxy Management	Not Started	0%	-
Scheduler/Orchestration	Not Started	0%	-
Data Normalization	Not Started	0%	-
Entity Matching	Not Started	0%	-
Storage Layer	Not Started	0%	-
API Endpoints	Not Started	0%	-
Monitoring & Alerts	Not Started	0%	-

Overall Web Scraping Engine Progress: 0%

6. Unified Backend Architecture

6.1 Microservices Foundation

The entire ecosystem is built on a shared microservices architecture consisting of 15-20 independent services.

6.1.1 Core Services

User Service: Authentication, profiles, preferences
Restaurant Service: Restaurant setup, configuration, staff management
Menu Service: Menu management, inventory tracking, item availability
Order Service: Order processing, delivery management, fulfillment tracking
Payment Service: Payment processing, wallet management, transaction handling
AI Integration Gateway: Data feeds, intent processing, AI workflow coordination

6.1.2 Business Logic Services

Search & Discovery Service: Content search, recommendation engine
Booking Service: Reservation management, availability processing
Loyalty Service: Rewards processing, customer retention programs
Notification Service: Multi-channel messaging and alert system
Analytics Service: Data processing, insights generation, reporting
Campaign Service: Marketing automation, promotional management

6.1.3 Integration Services

POS Integration Service: Third-party system coordination
Payment Gateway Service: Multiple payment processor management
Social Media Service: Platform integration and social commerce
Review Aggregation Service: Multi-source feedback collection
Delivery Service: Third-party delivery partner coordination
Media Management Service: Image processing, content optimization

6.2 Data Architecture

6.2.1 Database Strategy

PostgreSQL Primary: Structured data storage with Prisma ORM
Database per Service: Independent data ownership and scaling
Event Sourcing: Critical business event tracking and audit trails
CQRS Implementation: Separate read and write data models for performance

6.2.2 Caching & Performance

Redis: Session management, frequently accessed data caching
CDN Integration: Global content delivery and asset optimization
API Gateway: Request routing, rate limiting, and security enforcement
Load Balancing: Horizontal scaling and traffic distribution

7. Technology Stack

7.1 Frontend

Category	Tools / Technologies	Purpose
Frameworks	React.js, Next.js, TypeScript	SSR for SEO, PWA support
Styling / UI	TailwindCSS, shadcn/ui, Radix UI	Consistent UI & components
Animations	Framer Motion	Smooth transitions & micro-interactions
Charts	Recharts, Chart.js	Analytics dashboards & reporting
State / Data	React Query (TanStack), SWR	Server-state caching & data fetching

7.2 Backend

Category	Tools / Technologies	Purpose
Runtime / Framework	Node.js, NestJS (TypeScript)	Modular architecture, DI
ORM / DB	Prisma	Simple, type-safe DB access
Primary Database	PostgreSQL (RDS)	Relational data store
Cache / Realtime	Redis (cache, pub/sub, Streams)	Sessions, latency reduction, events
Async Messaging	Kafka / RabbitMQ / Redis Streams	Event-driven workflows

7.3 AI / ML

Category	Tools / Technologies	Purpose
AI Workers	Python, FastAPI, Node.js microservices	Batch tasks, menu optimization, recommendations
LLM Integration	Claude/Mistral via AWS Bedrock	RAG-based conversational AI

7.4 Infrastructure & DevOps

Category	Tools	Purpose
Containerization	Docker	Local/Prod consistency
Orchestration	Kubernetes (EKS/GKE) or ECS/Fargate	Scale services
IaC	Terraform	Infra automation
CI/CD	GitHub Actions	Build, test, deploy
Object Storage	AWS S3 + CloudFront	Assets, CDN
Monitoring	Prometheus, Grafana, ELK, Datadog	Metrics, logs, tracing

7.5 Integrations

Category	Tools
Payments	FudoPay, Stripe, Razorpay, PayPal
POS Integration	Square, Toast, Clover, custom APIs
Social Media	Instagram, WhatsApp Cloud API, FB Messenger
Maps	Google Maps / Places API
Notifications	FCM (push), Twilio SMS, WhatsApp API

