AI & ML capabilities

Learn how to run AI workloads and work with machine learning and advanced analytics in Exasol.

Exasol is an analytics database built for speed at scale. In this section you will learn how to put AI to work on top of it.

You can connect AI assistants like Claude or ChatGPT to your database through the Exasol MCP Server, run machine learning models directly inside the database with UDFs and Script Language Containers, and call out to foundation models from OpenAI, Anthropic, Google, or Hugging Face from SQL. The same engine that powers your analytics workloads handles AI inference in parallel across the cluster, so text analysis, forecasting, and metadata enrichment run where your data already lives.

Whether you want a natural language interface to your warehouse, in-database ML, or production text analytics, the articles in this section walk you through the setup and the working examples.

In this section

Get started with AI

Learn how to set up the tools and environments you need to run AI workloads.

Query your database with AI

Learn how to use the the Model Context Protocol (MCP) to provide AI assistants direct access to your Exasol database.

Build AI agents with Exasol

Learn how to build AI agents in Exasol with agent skills and MCP server building blocks. Exasol provides two building blocks that bring AI to your data in a controlled, governed way: agent skills (knowledge) and the MCP server (access).

Connect to AI models

Learn how to use in-database models, self-hosted and sovereign cloud models, and cloud API models with your Exasol database. Each path represents a different trade-off between performance, capability, and data control.

Real-world AI applications

Learn how to build real-world applications using Exasol’s AI capabilities. This section includes a production-ready text analysis extension and worked examples that demonstrate specific use cases.

Connect and load data

Learn more about the many ways you can to connect to your Exasol database and load data in these documentation sections.

Other examples and tutorials

Learn through tutorials and examples how to work with machine learning in Exasol.

Resources on GitHub

An index of Exasol repositories on GitHub with resources and documentation related to our AI features.