Speedrun Your RAG: Build an AI Recommender for your Steam Library

Machine Learning Tech Brief By HackerNoon

This story was originally published on HackerNoon at: https://hackernoon.com/speedrun-your-rag-build-an-ai-recommender-for-your-steam-library.
Build a Steam game retriever with Superlinked and LlamaIndex. Use the official SuperlinkedRetriever to add fast, accurate RAG search to your app.
Check more stories related to machine-learning at: https://hackernoon.com/c/machine-learning. You can also check exclusive content about #ai, #artificial-intelligence, #gaming, #rag, #machine-learning, #hackernoon-top-story, #good-company, #ai-recommender-steam-library, and more.
This story was written by: @superlinked. Learn more about this writer by checking @superlinked's about page, and for more stories, please visit hackernoon.com.
Custom retrievers give you control over domain context, metadata, and ranking logic. They outperform generic similarity search when queries are messy or jargon heavy. Superlinked combines multiple text fields into one semantic space and runs queries in memory for snappy results. LlamaIndex provides the clean retriever interface and plugs straight into query engines and response synthesis. There is an official Superlinked retriever integration for LlamaIndex that you can import and use.