Context stuffing is a massive drain on resources and increases your cost per query. It is a messy way to handle large datasets when you need fast and relevant answers.
Vector search with Qdrant offers a more technical and cost effective alternative. By building a proper retrieval pipeline, you can get better results without the overhead. Here is what this workflow covers:
- Moving from context stuffing to vector search for 25x lower costs
- Implementing chunking strategies that actually work for your data
- Setting up embedding scripts and retrieval logic
- Using a debug panel for local testing and deployment
Check out the full technical write-up to see how to deploy this pipeline on Upsun:
Building a RAG pipeline with Qdrant on Upsun - Upsun Developer
Replace context stuffing with vector search using Qdrant for 25x lower cost per query.
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