Data engineering is shift from “building tables & pipelines” to “building scoped, domain-aware subagents for DA/business users.

LLMs hallucinate without context, and data engineers are buried in repetitive queries and validations. Datus builds a context engine — combining metadata, metrics, SQL history, and external knowledge into a unified agent environment.

A feedback-driven learning loop continuously evolves both the context and the model. Each subagent serves as an ideal environment for reinforcement learning, since NL2SQL tasks provide clear rewards — but the real challenge lies in defining the right scoped environment, and that’s where Datus excels.

See more : https://docs.datus.ai/

DatusAI

Org chart

Teams

Offices