Category: Artificial Intelligence (AI)
A Benchmark for Evaluating NL2SQL++ Systems
In the modern data ecosystem, natural language to code capabilities are becoming paramount, with JSON rapidly emerging as the lingua franca for communication with large language models (LLMs). At Couchbase, we work with this knowledge to provide our customers with...
What Is an AI-Powered Recommendation Engine?
Learn how AI recommendation engines work, key algorithms, real-world use cases, and best practices for building scalable, personalized experiences.
An Overview of Vision Language Models (VLMs)
Learn what vision language models are, how they work, key use cases, challenges, and why they matter for multimodal AI.
PatientIQ: Building a Patient 360 on Couchbase
What Is PatientIQ and Why Build it? PatientIQ is an agentic patient 360 built using Couchbase Capella AI Services. It is one example of a solution to a problem that we are trying to solve. For PatientIQ, it began with...
A Breakdown of Graph RAG vs. Vector RAG
Explore the differences between graph RAG and vector RAG, how each enhances retrieval-augmented generation, and which suits your AI use case best.
Optimizing Multi-Agent AI Systems With Couchbase
In a previous post, Building Multi-Agent AI Workflows With Couchbase Capella AI Services, we explored how collaborative AI agents can be designed and orchestrated using Capella AI Services, Vector Search, and RAG patterns. As AI systems move from experimentation into...
AI in Customer Service: Benefits, Examples, Use Cases
AI in customer service boosts efficiency, personalization, and satisfaction. Explore key benefits, real-world examples, and top use cases.
What Are My AI Agents Doing? How to Gain Insight and Control.
AI agents are no longer simple chatbots – they’re autonomous problem solvers. They call tools, orchestrate workflows, and can make decisions on behalf of users. That power can unlock huge value, but it also raises a hard question: when something...
Codelab: Building an AI Agent With Couchbase AI Services & Agent Catalog
In this CodeLab, you will learn how to build a Hotel Search Agent using LangChain, Couchbase AI Services, and Agent Catalog. We will also incorporate Arize Phoenix for observability and evaluation to ensure our agent performs reliably. This tutorial takes...
CodeLab: Building a RAG Application With Couchbase Capella Model Services and LangChain
In this tutorial, you will learn how to build a retrieval-augmented generation (RAG) application using Couchbase AI Services to store data, generate embedding using embedding models, and LLM inference. We will create a RAG system that: Ingests news articles from...
Capella AI Services: Build Enterprise-Grade Agents
Production-Ready AI Agents Building agentic AI applications that can make real business decisions is a complex undertaking. Developers often find themselves juggling multiple disparate tools to manage different data types, ensure data privacy, and maintain control over a rapidly evolving...
Enterprise AI: The Ecosystem Behind Couchbase AI Services
Powering Enterprise-Ready Agentic AI with Security, Governance, and End-to-End Innovation As we announce the General Availability of Couchbase AI Services, we’re also taking a significant step toward enabling enterprise-grade agentic AI by growing and developing the Couchbase AI Partner Ecosystem....
Top Posts
- Data Modeling Explained: Conceptual, Physical, Logical
- What are Embedding Models? An Overview
- Data Analysis Methods: Qualitative vs. Quantitative Techniques
- What Is Data Analysis? Types, Methods, and Tools for Research
- Application Development Life Cycle (Phases and Management Models)
- What are Vector Embeddings?
- Data Normalization vs. Denormalization Comparison
- The Importance of Data Preprocessing in Machine Learning (ML)
- High Availability Architecture: Requirements & Best Practice...
