Elementary AI Agent
Elementary’s AI agents run continuously on your data platform — triaging incidents, recommending tests, classifying assets, and surfacing performance issues. They’re powered by the Context Engine, which maps your entire stack from ingestion through transformations to BI.AI Agent Overview
What the agents do, how they work, and how to get started.
Context Engine
The knowledge layer that powers all agents — lineage, metadata, test results, and execution history unified.
Triage & Resolution Agent
Investigates root cause, assesses blast radius, and suggests a fix — automatically when an incident opens.
Test Recommendation Agent
Analyzes your data and usage patterns to recommend the right tests for untested assets.
Governance Agent
Identifies undocumented assets, assigns owners, and generates descriptions — synced back to your dbt project.
Performance & Cost Agent
Surfaces slow models, redundant tests, and expensive queries with specific optimization recommendations.
Data Tests
Cloud Tests
ML-powered freshness and volume anomaly detection that runs automatically — no configuration needed to get started.
dbt Tests
All dbt, dbt-utils, dbt-expectations, and Elementary package tests appear in Elementary automatically with no extra setup.
Schema Validation
Detect schema changes that break downstream consumers — tables, JSON fields, and BI dashboards.
Test Coverage
Visual map of coverage gaps across your stack. Add tests from the UI or use the Test Recommendation Agent.
Data Lineage
Lineage Graph
Full-stack lineage from ingestion sources through dbt models, Python pipelines, and BI tools — enriched with monitoring results.
Column-Level Lineage
Trace individual columns across transformations to pinpoint root cause and understand blast radius.
Snowflake Semantic Views
Discover and trace lineage through Snowflake Semantic Views — metrics, dimensions, and facts connected to your physical tables.
Alerts & Incidents
Alerts
Highly configurable alerts routed to any channel — Slack, PagerDuty, email, Jira. Owners tagged automatically.
Alert Rules
Define routing logic to send the right alerts to the right people and channels.
Incidents
Related failures are grouped automatically into a single incident. Manage status and assignees in one place.
Config in Code
Configure owners, subscribers, suppression, and alert properties directly in your dbt project YML.
Performance & Cost
Performance Monitoring
Track execution times, failure rates, and run trends for dbt models and tests over time.
Performance Alerts
Get notified when models or tests breach duration thresholds or start failing unexpectedly.
Data Catalog & Governance
Data Catalog
Search and explore datasets — descriptions, columns, compiled code, lineage, and health status in one place.
Critical Assets
Mark and prioritize your most important tables for tighter monitoring and faster response.
AI Descriptions
Auto-generate column and table descriptions using AI, reviewed and synced back to your dbt project.
Governance Best Practices
Set up ownership, tagging, and accountability across your data assets.
Data Health
Overview Dashboard
Live view of issue status and trends across your platform. Share with stakeholders or embed in your reporting.
Data Health Scores
Track health scores by domain, surface deterioration early, and share progress with your organization.