Project Overview

Sunrise Communication is a technical service integration platform for security and telecommunications systems. The project provides a lead-generation catalog and interactive estimation tools for B2B and B2C clients, specializing in CCTV, EPABX, biometrics, and structured networking. The system architecture emphasizes Search Engine Optimization (SEO), AI Engine Optimization (AEO), and technical discovery through machine-readable specifications.

Sources: implementation_plan.md:9-11, llms-full.txt:7-14, task.md:3-5

System Architecture

The project utilizes a decoupled architecture with an Angular frontend and a Django backend. The frontend focuses on Server-Side Rendering (SSR) for SEO performance and utilizes Angular Signals for reactive state management.

Frontend Technical Stack

The frontend application uses Angular v22 with Standalone Components and the @angular/ssr package. It manages data through services decorated with @Service and leverages HttpClient for both static JSON assets and future REST API integration.

Sources: implementation_plan.md:15-30, implementation_plan.md:104-118

Architectural Data Flow

The following diagram illustrates the data flow between the Product Service, signals, and the UI components.

Core Features and Modules

Product Catalog & Discovery

The catalog provides a filtered interface for hardware products like CCTV cameras and biometric terminals. It utilizes signal-based filtering to manage search queries, categories, and brands without page reloads.

Sources: implementation_plan.md:203-228

Sources: implementation_plan.md:46-52, implementation_plan.md:247-255, implementation_plan.md:309-322

Interactive Requirement Estimator

The RequirementEstimatorComponent allows users to select premise types and service needs to receive a technical Bill of Quantities (BOQ). It calculates hardware requirements such as NVR channels and HDD storage sizes based on user input.

AI and Search Optimization (AIO/AEO)

The project includes a dedicated "Agentic Discovery Layer" to serve AI crawlers and LLMs. This involves specialized manifests and structured data injection.

• Machine-Readable Manifests: Includes llms.txt, llms-full.txt, and llms.json for technical specifications.
• Knowledge Graph: The SeoService refactors metadata into a unified JSON-LD @graph containing LocalBusiness, Service, FAQPage, and HowTo schemas.
• Robot Permissions: Configures robots.txt to permit specific AI agents like GPTBot and PerplexityBot.

Sources: task.md:9-15, sunrise-angular/src/app/core/services/seo.service.ts:51-140

Data Models

The system defines products through a strictly typed interface to ensure consistency between the mock JSON data and future API responses.

export interface Product {
  id: string;
  slug: string;
  name: string;
  brand: string;
  category: string;
  category_slug: string;
  short_description: string;
  specs: ProductSpec[];
  services_offered: ServiceType[];
}

Sources: implementation_plan.md:73-90

Lead Generation Logic

Leads are captured through a WhatsApp integration that bypasses traditional forms. The SeoService and various components construct deep links to WhatsApp, pre-filling the message with product details or calculated BOQ specifications to facilitate immediate technical consultation.

Sources: implementation_plan.md:313-322, sunrise-angular/src/app/shared/components/requirement-estimator/requirement-estimator.component.ts:98-105

Conclusion

Sunrise Communication integrates traditional service delivery with modern discovery technologies. By combining Angular v22's reactive primitives with extensive structured data for AI engines, the platform serves as both a user-facing catalog and a machine-readable knowledge base for security and telecommunications infrastructure in the Mumbai MMR region.

Sources: task.md:3-7, implementation_plan.md:9-13, llms-full.txt:134-142