Build fast, production-worthy AI apps with Spring AI and Redis
Blog post from Redis
This post showcases how to use Redis in Spring AI 1.0, a comprehensive solution for AI engineering in Java, to build fast and efficient AI apps that scale. The integration of Redis with Spring AI enables developers to leverage the power of vector storage, retrieval augmented generation, and Model Context Protocol (MCP) support. With this setup, developers can create AI-powered applications that can process large amounts of data efficiently, making it an ideal solution for various use cases such as chatbots, content moderation, and more.
| Trend | Post Mentions | Total Month Mentions | Posts | Companies | MoM |
|---|---|---|---|---|---|
| MCP | 8 | 2,993 | 206 | 96 | -12% |
| RAG | 4 | 899 | 167 | 74 | -45% |
| Vector Search | 4 | 1,624 | 285 | 110 | -19% |
| LLM | 2 | 3,765 | 540 | 172 | -11% |
| Observability | 1 | 1,696 | 379 | 123 | -20% |
Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.