Own your data. Own your AI.

Zen 17 AI brings native vector search, semantic retrieval, and AI agent connectivity directly into your embedded database. No cloud dependency, no separate infrastructure.

Zen 17 AI
Build with Zen 17 AI

KI entwickeln, ohne die Komplexität zu erhöhen

Modernize your applications with AI using native vector support built directly into Actian Zen — the embedded database your applications already run on.

Store embeddings alongside your existing relational and document data. No need to provision, manage, or sync a separate vector store.

Run similarity search and hybrid queries using standard SQL. No new APIs or tools to learn. It works with the skills and stack your team already has.

RAG pipelines, semantic search, recommendations, and anomaly detection work in embedded, edge, and air-gapped environments. No cloud dependency, no stitching results in application code.

Connect Zen directly to Claude, ChatGPT, and other AI apps via the built-in MCP Server. Out-of-the-box integration with OAuth 2.0 security with no custom connectors required.

Sensitive data stays where it is created, searched, and acted on. Lower architecture overhead, less data movement, and no cloud dependency — built for regulated and privacy-sensitive environments.

Why Actian Zen for AI

Most AI stacks require adding a separate vector database, syncing data across systems, and managing new cloud infrastructure. Zen 17 AI collapses that complexity into the embedded engine your applications already trust.

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A lightweight database with native vector search and MCP Server.

Native vector search, SQL-accessible hybrid queries, and MCP Server support added to the Zen embedded engine. Relational data, metadata, and vector embeddings in one lightweight, zero-admin database.

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One engine for relational and vector search, anywhere your app runs.

RAG, semantic search, recommendations, and anomaly detection work in embedded, edge, and air-gapped environments. No extra infrastructure, no stitching results together in application code.

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AI-powered hybrid search where the data lives, without the complexity.

Lower architecture overhead, less data movement, and no cloud dependency. Sensitive data stays close to where it's created, searched, and acted on.

Was Sie bauen können

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Semantic search

Search documents and knowledge bases by meaning, not exact keywords across millions of records without keyword matching constraints.

Integrationen

RAG pipelines

Build Retrieval-Augmented Generation applications with your own private data, running entirely on-premises or at the edge.

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Empfehlungen

Personalize recommendations using contextual signals from past interactions, stored and retrieved directly from Zen.

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Anomalieerkennung

Identify hidden patterns and outliers using vector similarity without transferring data to a cloud analytics platform.

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Hybride Suche

Combine keyword and semantic search in a single SQL query. No result stitching, no dual-database architecture.

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AI agent memory

Give your AI agents secure, low-latency local context directly from Zen via the native MCP Server.

Entwickelt für Entwickler

Zen 17 AI integrates into the stacks and workflows developers already use.

Nehmen Sie am Early-Access-Programm teil

Test Zen 17 AI in your own environment, with your own data and use case. Be among the first to build with vector search and MCP Server connectivity in Actian Zen.

Request Early Access

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