Data Governance Intelligence
Your AI is only as good as your data. Get a readiness score across six factors and know exactly what to fix before you build.
57%
of organizations say their data isn't AI-ready
Gartner, 2025
65%
of stalled AI projects cite data as the blocker
S&P Global / Gartner, 2025
2026
New AI data-governance rules taking effect across major markets
EU AI Act · US state AI laws
Six factors of readiness
Accurate, complete, and free of errors that compromise AI output
Meaning is explicit. No tribal knowledge required for AI to understand
Right format, right latency for RAG, training, and inference
Freshness enforced by infrastructure, not assumed by convention
Traceable from source to every AI decision it informs
Governed with enforced access, classification, and AI-specific safeguards
Compliance coverage
Select the frameworks your organization tracks, and every assessment maps its findings to that framework's data-governance expectations: the evidence already in place, and the gaps to close. Readiness to produce evidence, never a certification claim.
How it works
Connect
Add read-only credentials for BigQuery, Snowflake, Databricks, PostgreSQL, Redshift, or Microsoft Fabric. We only query catalog metadata, with no access to your actual data.
Assess
We scan your schema against 8-50 requirements across 6 factors, tailored to your AI workload: RAG, agents, training, or feature serving.
Improve
Get prioritized recommendations. Each one tells you what to fix, which factor it improves, and the estimated score gain.
Built to be trusted with production data
Security details →Read-only metadata
We query INFORMATION_SCHEMA only. Connect with a metadata-viewer role, nothing more.
We never read your data
No SELECT against your tables, ever. We can't see a single row, value, or query result.
Encrypted credentials
Saved connections are encrypted at rest (AES-256-GCM) with the key held outside the database.
Your data isn't training
Findings go to our AI provider as assessment results: scores and the metadata they cite, never your data values or credentials. They're never used to train models.
Don't want to connect anything yet? Run the same scan locally with the open CLI: credentials never leave your machine, and --html writes a report you can share internally. No account needed.
Platforms
AWS: Amazon Redshift natively; Amazon RDS and Aurora PostgreSQL through the PostgreSQL connector; Databricks on AWS through the Databricks connector.
Google Cloud: BigQuery natively; Cloud SQL for PostgreSQL through the PostgreSQL connector; Databricks on GCP through the Databricks connector.
Azure: Microsoft Fabric natively; Azure Databricks through the Databricks connector; Azure Database for PostgreSQL through the PostgreSQL connector.
Snowflake runs on all three clouds with the same connector, and managed PostgreSQL services (Neon, Supabase, Railway, Heroku) connect through the PostgreSQL connector.
Pricing
Start free. Pay when the fixes are worth it. No credit card to try.
Free
$0
See where you stand
Pro
$149/mo
Know what to fix
Team
$499/mo
Run it as a program
Enterprise
Let's talk
Prove it to auditors
A readiness assessment from a consultant runs ~$50–100K and six weeks. MortarIQ runs in minutes, repeats whenever you want, and starts free.
Maps assessment results to compliance frameworks to help you prepare evidence for: