Join us at
Gartner Data & Analytics
Summit 2026
Experience the Future of Data Observability, Quality and Context
Discover how leading data teams are moving from reactive monitoring to AI-driven intelligent data operations. Meet the team behind PRIZM, the industry’s first AI-native platform where Data Observability, Data Quality, and Context work together as one system.
The Shift Toward
Self-Driving Data Platform
PRIZM by DQLabs brings autonomous intelligence to data observability, quality and context.
Experience Self-Driving Data Observability, Quality and Context at Booth 316
See PRIZM in Action
See how PRIZM uses AI agents & semantic intelligence to:
- Detect anomalies before they disrupt analytics or AI
- Automatically trace issues across the entire data lineage
- Reduce alert noise with signal-based intelligence
- Turn data observability and quality into autonomous operations
Meet With Our Experts
Our team will showcase how organizations are using PRIZM to:
- Improve trust in business data
- Accelerate analytics and AI initiatives
- Reduce time spent investigating data issues
- Build resilient, AI-ready data platforms
Why Data Leaders Are Exploring PRIZM
Modern data ecosystems are growing rapidly, but traditional monitoring tools weren't designed for AI-scale complexity. PRIZM brings a fundamentally new approach.
- Data Observability
- Data Quality
- Data Context
— into a unified, AI-native platform that helps enterprises detect, understand, and resolve data issues intelligently.
An Insightful Theater Session Awaits You
Raj Joseph
Founder and CEO,
DQLabs, Inc.
Prizm by DQLabs: The AI-Native Platform for
AI-Ready Data
Experience PRIZM’s Impact Across Data Roles
Register Now
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Data Engineers
Build and operate adaptive, AI-orchestrated data systems without constant firefighting.
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Data Stewards
Move beyond manual checks to semantic intelligence that guides machine understanding at scale.
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Data Consumers
Trust dashboards, analytics, and AI outputs with reliable, AI-ready data.
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Data Leaders
Drive enterprise AI transformation with governed, observable, and trustworthy data foundations.
