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AI Education Agent

Transforms education course content into a conversation experience and a Slide bullet points

The AI Education Agent app: a chat conversation on the left and a generated slide on the right

The project was born from a desire to make learning complex subjects like Machine Learning more interactive and visually intuitive. Standard LLM interfaces often provide walls of text that can be overwhelming. This project aims to bridge that gap by combining a conversational AI tutor with a dynamic visualization canvas that renders concepts in real-time.

Conversational AI Tutor

RAG Agent that collects knowledge from provided learning materials. Knowledge source can be any reliable source in text format from school or education providers. The Agent is built on Langflow and powered by OpenAI LLM.

The Langflow graph wiring the retrieval agent together
A chat response from the tutor explaining a machine learning concept
A generated slide summarising the explanation as bullet points
A second generated slide continuing the explanation

Dynamic Visualization Canvas

A dedicated side panel that creates Slide of bullet points based on the AI’s explanation. A student can read the explanation in a better visual than a wall of text.

System Flow

System flow diagram: learning materials feed the Langflow RAG agent, which returns a chat answer and a slide

Technology Stack

Technology stack diagram covering Langflow, OpenAI, Antigravity and Figma

Project Demo

Project Information

Role:

AI Product Designer

Project Status

Personal Project

Timeline:

February 2026

Tools / Technology:

Langflow, OpenAI, Antigravity, Figma

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