🧑‍💻Tech Stack

Boogl.AI Tech Stack

Overview

Boogl.AI is built on a modern, privacy-focused architecture that combines advanced web search capabilities with state-of-the-art AI summarization. This document outlines the technical components that power our platform and explains how they work together to deliver accurate, up-to-date search results with proper source attribution.

Core Components

1. Search Infrastructure

At the heart of Boogl.AI is our search infrastructure, which leverages the Tavily API to retrieve high-quality, relevant information from across the web.

Tavily Integration

Boogl.AI uses Tavily's powerful search API to access real-time web data:

• Query Processing: User queries are analyzed and enhanced to improve search relevance

• Source Retrieval: The system fetches information from multiple high-quality sources

• Content Extraction: Detailed content is extracted from web pages for comprehensive analysis

• Result Ranking: Sources are ranked by relevance and credibility

Enhanced Search Optimization

Our enhanced search system automatically optimizes queries based on content type:

• News Queries: For current events, the system prioritizes recency and authoritative news sources

• Academic Queries: For research topics, it focuses on scholarly sources with deeper historical context

• Technical Queries: For programming and technical topics, it targets developer resources and documentation

• Financial Queries: For market information, it emphasizes timely data from financial publications

2. AI Summarization Engine

The retrieved search results are processed by our AI summarization engine, which:

1. Analyzes Multiple Sources: Examines content from various websites to identify key information

2. Verifies Information: Cross-references facts across different sources

3. Generates Summaries: Creates concise, accurate summaries of the information

4. Cites Sources: Automatically includes links to original sources for transparency and attribution

3. Privacy-First Architecture

Unlike traditional search engines that track user behavior, Boogl.AI is designed with privacy at its core:

• No User Profiling: We don't build or maintain user profiles

• No Search History: We don't store your search history

• No Tracking Cookies: We don't use cookies to track you across the web

• Contextual Results: Search results are based on your query, not your personal data

Technical Implementation

Search Process Flow

1. Query Enhancement

   // The system automatically enhances user queries
   function enhanceQuery(query: string) {
     // Add recency indicators for time-sensitive queries
     // Optimize parameters based on query type
     // Return enhanced query with optimized parameters
   }

2. Parallel Content Retrieval

   // Multiple sources are processed in parallel for efficiency
   const extractionPromises = topResults.map(async (result) => {
     // Extract detailed content from each source
     const extractedContent = await extractUrlContent(result.url);
     return { content: extractedContent };
   });
   
   // Wait for all extractions to complete
   const extractionResults = await Promise.allSettled(extractionPromises);

3. AI Analysis and Summarization

   // The AI researcher agent processes search results
   const SYSTEM_PROMPT = `
     You are a helpful AI assistant with access to real-time web search.
     When asked a question, you should:
     1. Search for relevant information using the search tool
     2. Analyze all search results to provide accurate information
     3. Always cite sources using the [number](url) format
     4. Provide comprehensive responses based on search results
   `;

Performance Optimizations

Boogl.AI implements several optimizations to ensure fast, reliable results:

1. Intelligent Caching

   // Create a search cache instance
   const searchCache = new Cache<any>({
     maxSize: 100,
     ttl: 5 * 60 * 1000 // 5 minutes
   });
   
   // Check cache before performing a search
   const cachedResult = searchCache.get(cacheKey);
   if (cachedResult) {
     return cachedResult;
   }

2. Adaptive Extraction Strategies

   // Use different extraction strategies based on query urgency
   const isTimeSensitive = /breaking|latest|news|today|now|current|update/i.test(query);
   const extractionStrategy = isTimeSensitive ? 'fast' : 'complete';

3. Timeout and Retry Logic

   // Implement timeouts to prevent hanging on slow requests
   const response = await fetchWithRetry('https://api.tavily.com/search', {
     timeout: 20000,    // 20 second timeout
     retries: 2,        // 2 retries
     retryDelay: 1000,  // Start with 1 second delay
     exponentialBackoff: true // Use exponential backoff
   });

Integration Architecture

Web Application

Our web application is built with:

• Next.js: For server-side rendering and optimal performance

• React: For component-based UI development

• Tailwind CSS: For responsive, utility-first styling

API Layer

The API layer connects the frontend to our search and AI services:

• REST API: Handles search requests and returns results

• Streaming Responses: Delivers AI-generated content in real-time as it's generated

• Rate Limiting: Ensures fair usage and system stability

Deployment Infrastructure

Boogl.AI is deployed on a scalable, reliable infrastructure:

• Vercel: For global CDN and edge computing

• Serverless Functions: For on-demand scaling of API endpoints

• Redis: For distributed caching and performance optimization

Future Technical Roadmap

Our technical roadmap includes:

1. Custom AI Model Development: Creating a specialized, distilled AI model optimized for search summarization

2. Expanded Multi-Modal Search: Adding support for image and video search capabilities

3. Mobile Application Development: Building native mobile apps for iOS and Android

4. Bot Integrations: Developing Telegram and Twitter bots for search access on social platforms

Conclusion

Boogl.AI's technical architecture represents a new approach to search that prioritizes privacy, accuracy, and transparency. By combining Tavily's powerful search capabilities with advanced AI summarization, we deliver a superior search experience that respects user privacy while providing comprehensive, well-cited results.