The Democratization Paradox
Can't Open Access Without Governance
- ✗No catalog means users can't find the right data
- ✗No quality checks means unreliable insights
- ✗No documentation means constant questions
- ✗Opening access without these = chaos
Can't Build Governance Without Pausing Work
- ✗Cataloging 1000+ tables takes months
- ✗Manual documentation falls behind immediately
- ✗Quality checks require dedicated eng time
- ✗Team still needs to ship features meanwhile
You're stuck between chaos and paralysis
AI Builds Governance as Your Team Works
Don't choose between progress and preparation. Do both simultaneously.
Catalog Builds Itself
As your team queries data, AI documents tables, columns, and relationships automatically. No manual cataloging required.
Quality Verified
Continuous monitoring catches issues before they impact decisions. Quality metrics tracked and validated automatically.
Docs Stay Current
Documentation evolves with your data. Business context captured from actual usage patterns, not stale wiki pages.
Your Path to Safe Democratization
AI Accelerates Your Data Team
Start by making your data team more productive. AI handles repetitive tasks, generates documentation, and monitors quality—all while your team ships features.
What You Get
- • 40% faster development
- • Auto-generated docs
- • Quality monitoring
- • Reduced manual work
What's Building
- • Comprehensive catalog
- • Quality baselines
- • Usage patterns
- • Trust foundation
Catalog & Quality Verified
Your catalog is now comprehensive, your quality baselines are established, and you have full visibility into your data estate. Time to expand access.
What You Have
- • Complete data catalog
- • Quality SLAs defined
- • Lineage tracked
- • Governance in place
Who Can Access
- • Analytics team (self-serve)
- • Power users (guided)
- • Executives (dashboards)
- • Product managers (reports)
Business Users Get AI Assistants
Now that governance is solid, business users can ask questions directly. AI assistants provide answers while respecting permissions and quality guardrails.
What's Possible
- • Natural language queries
- • Self-service analytics
- • Governed data access
- • Instant insights
What's Protected
- • Quality maintained
- • Permissions enforced
- • Usage audited
- • Data team unblocked
What Makes It Safe
Governed Catalog
Every table, column, and metric is documented with ownership, quality scores, and usage guidelines. Users know what data they can trust.
Verified Quality
Continuous monitoring ensures data meets quality SLAs before it's surfaced to users. Bad data gets flagged automatically.
Transparent Queries
Business users see the SQL behind every answer. Data team can audit what questions are being asked and how they're answered.
Permission-Aware
AI respects existing warehouse permissions. Users only see data they're authorized to access—no backdoors.
From 5 Data Users to 50
TechCorp's Journey
A mid-size SaaS company with 300 employees wanted to make data accessible across the organization, but their 5-person data team was already overwhelmed.
Before (6 users accessing data)
- • Data team spent 60% of time answering questions
- • Average question turnaround: 3-5 days
- • No documentation for most tables
- • Quality issues discovered in production
After 9 months (52 users accessing data)
- • Data team spends 15% of time on questions
- • Average question turnaround: 10 minutes (self-serve)
- • 94% of tables documented automatically
- • Quality monitoring catches issues before impact