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Next-Level Accuracy with Astra DB Hybrid Search and NVIDIA AI
Join DataStax for the DataStax Astra DB Hybrid Search product launch livestream on April 16th.
AI-powered applications live or die by Retrieval Accuracy. DataStax’s Hybrid Search with NVIDIA’s Reranker puts AI directly into Retrieval. This new approach to search retrieval changes the game on relevancy: Using an LLM to determine the most accurate result delivers up to 45% better accuracy over traditional methods, and Astra DB lets you combine AI-powered and classic search for best-in class RAG accuracy.
Hybrid Search combines the best of BM25 lexical search, vector search, and NVIDIA NeMo Retriever reranking to deliver more relevant results—all in one place.
Designed for developers and IT leaders, this session will dive into why hybrid search and auto-reranking are game changers for retrieval-augmented generation (RAG) agents—and what’s at stake if you don’t use them.
What Problems Does This Solve?
Precision & Recall Boost – Hybrid search combines BM25 keyword matching with vector search, ensuring both relevance and contextual depth.
AI That Actually Understands Your Data – NVIDIA NeMo Retriever & Reranker elevate search accuracy by up to 45%, ensuring your AI retrieves and ranks the most contextually relevant results.
Scalability & Performance – DataStax Astra DB delivers sub-millisecond latency, supporting enterprise-grade AI at scale.
Enterprise-Ready AI Performance – Astra DB delivers low-latency hybrid search at scale, while MongoDB and others struggle with performance bottlenecks in high-query environments.
Hybrid Search Make Easier – With Langflow, developers can easily change and optimize state-of-the-art search accuracy for AI-driven applications with minimal code changes and no vendor lock-in.
How It Works:
Hybrid retrieval: Combines BM25 lexical search with vector search.
Smarter ranking: NVIDIA NeMo Retriever Reranking intelligently reorders results using fine-tuned LLMs.
Easy integration: Use Astra DB’s Python client and schema-less Data API for a smooth development experience.
Discover how DataStax, NVIDIA, and BM25-powered hybrid search can supercharge your AI applications and give your RAG agents an unparalleled accuracy edge. Register now and take your AI search to the next level!
Livestream Resources:
Talk to an AI Expert: dtsx.io/3YA7GNv
Hybrid Search Blog: dtsx.io/4jl1di4
Hybrid Search Press Release: dtsx.io/4il6NzE
Additional Resources:
- DataStax Developer Hub: https://dtsx.io/devhub
- DataStax Blog: https://dtsx.io/howto
- Try Langflow: https://dtsx.io/trylangflow
- Try Astra DB: https://dtsx.io/40kQpI6
____________________
Stay in touch:
- Join our Discord Community: https://discord.gg/datastax
- Follow us on X: https://x.com/DataStaxDevs
Видео Next-Level Accuracy with Astra DB Hybrid Search and NVIDIA AI канала DataStax Developers
AI-powered applications live or die by Retrieval Accuracy. DataStax’s Hybrid Search with NVIDIA’s Reranker puts AI directly into Retrieval. This new approach to search retrieval changes the game on relevancy: Using an LLM to determine the most accurate result delivers up to 45% better accuracy over traditional methods, and Astra DB lets you combine AI-powered and classic search for best-in class RAG accuracy.
Hybrid Search combines the best of BM25 lexical search, vector search, and NVIDIA NeMo Retriever reranking to deliver more relevant results—all in one place.
Designed for developers and IT leaders, this session will dive into why hybrid search and auto-reranking are game changers for retrieval-augmented generation (RAG) agents—and what’s at stake if you don’t use them.
What Problems Does This Solve?
Precision & Recall Boost – Hybrid search combines BM25 keyword matching with vector search, ensuring both relevance and contextual depth.
AI That Actually Understands Your Data – NVIDIA NeMo Retriever & Reranker elevate search accuracy by up to 45%, ensuring your AI retrieves and ranks the most contextually relevant results.
Scalability & Performance – DataStax Astra DB delivers sub-millisecond latency, supporting enterprise-grade AI at scale.
Enterprise-Ready AI Performance – Astra DB delivers low-latency hybrid search at scale, while MongoDB and others struggle with performance bottlenecks in high-query environments.
Hybrid Search Make Easier – With Langflow, developers can easily change and optimize state-of-the-art search accuracy for AI-driven applications with minimal code changes and no vendor lock-in.
How It Works:
Hybrid retrieval: Combines BM25 lexical search with vector search.
Smarter ranking: NVIDIA NeMo Retriever Reranking intelligently reorders results using fine-tuned LLMs.
Easy integration: Use Astra DB’s Python client and schema-less Data API for a smooth development experience.
Discover how DataStax, NVIDIA, and BM25-powered hybrid search can supercharge your AI applications and give your RAG agents an unparalleled accuracy edge. Register now and take your AI search to the next level!
Livestream Resources:
Talk to an AI Expert: dtsx.io/3YA7GNv
Hybrid Search Blog: dtsx.io/4jl1di4
Hybrid Search Press Release: dtsx.io/4il6NzE
Additional Resources:
- DataStax Developer Hub: https://dtsx.io/devhub
- DataStax Blog: https://dtsx.io/howto
- Try Langflow: https://dtsx.io/trylangflow
- Try Astra DB: https://dtsx.io/40kQpI6
____________________
Stay in touch:
- Join our Discord Community: https://discord.gg/datastax
- Follow us on X: https://x.com/DataStaxDevs
Видео Next-Level Accuracy with Astra DB Hybrid Search and NVIDIA AI канала DataStax Developers
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17 апреля 2025 г. 9:56:12
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