Introduction

Features

Data & Intelligence

• Intelligent Data Collection: Automatically gathers information from news sites, social media platforms, and public media sources using targeted search queries and intelligent web scraping
• Entity Intelligence: Maintains dynamic entity relationship graphs (competitors, suppliers, customers, executives, partners) to enhance search queries and provide comprehensive business context

AI & Analysis

• Multi-Agent Architecture: Specialized AI agents handle different aspects of the pipeline (data collection, analysis, content generation, quality assurance, delivery, learning) for optimal performance and maintainability
• Comprehensive Analysis: Performs sentiment analysis to understand public perception, competitive landscape research to monitor what's being said about competitors in the media, and event/context analysis to identify external events (natural disasters, political changes, regulatory updates, economic shifts, social movements) that could affect the company
• Extensible Plugin System: Analysis capabilities are built on a plugin-based architecture that allows easy addition, removal, or modification of analysis types without code changes. New analysis types can be registered in the database and automatically integrated into the system
• Self-Improving System: Learning agent analyzes user feedback, engagement metrics, and agent performance to continuously optimize content generation strategies
• Agent Versioning: Complete version history for all agents with admin-controlled production deployments. Learning agent creates optimized versions automatically, while admins maintain full control over which version runs in production with instant rollback capability

Content & Personalization

• Personalized Content: Generates newsletters tailored to each user's preferences, focus areas, and risk tolerance with customizable detail levels and delivery schedules
• Executive-Focused Format: Concise, actionable media insights designed for busy executives who need quick understanding of public perception and media coverage about their companies
• A/B Testing: Built-in A/B testing framework allows experimentation with different content styles, structures, and delivery times to maximize engagement

Quality & Delivery

• Quality Assurance: Automated fact-checking, compliance verification, and quality scoring ensure accurate, compliant, and high-quality content before delivery
• Multi-Channel Delivery: Delivers newsletters via email and web dashboard with tracking, personalization, and responsive design
• Interactive Feedback: Section-level feedback buttons (Like/Dislike, Useful/Irrelevant) allow users to provide granular feedback on newsletter content, enabling continuous improvement and personalization

Infrastructure & Scalability

• Database-Driven Configuration: All system configurations stored in the database for dynamic updates without code deployments
• Plugin-Based Extensibility: Analysis types and other capabilities can be extended through a plugin registry system, enabling runtime addition/removal of features without code changes
• Agent Version Management: Version control system for agents with production deployment controls, performance tracking per version, and instant rollback capabilities
• Scalable Architecture: Queue-based job processing with BullMQ and Redis enables handling multiple tickers and users concurrently

System Architecture

A modular multi-agent system built with Next.js (App Router), TypeScript, Python, and OpenAI, designed for busy executives who need concise, actionable media monitoring insights.

Core Components

The system consists of 7 specialized agents and 1 orchestrator component:

Agents (7 types):

1. Query Strategy Agent - Maintains entity relationships, generates dynamic search queries, detects trends, and learns from successful content
2. Data Collection Agent - Uses queries from Query Strategy Agent to collect data from news sites, social media, and public media sources
3. Analysis Agent - Performs analysis using a plugin-based system. By default includes sentiment analysis, competitive landscape research, and event/context analysis. New analysis types can be added by implementing plugin code and registering metadata in the database
4. Content Generation Agent - Creates newsletter content using AI with consistent formatting and tone
5. Quality Assurance Agent - Validates content quality, fact-checks, and ensures compliance
6. Delivery Agent - Handles email delivery and web dashboard updates
7. Learning Agent - Tracks metrics, learns from user feedback, optimizes content generation, and creates new agent versions with improvements

Orchestrator (core system component, not an agent):

• Scheduler/Orchestrator - Manages periodic tasks, job orchestration, and agent instance lifecycle. The orchestrator is a core system component that schedules and coordinates agent execution, but is not itself an agent. See Architecture for details.

Technical Stack

• Framework: Next.js 16+ (App Router) with TypeScript
• Database: PostgreSQL with Prisma ORM
• Queue System: BullMQ with Redis for job processing
• AI Provider: OpenAI (GPT-4) with fallback support
• Email: Resend or SendGrid
• Web Scraping: Playwright for dynamic content, Cheerio for static
• Authentication: NextAuth.js for user management
• Monitoring: Custom metrics dashboard + error tracking