8. Project Timeline Summary

8.1 Parallel Execution Timeline

Week	Snac Workspace	Plateaway	Snac Backend	Web Scraping
1-2	Foundation & Card Builder	Foundation & Branded Website	Phase 1: Foundation, NestJS Template, API Gateway	TBD
3-4	B2B AI Setup Assistant	Menu Management	Phase 2: Core Services - User, Restaurant	TBD
5-6	Ordering Tool Management	Advanced Ordering & Checkout	Phase 2: Core Services - Menu, Order	TBD
7-8	Table Booking, Loyalty	Social Media, Upselling AI	Phase 2: Core Services - Payment, AI Gateway	TBD
9-10	WiFi Marketing, Sponsored Listing	Real-Time Tracking, Multi-Outlet	Phase 3: Priority Services - Search, Booking	TBD
11-12	Analytics Tool	Dynamic Menu, POS Integration	Phase 3: Priority Services - Loyalty, Review, Notification	TBD
13-14	FudoPay	Analytics, Payment Options	Phase 4: Polish, Performance, Security Audit	TBD
15-16	Inventory, Review & Feedback	Feedback, Promotions	Phase 5: Testing, Load Testing, UAT	TBD
17-18	AI Growth Manager, AI Workers	Multi-Language, Currency	-	TBD
19-20	Integration & Testing	Customer Support	-	TBD
21-22	-	Final Integration & UAT	-	TBD

8.1.1 Web Scraping Engine Timeline (TBD)

Phase	Duration	Activities	Status
Phase 1: Infrastructure	TBD Weeks	Scraping framework setup, proxy management, scheduler	Not Started
Phase 2: Core Scrapers	TBD Weeks	Deliveroo, Uber Eats, Just Eat, Google Places	Not Started
Phase 3: Reservation Platforms	TBD Weeks	OpenTable, Resy, Quandoo, TheFork	Not Started
Phase 4: Review Platforms	TBD Weeks	Tripadvisor, SquareMeal	Not Started
Phase 5: Social Media	TBD Weeks	Instagram, Facebook, TikTok	Not Started
Phase 6: Data Pipeline	TBD Weeks	Normalization, entity matching, deduplication	Not Started
Phase 7: Integration	TBD Weeks	API endpoints, service integration, testing	Not Started

Web Scraping Engine Total Duration: TBD Weeks Web Scraping Engine Team Size: TBD members

8.2 Component Completion Summary

Component	Timeline	Team Size	Completion Week
Snac Backend	16 Weeks	11 members	Week 16
Snac Workspace	18-20 Weeks	14 members	Week 18-20
Plateaway	20-22 Weeks	15 members	Week 20-22
Web Scraping Engine	TBD	TBD	TBD

8.3 Key Milestones & Deliverables

Component	Phase	Weeks	Key Deliverables
Snac Backend	Foundation	1-2	NestJS template, API Gateway, AI contracts with RichBrains
Snac Backend	Core Development	3-8	6 core services (User, Restaurant, Menu, Order, Payment, AI Gateway)
Snac Backend	Feature Expansion	9-12	5 priority services (Search, Booking, Loyalty, Review, Notification)
Snac Backend	Polish & Testing	13-16	Performance optimization, security audit, E2E testing, UAT
Snac Workspace	Core Modules	1-12	Card Builder, Ordering, Table Booking, Loyalty, Analytics
Snac Workspace	Advanced Features	13-18	FudoPay, AI Growth Manager, AI Workers
Plateaway	Core Platform	1-10	Branded Website, Menu, Ordering, Social Media, Tracking
Plateaway	Advanced Features	11-20	POS Integration, Analytics, Promotions, Multi-language
Plateaway	Final Polish	21-22	Customer Support, Final Integration, UAT
Web Scraping	Infrastructure Setup	TBD	Scraping framework, proxies, scheduling
Web Scraping	Platform Scrapers	TBD	Deliveroo, Uber Eats, Just Eat, OpenTable, Google, etc.
Web Scraping	Data Pipeline	TBD	Normalization, deduplication, entity matching
Web Scraping	Integration	TBD	API endpoints, service integration
Web Scraping	Testing & Optimization	TBD	Performance, accuracy, compliance testing

8.4 Combined Team Summary

Component	Team Size
Snac Workspace	14 members
Plateaway	15 members
Snac Backend	11 members
Web Scraping Engine	TBD
Total (with overlap)	~35-40+ members

Overall Project Delivery: 22 Weeks (Parallel Execution) + Web Scraping TBD

Snac Backend completes at Week 16
Snac Workspace completes around Week 18-20
Plateaway completes around Week 20-22
Web Scraping Engine timeline to be confirmed

8.5 Overall Project Completion Status

Component	Progress	Status
Snac Workspace (B2B)	0%	Not Started
Plateaway (White-Label)	0%	Not Started
Snac Backend (B2C)	0%	Not Started
Web Scraping Engine	0%	Not Started
Overall Project	0%	Not Started