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How it works

Three layers.
One platform.

Relium combines metadata inspection, SQL lineage analysis, and risk detection to catch data quality issues before they reach dashboards.

STEP 01

Inspect Metadata

Track schema, row counts, NULL rates, and freshness across all tables and models.

STEP 02

Detect Anomalies

Compare current metrics against learned baselines to spot unexpected changes.

STEP 03

Analyze SQL Risk

Parse SQL to identify join logic, filter placement, and cardinality issues.

STEP 04

Trace Lineage

Map which models depend on affected tables and what downstream impact matters most.

STEP 05

Create RCA Report

Correlate symptoms and generate root cause analysis with evidence and remediation paths.

Core Capabilities

Baseline Learning

Relium learns normal behavior from historical metrics. You set the sensitivity — we do the anomaly detection.

Pattern Recognition

SQL Risk Detection

Parse dbt models and raw SQL to flag risky patterns: implicit JOINs, INNER vs LEFT mismatches, complex subqueries.

Code Analysis

Incident Correlation

When a source table breaks, we automatically find all downstream models affected and group them into one incident report.

Graph Lineage

AI-Powered Explanations

Optional integration with Groq or OpenAI for natural-language root cause hypotheses and remediation suggestions.

Optional LLM