← BACK TO PROJECTS
PROJECT [01]

ICCN AI Agent Implementation

MULTI-AGENT / RAG SYSTEM
TYPEMULTI-AGENT / RAG SYSTEM
STATUSPRODUCTION
YEAR2026
STACKPython / LangGraph / Tavily / Redis / Multi-Model LLMs
ICCN CHATBOTType "ramalan karir" to access the gamification data collector.
AI RESEARCH AGENTLogin required to access the AI Research Agent dashboard.
VIDEO COMING SOON
PROJECT PREVIEW

The ICCN AI Agent Implementation consists of two major sub-projects: an AI Research Agent and a Ramalan Agent (Gamification Data Collector), both designed to serve the needs of the ICCN organization.

The AI Research Agent leverages LangGraph's multi-step reasoning with the ReAct paradigm, integrated with Tavily for real-time web research. It automates the synthesis of comprehensive Markdown reports with citations, working across multi-model LLMs for optimal results in different reasoning tasks.

The Ramalan Agent is a gamified task-oriented agent designed for user profiling and data collection. It uses Redis for session management across multi-turn conversations and implements async background tasks for UI responsiveness, creating an engaging experience for users while gathering valuable data.

  • Python
  • LangGraph
  • LangChain
  • Tavily Search API
  • Redis
  • FastAPI
  • Amazon Bedrock