根据Menlo Ventures数据，51%的企业AI生产部署采用RAG技术，而仅9%主要依赖微调。Actian推出的VectorAI DB是一款专为云访问受限、延迟高或风险大的边缘环境设计的向量数据库。它支持在本地、边缘或物理隔离网络中运行RAG流水线、语义搜索和实时AI智能体，核心优势包括数据保留在内部网络、原生集成LangChain/LlamaIndex、实时索引更新以及混合搜索功能。该产品已通过黑客马拉松验证，应用于海事AI、设备端治疗师等场景，现正式向公众开放。
RAG is how 51% of enterprise AI ships in production according to Menlo Ventures. only 9% rely primarily on fine-tuning.
Actian just launched VectorAI DB, a vector database built for RAG in places where cloud access is too slow, too risky, or not allowed.
VectorAI DB runs RAG pipelines, semantic search, and real-time AI agents on-premises, at the edge, or air-gapped.
- embeddings stay inside your network, queries resolve locally
- LangChain and LlamaIndex integration that connects natively
- real-time indexing keeps context current as documents update
- hybrid search handles semantic and keyword queries in the same call
We're excited to announce VectorAI DB, the first vector database purpose-built for high-performance, reliable AI at the edge. RAG isn't dead. It just can't run in the environments that need it most. In manufacturing, 46% of AI pilots never leave the OT network. Healthcare, defense, and financial services are no different. VectorAI DB runs RAG pipelines, semantic search, and real-time AI agents on-premises, at the edge, or air-gapped. Before today, 1,000+ devs across three hackathons had already built on it. A maritime AI system. An on-device AI therapist. Cardiac imaging on a closed hospital cluster. And these are just a handful of what VectorAI DB makes possible. VectorAI DB is NOW OPEN to the public. Come throw your hardest problem at it. Download link in the comments.在 X 查看被引用的帖子
来源：Rohan Paul · x.com