Eliminating the Precision–Latency Trade-Off in Large-Scale RAG

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Retrieval-Augmented Generation (RAG) systems constantly face a trade-off: Precise results often mean higher latency and cost, while faster responses risk losing context and accuracy. The solution isn’t choosing one or the other. It’s redesigning retrieval. Let’s explore three techniques that together eliminate this trade-off: multiphase ranking, layered retrieval and semantic chunking.

When combined, they create a retrieval stack that balances speed, scalability and precision.

Multiphase Ranking: Incremental Refinement of Results

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Eliminating the Precision–Latency Trade-Off in Large-Scale RAG


Retrieval-Augmented Generation (RAG) systems constantly face a trade-off: Precise results often mean higher latency and cost, while faster responses risk losing context and accuracy. The solution isn’t choosing one or the other. It’s redesigning retrieval. Let’s explore three techniques that together eliminate this trade-off: multiphase ranking, layered retrieval and semantic chunking.

When combined, they create a retrieval stack that balances speed, scalability and precision.

Multiphase Ranking: Incremental Refinement of Results

At the…



Source link

Disclaimer

We strive to uphold the highest ethical standards in all of our reporting and coverage. We StartupNews.fyi want to be transparent with our readers about any potential conflicts of interest that may arise in our work. It’s possible that some of the investors we feature may have connections to other businesses, including competitors or companies we write about. However, we want to assure our readers that this will not have any impact on the integrity or impartiality of our reporting. We are committed to delivering accurate, unbiased news and information to our audience, and we will continue to uphold our ethics and principles in all of our work. Thank you for your trust and support.

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