The Data Agent Access Layer: Finding the Right Data Before Querying
A practical design for source registration, asset discovery, policy filtering, context packaging, runtime authorization, and access-layer evaluation.
Knowledge path
Tech
Architecture, semantics, tool use, evaluation, security, and production patterns for trustworthy Data Agents.
DataAgentX Tech explains the systems behind reliable agentic data work—from the semantic layer and execution harness to observability, evaluation, and human control.
A Seven-Layer Architecture for Production Data Agents
A practical architecture for turning an ambiguous business question into a governed, testable chain of semantics, planning, execution, verification, and delivery.
Data Agent Levels L0–L5: Autonomy Transfers Responsibility
A practical reading of Data Agent levels through initiation, planning, execution, verification, and recovery—not tool count or marketing claims.
Five Data Agent Routes: Compare Products by the Work They Own
A practical taxonomy for comparing Data Agents across business Q&A, analysis, data science, multimodal research, and data engineering.
The SQL Ran. Why Is the Answer Still Wrong?
A successful query is not necessarily a defensible business answer. This guide covers semantic, grain, time, status, and version errors—and a practical trust chain.
What Is a Data Agent? Four Practical Tests
A data agent is more than a chatbot that writes SQL. Four practical tests—real environments, multi-step execution, verification, and governance—define its production boundary.