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BACK TO CXV LIFT
Data Lift: A CXV Lift Solution

The 90-Day Path to AI-Ready Data

Ideal for mid-market wholesaler distributors ($50M - $500M revenue) who are looking for scalable foundations.

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THE CHALLENGE

Solving the Data Hurdle

The hurdle for most distributors is not the AI model; it is the data pipeline feeding it. We solve the most common friction points.

THE Hurdle (Before)

The primary barrier to AI adoption isn't the technology—it's the fragmented, inconsistent data trapped in legacy silos.

  • Legacy Silos: Fragmented ERP, WMS, and CRM systems that don't speak the same language.
  • Catalog Chaos: Duplicate SKUs and inconsistent units of measure that break automation.
  • Shadow Data: Fragmented, siloed, and unreliable data streams across the organization.
  • Wasted Spend: High-stakes AI pilots failing due to poor quality data inputs.

THE Solution (After)

Integrātz offers a unified, clean, and AI-ready architecture with fixed scope, fixed price and tangible results.

  • Data Harmonization: Automated synchronization across all disparate sources.
  • Distribution Models: Proprietary schemas built specifically for wholesale distribution.
  • Real-time Visibility: Instant insights into data health, quality, and reliability.
  • Seamless Integration: Plug-and-play compatibility with your current AI and analytics stack.

THE Data (Why)

Without a clean, connected data foundation, even the most advanced systems fail to deliver results. When data is unified and reliable, it becomes the engine of operational velocity, powering predictability, scalability, and long-term advantage.

Deloitte | Agentic enterprise 2028: A blueprint for cost savings, job creation, and faster growth through agentic AI

"AI agents are only as effective as the data that fuels them. To reason, predict, and act reliably, they need seamless access to accurate, complete, and context-rich information...When data pipelines are fragmented or lineage is opaque, agents inherit those weaknesses."

IDC Sponsored by IBM | Increasing AI Adoption with AI-Ready Data

"83% of organizations have increased their focus on data management since the emergence of GenAI. Over one-quarter of these respondents have cited data management as their top area of focus. Their main strategic objectives in data management are supporting AI use cases, improving the quality of data and analytics products, and enhancing data security and privacy. These objectives are critical to making data AI ready in the modern data environment."

THE ROADMAP

Our 90-Day Delivery Roadmap

A structured, high-velocity engagement that moves from assessment to handoff in 90 days from start to finish.

DAY 1 - 15

Assessment

DELIVERABLE
AI Readiness Audit
OUTCOME
Identified data leaks & ROI map
Day 16 - 45

Integration

DELIVERABLE
Live Integrated Hub
OUTCOME
Unified schema & API build
Day 46 - 75

Cleanup & Enrichment

DELIVERABLE
Validated Datasets
OUTCOME
Unit harmonization & pruning
Day 76 - 90

Governance & Handoff

DELIVERABLE
Handoff & Monitoring
OUTCOME
Ownership framework & training
The Financials

Straightforward Investment

Delivered by an expert team powered by proprietary, AI-ready accelerators.

“Outsourcing AP didn’t improve efficiency or manual work and errors remained. Integrātz cleaned up the data and automated the process which eliminated errors, sped up reporting, and released employees to work on higher value tasks.”

- VP of Finance Operations, Global Food & Beverage Company

Standard Accelerator

$85,000 Fixed

  • Up to 2 data sources
  • 1 primary AI use case
  • Standard Distribution Data Models
  • 90 Calendar Day Delivery
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Enterprise Custom

$125,000+

  • 3+ data sources
  • Complex legacy environments
  • Custom schema mapping
  • Full dedicated fractional squad
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$3 Million

Revenue Recovered from Improper Billing

Money recuperated within first cycle

25 FTEs

Freed from low-value work

All employees redeployed to high-value projects

300%

Increase in Processing Efficiency

Automation lead to results within six months

Next Steps

Have more questions? Contact us.