Category: Search
Unlocking the Power of AWS Bedrock with Couchbase
The explosion of generative AI has made vector databases a crucial part of modern applications. As businesses seek scalable and efficient solutions for AI-powered search, recommendation, and knowledge retrieval, AWS Bedrock and Couchbase emerge as a compelling combination. AWS Bedrock...
Semantic Similarity with Focused Selectivity
Why does semantic search need selectivity? Up until now, we’ve viewed a vector embedding as a complete, stand-alone entity – focused entirely on the meaning it encodes. While this enables semantic search, often with a high degree of similarity, it...
Introducing Couchbase as a Vector Store in Flowise
We’re excited to announce that Couchbase is now officially supported as a vector store in Flowise, providing users with a powerful, high-performance solution for managing and retrieving vector data. This new integration combines Flowise’s intuitive, no-code AI workflow capabilities with...
Build Your First Open Source AI Agent with Couchbase
If 2024 was the year of AI chatbots, then 2025 is the year of AI agents. At first glance, they may seem similar, but nothing could be farther from the truth. While you may interact with an AI agent in...
Extending RAG capabilities to Excel with Couchbase, LLamaIndex, and Amazon Bedrock
As everything around us is gradually becoming more data-driven, Excel is still integral for businesses, providing the capability to provide invaluable insights from the data in the sheets. However, data scientists and analysts agree that extracting meaningful information from these...
Chat With Your Git History, Thanks to RAG and Couchbase Shell
Don’t you love reading other people’s commit messages? No? Well, I do and as I was reading a very insightful commit message, I realized all the untapped content living in various Git logs (assuming the dev you follow are writing...
A Guide to LLM Embeddings
LLM embeddings are numerical representations of words, sentences, or other data that capture semantic meaning, enabling efficient text processing, similarity search, and retrieval in AI applications. They are generated through neural network transformations, particularly using self-attention mechanisms in transformer models...
AI-Ready Data: Automate Embeddings with Capella’s Vectorization Service
Couchbase Capella has launched a Private Preview for AI services! Check out this blog for an overview of how these services simplify the process of building cloud-native, scalable AI applications and AI agents. In our previous blog, we demonstrated how...
DeepSeek Models Now Available in Capella AI Services
Unlock advanced reasoning at a lower TCO for Enterprise AI Today, we’re excited to share that DeepSeek-R1 is now integrated into Capella AI Services, available in preview! This powerful distilled model, based on Llama 8B, enhances your ability to build...
Integrate Groq’s Fast LLM Inferencing With Couchbase Vector Search
With so many LLMs coming out, a lot of companies are focusing on enhancing the inference speeds for large language models with specialized hardware and optimizations to be able to scale the inference capabilities of these models. One such company...
Plataforma única, Couchbase multiuso: Pesquisa vetorial, geoespacial, SQL++ e muito mais
Há casos de uso que são melhor atendidos por vários tipos de acesso a dados, incluindo SQL, pesquisa vetorial, consultas geoespaciais e acesso de valor-chave. Uma abordagem é combinar/encadear vários sistemas de dados para cada método de acesso. No entanto,...
2025 Enterprise AI Predictions: Four Prominent Shifts Reshaping Infrastructure and Strategy
Organizations are moving beyond initial experimentation to implement more sophisticated and practical AI strategies. The trend of simply adopting off-the-shelf AI solutions is giving way to a more nuanced approach, where businesses are carefully balancing the power of large language...