Scaling Retrieval Augmented Generation with RAG Fusion: Lessons from an Industry Deployment
Scaling Retrieval Augmented Generation with RAG Fusion: Lessons from an Industry Deployment explores Optimize RAG pipelines by considering production constraints on retrieval and re-ranking budgets.. Commercial viability score: 5/10 in Retrieval Augmented Generation.
BUILDER'S SANDBOX
Build This Paper
Use an AI coding agent to implement this research.
OpenAI CodexAI Agent
Lightweight coding agent in your terminal.
Claude CodeAI Agent
Agentic coding tool for terminal workflows.
AntiGravity IDEScaffolding
AI agent mindset installer and workflow scaffolder.
CursorIDE
AI-first code editor built on VS Code.
VS CodeIDE
Free, open-source editor by Microsoft.
Recommended Stack
Startup Essentials
Estimated $9K - $13K over 6-10 weeks.
See exactly what it costs to build this -- with 3 comparable funded startups.
7-day free trial. Cancel anytime.
Discover the researchers behind this paper and find similar experts.
7-day free trial. Cancel anytime.
Related Papers
- Builds On ThisBeyond Relevance: On the Relationship Between Retrieval and RAG Information CoverageViability: 4.0
- Builds On ThisRetrieval Improvements Do Not Guarantee Better Answers: A Study of RAG for AI Policy QAViability: 4.0
- Prior WorkRevisiting RAG Retrievers: An Information Theoretic BenchmarkViability: 5.0
- Prior WorkConnect the Dots: Knowledge Graph-Guided Crawler Attack on Retrieval-Augmented Generation SystemsViability: 5.0
- Prior WorkComprehensive Comparison of RAG Methods Across Multi-Domain Conversational QA