An agentic company research tool powered by LangGraph and Tavily that conducts deep diligence on companies using a multi-agent framework. It leverages Google's Gemini 2.5 Flash and OpenAI's GPT-5.1 on the backend for inference.

The backend code for the LangGraph-research-agent-v2... using LangGraph multi-turn agents and LangChain tools- for Q&A, draft paper writing and whole lot of research stuffs

A fullstack project using LangGraph, combining frontend and backend for AI research and agent development.

Complete Deep Agents system with LangGraph research agent backend and Next.js UI frontend - Docker Compose deployment ready

Combines specialized agents (Research, Reasoning, Writing) orchestrated with CrewAI/LangGraph, document retrieval via embeddings and vector databases (FAISS/Chroma), and a FastAPI backend with an interactive React interface. Designed for scalable, explainable, and real-world AI applications.

Deep Research Agent with LangGraph backend and React frontend

This project serves as the backend for a GenAI Deep Research application, utilizing FastAPI for the API and Langchain/Langgraph for orchestrating research agents.

An agentic company research tool powered by LangGraph and Tavily that conducts deep diligence on companies using a multi-agent framework. It leverages Google's Gemini 2.0 Flash and OpenAI's GPT-4.1 on the backend for inference.

AI-powered YouTube automation pipeline - multi-agent system (LangGraph) that researches trends, writes scripts, generates voiceover (Kokoro TTS / ElevenLabs), animates avatars, sources B-roll, adds captions (WhisperX) and BGM (MusicGen), compiles the final video (FFmpeg), and uploads to YouTube - FastAPI backend + Next.js dashboard.

Lens AI - Research Agent Backend (Python + LangGraph)

Autonomous multi-agent research assistant backend — LangGraph + FastAPI + Celery

Gemini Fullstack Agent with LangGraph backend - AI research agent with web interface

Automated research gap identification & hypothesis generation. 7-agent LangGraph pipeline, 5 literature sources, semantic clustering, FastAPI backend.

Backend Agentic AI Research Assistant built using FastAPI and LangGraph that automates research planning, information gathering, and structured content generation through a multi-agent workflow.

FastAPI backend for QueryNest for multi-agent LangGraph pipeline that autonomously searches, fact-checks and compiles research reports with WebSocket streaming.

A multi‑agent AI research assistant that combines web search, summarization, and Q&A using LangGraph with a FastAPI backend and Streamlit UI

Production-grade multi-agent email triage system built with LangGraph. Features 6 specialized agents for classification, context gathering, research, drafting, and adaptive learning. Includes FastAPI backend and React analytics dashboard.

Multi-Agent Research Assistant Simple multi-agent research assistant that answers user questions using multiple AI agents working together. Overview: A Research assistant using: 1. LangGraph to orchestrate agents 2. Mock MCP tool 3. Django REST API as backend 4. Streamlit UI as frontend 5. Database to store conversations (SQLLite)

AI-powered backend for automated book/document updating. Built with FastAPI & LangGraph agents for document ingestion, research & fact-checking, selective content updates, and DOCX export with auto-renumbering.

An intelligent task orchestration system powered by multiple AI agents. Features planner, researcher, executor, and critic agents working together using LangGraph. Built with FastAPI backend, React frontend, JWT authentication, MongoDB persistence, and Google OAuth integration.

A sophisticated, production-ready multi-agent RAG system orchestrating specialized agents (Researcher, Planner, Coder) via LangGraph. Features high-performance FastAPI backend, Redis-powered caching, real-time thought streaming, multimodal support, and detailed per-model cost analytics.

A multi-agent Business Intelligence system built with LangGraph and Google Gemini. Three collaborative AI agents — Planner, Researcher, and Writer — work in sequence to produce comprehensive business intelligence briefs on any company or market. Backend deployed on Render.

AI Researcher is a platform that leverages advanced AI models to handle complex research queries, featuring a backend agent for processing and a Next.js-based frontend for user interaction. It integrates CopilotKit for real-time updates and LangGraph for structured workflow management.

A unified Computational Research Platform monorepo using a production-grade architecture (Turborepo). It organizes Apps (Next.js UIs), Packages (shared logic), Agents (LangGraph logic), and Services (MCP backends) to automate user insight and alignment at scale.

Agentic AI Chatbot is a production-ready framework combining Streamlit UI with a LangGraph backend to build intelligent, tool-using AI agents. It supports parallel workflows and modular node design for scalable conversational automation. Ideal for real-world industry, research, or freelance AI solutions.

AgnesOps is a multi-agent RaaS (Research-as-a-Service) backend built on OpenClaw and LangGraph. Using Agnes-1.5-Pro, a Coordinator decomposes user goals into tasks for Research, Writer, and Critic agents. It features a score-gated revision loop, 24/7 cloud execution via Telegram, and persistent memory—all without a web frontend.

AI-powered full-stack Blog Writing Agent with a React frontend and FastAPI backend. Generates research-backed technical blogs using LangGraph workflows, live progress streaming, evidence collection, markdown preview, image support, MongoDB persistence, and Cloudinary-ready media handling.

A live-deployed, asynchronous LangGraph agent that fully automates deep web research. Hosted on a decoupled Render backend, the agent executes recursive, self-correcting scraping loops, integrates human-in-the-loop feedback, and bypasses client wait times by asynchronously emailing structured PDF reports directly to your inbox.

A multi-agent, citation-aware research system that plans, delegates, reflects, and synthesizes high-quality reports in real time. This project combines a FastAPI + LangGraph backend with a modern Next.js interface to deliver an end-to-end research workflow: from user query to structured, source-backed final report.

A Deep Research Agent that orchestrates in-depth web research on any topic. Built on LangGraph with 5 search providers, three-tier LLM hierarchy, iterative self-critique, fact-checking, and PDF/MD/JSON export. FastAPI backend streams real-time progress to a React frontend with follow-up RAG chat.