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What is Datus

The problem, the product, and the thesis behind it.

Data Engineering Agent

The category, the comparisons, and how to build with one — our core cluster.

Semantic Layer

What a semantic layer is, and how it differs from a metric layer, model, ontology, or catalog.

Glossary

Core data engineering terms — defined, with how they connect to agents and context.

Why agents, not copilots

The shift from assistive AI to autonomous data workflows.

Architecture and pipelines

How Datus works under the hood — agent design, storage, ETL, and pipeline automation.

Why context is everything

Semantic models, structured context, and what makes agents reliable.

Tooling and integrations

MCP, extensions, and how agents connect to real data systems.

In practice

Real use cases and how agentic data teams operate.

Releases

Reference

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