Build Your Own Perplexity in 15 Minutes With Supermemory

A tutorial demonstrates how to build a simplified, memory-enhanced web search assistant inspired by Supermemory’s OpenSearch AI in roughly 30 minutes. The application combines Supermemory’s API to store and retrieve relevant past queries and generated answers, Brave Search API to obtain current web results, and OpenAI’s GPT model to synthesize both sources into concise responses with links. Its Express backend accepts a question, saves it as memory, retrieves the three most relevant memories, searches the web, selects useful snippets, prompts the model with the combined context, saves the resulting answer, and returns all data to the client. A minimal frontend built with plain HTML, CSS, and JavaScript submits queries, safely renders Markdown answers, and displays search results alongside related memories. The project is intended as an accessible demonstration rather than a production-ready system, emphasizing how managed memory APIs can reduce the complexity of creating context-aware AI applications.

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