Raseed: Intelligent Financial Insights

This document outlines the comprehensive project architecture for Raseed, a revolutionary financial application that leverages Google's AI and Cloud stack to provide users with proactive, context-aware financial wisdom. It moves beyond simple expense tracking to deliver personalized insights directly within the user's native digital wallet experience.

Project Architecture Diagram

USER INTERFACE
Google Wallet App
Primary mobile interface
Assistant Integration
Voice and proactive commands
Web Interface
Desktop/browser access
API GATEWAY
Cloud API Gateway + Load Balancer
Secure, scalable entry point for all requests
PROCESSING
Gemini Pro
Multimodal data extraction
Vertex AI
Agent Builder for complex workflows
Cloud Functions
Event-driven orchestration
DATA
Cloud Storage
Stores unstructured data (receipts)
Firestore
User profiles and real-time data
BigQuery
Data warehouse for analytics
INTELLIGENCE
Pattern Recognition
ML Models for spending habits
Predictive Analytics
BigQuery ML for future insights
Personalization
Recommendations engine
INTEGRATION
Google Wallet API
Pass and card management
Push Notifications
Firebase for user engagement
External APIs
Price comparison, offers etc.

Data Flow Diagrams (DFD)

DFD Level 0: Context Diagram

User
Receipt Image, Voice Query
0
Raseed System
Wallet Pass, Insights
Google Wallet

DFD Level 1: Core Processes

This diagram breaks down the Raseed system into its main sub-processes, showing how data flows between them and to the primary data stores.

User
Receipt Image/Query
1.0
Receipt & Query Processing
Structured Data
2.0
Analysis & Insight Generation
Personalized Insights
3.0
Wallet & Notification Management
Wallet Pass / Notification
User Interface
D1: Receipt Storage (Cloud Storage)
D2: User Data (Firestore)
D3: Analytics Data (BigQuery)

DFD Level 2: Receipt Processing Detail

A detailed look into the "Receipt & Query Processing" sub-system, showing the sequence of operations from image submission to data storage.

User Interface
Receipt Image
1.1
Image Pre-processing (Vision API)
Processed Image
1.2
Multimodal Data Extraction (Gemini Pro)
Extracted Text & Context
1.3
Categorization & Enrichment (NL API)
Structured JSON Data
To D1, D2, D3

✍️ Wireframes

Low-fidelity wireframes outlining the core screens and user flows, focusing on structure and functionality.

1. Dashboard Screen
+
2. Receipt Analysis View
3. Wallet Insight Pass

🎨 UI Mockups

High-fidelity mockups demonstrating the application's final look and feel, based on the Google Wallet design system.

1. App Dashboard
A

Good afternoon, Alex

This Month's Spending
$842.50
Recent Transactions

Starbucks $12.50

Amazon.com $78.99

2. Insight Pass in Google Wallet
Wallet Icon
Raseed.ai Financial Wisdom

Your grocery spending is trending up:

+18%

this month vs. last

Tap to see detailed breakdown and suggestions

Added to your Google Wallet

3. Receipt Analysis Complete
✓

Analysis Complete

Gemini has processed your receipt.

Merchant

SuperMart

Total Amount

$45.67

Category

Groceries

Done

⚙️ Technologies to be Used

Google AI & Cloud Stack

  • Gemini Pro: Core of the system for multimodal analysis of receipts, understanding both the image and the text in context.
  • Vertex AI Agent Builder: Powers the conversational AI for intelligent, human-like responses to user queries via voice or text.
  • Google Wallet API: Enables the native creation and management of financial insight "passes" directly in Google Wallet.
  • Cloud Vision API: Enhances raw receipt images through OCR, pre-processing, and quality improvement before analysis.
  • Cloud Natural Language API: Performs sentiment analysis on purchases and extracts contextual entities for deeper understanding.

Supporting & Data Technologies

  • Firebase (Auth & Firestore): Manages user authentication, profiles, and real-time synchronization of user-specific data.
  • Cloud Functions: Acts as the serverless "glue" orchestrating the entire processing pipeline from receipt upload to insight delivery.
  • BigQuery & BigQuery ML: Serves as the data warehouse for all transactional data and runs ML models for predictive analytics and pattern recognition.
  • Cloud Storage: Provides secure, scalable, and durable storage for raw and processed receipt images.