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Preparing Enterprise Data for AI
AI initiatives depend on consistent, governed, high-quality master data. Without trusted core entities, AI models amplify data inconsistencies rather than solve them.
How Agentic Master Data Management Works
Why AI Fails in the Enterprise
Enterprise AI projects fail when:- Customer and product records are fragmented
- Entity relationships are unclear
- Governance policies are inconsistent
- Data quality is unstable
AI systems require stable master data foundations.
The Hidden Cost of Poor Master Data
Poor master data leads to:- Operational inefficiency
- Compliance risk
- Failed AI pilots
- Duplicated effort across departments
AI Requires Continuously Managed Master Data
AI readiness requires:- Resolved core entities
- Governance enforcement
- Continuous monitoring
- Cross-system consistency
This is achieved through Agentic Master Data Management.
How CluedIn Enables AI-Ready Master Data
CluedIn delivers continuously managed, graph-native master data infrastructure designed to support enterprise AI and advanced analytics initiatives. See how to modernise your MDM architecture.
Enterprise data challenges solved.
The resource drain
Challenge: Data teams spend most of their time cleaning and maintaining data.
CluedIn: Agents automate the grunt work - detect, fix, enrich - so teams focus on strategy.
Free your experts to deliver insight, not maintenance.
Scale without scale
Challenge: Manual data management can’t keep up with business or AI velocity.
CluedIn: CluedIn Agents handle millions of records in parallel - continuously improving quality and context.
Scale 100x faster without scaling headcount.
Fragmented systems, fragmented truth
Challenge: Data lives across clouds and apps, breaking consistency and governance.
CluedIn: Agents unify and govern data across all platforms - enforcing global rules locally.
A single, trusted layer across your data landscape.
Rising cost, falling ROI
Challenge: Traditional MDM is expensive and slow to prove value.
CluedIn: Autonomous Agents deploy in minutes and cost cents per run.
$0.13 vs $1,000 per job - measurable impact from day one.
Governance at scale
Challenge: Automation often introduces compliance risk.
CluedIn: CluedIn Agents are governed by design - every action is logged and explainable.
Autonomous, auditable, and compliant by default.
Data quality blind spots
Challenge: Even ‘good’ data hides silent errors that undermine AI.
CluedIn: Agents continuously validate, enrich, and learn from feedback.
Data that gets smarter every day - and AI you can trust.
The AI readiness gap
Challenge: AI fails without complete, current, trusted data.
CluedIn: Agents continuously prepare and enrich data to feed copilots and models.
AI that performs as promised - powered by data you can depend on.