Category: Agentic AI Applications
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Securing Agentic/RAG Pipelines with Fine-Grained Authorization
Over the previous 3 years, the AI landscape has gone through a massive transformation. We’ve gone from basic language models to full-fledged AI Agents that can take action on our behalf in just a…
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Building Smarter Agents: How Vector Search Drives Semantic Intelligence
The way we search and interact with information has shifted dramatically over the past decade. Traditional keyword-based search engines once served us well in finding documents or answers, but today’s business challenges demand much…
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Announcing Couchbase Support in Google’s MCP Toolbox for Databases
Unlock real-time access for AI agents with SQL++ and the Model Context Protocol (MCP) As autonomous AI agents become more powerful and pervasive, developers need ways to securely and reliably connect these agents to…
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Polaris: AI-Powered Conversational Data Intelligence for the Enterprise Through a Multi-Agent Architecture
In today’s fast-paced environment, the ability to swiftly access, understand, and act upon data is no longer a luxury , it’s a necessity. However, many organizations find that while they are rich in data, deriving…
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Why You Only Need Couchbase When Building Your Agents
Agents are intelligent systems powered by large language models (LLMs) that can autonomously perform tasks, make decisions, and interact with users or other systems. Unlike traditional software, agents can understand natural language inputs, determine…
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AI Agents: The Protocol Revolution Driving Next-Gen Enterprise Intelligence
As protocol standards mature, are enterprises ready for agentic AI? There has been significant progress in AI in terms of generative AI (GenAI), agentic AI and growing interest in physical AI. While hardware, software,…
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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…
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Introducing Model Context Protocol (MCP) Server for Couchbase
The cornerstone of autonomous AI Agentic systems and GenAI applications is an “Augmented LLM”, which is defined as an LLM enhanced with augmentations from various data sources and knowledge bases. Since its introduction, there…
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Couchbase Partners with Arize AI to Enable Trustworthy, Production-Ready AI Agent Applications
As enterprises look to deploy production-ready AI agent applications, Large Language Model (LLM) observability has emerged as a critical requirement for ensuring both performance and trust. Organizations need visibility into how agents interact with…
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Self-Hosted AI Chatbots with Docker and Couchbase Capella
AI chatbots have become an essential tool for businesses and organizations. But most chatbot solutions depend on cloud-based models that introduce latency, API limitations, and perhaps most importantly, privacy concerns. What if you could…
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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…
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Couchbase + Dify: High-Power Vector Capabilities for AI Workflows
We’re excited to announce the new integration between Couchbase and Dify.ai, bringing Couchbase’s robust vector database capabilities into Dify’s streamlined LLMops ecosystem. Dify empowers teams with a no-code solution to build, manage, and deploy…