Vectorless RAG vs every flavour of vector RAG: a head-to-head on real 10-Ks.

1. 1Build a vectorless RAG pipeline using a suitable library
2. 2Run the pipeline on a dataset of 10-K financial reports
3. 3Configure and test multiple vector RAG pipelines with different settings
4. 4Compare the performance of each pipeline on a set of 54 finance questions
5. 5Apply the results to select the most suitable RAG pipeline for financial analysis tasks

Machine learning engineers and data scientists can benefit from this comparison to choose the best RAG pipeline for their financial analysis tasks

💡 Vectorless RAG and vector RAG pipelines have different strengths and weaknesses when applied to real-world financial data

💡 Vectorless RAG vs vector RAG: which one performs better on real 10-K financial data?