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Executive briefPrepared for a President, Support Services Group
Aevah executive brief

Your MDM was not built for this.

Distributed enterprises do not need another configuration-heavy master data project. They need an architecture that creates trusted enterprise intelligence, keeps local operations flexible, and makes AI safe to deploy in production.

Scale
700+

locations working from a single enterprise view.

Complexity
Hundreds of thousands

of SKUs that need coherent semantics, not manual cleanup.

Opportunity
AI-native

decisioning built on trusted, unified data.

What you already know

Legacy MDM creates friction where the business needs speed.

The problem is not just data quality. It is that your current architecture was never designed for distributed operations, local variation, or production AI.

The same item coded differently across dozens of locations, which turns enterprise aggregation into a manual reconciliation exercise.
Customer records fragmented by business unit, with no reliable way to see a single customer relationship across the network.
A golden record that still requires creative cross-referencing to approximate the enterprise view leadership needs.
Customer and product onboarding cycles that stall while teams wait for full enrichment before the business can move forward.
An MDM platform that depends on specialized consultants, constant configuration, and rising license fees while delivering diminishing returns.
What becomes possible

Aevah gives leadership unified intelligence without forcing uniformity.

The result is cleaner execution across pricing, onboarding, reporting, and AI adoption, with local teams still able to operate the way the business requires.

Pricing optimization at scale

Trigger AI-suggested pricing for any customer-item combination using enterprise pricing intelligence, regional strategy, and live market segmentation.

Enterprise visibility without sacrificing autonomy

Preserve local operating freedom while giving leadership a coherent view across industries, verticals, and regions.

AI you can trust

Build governed, semantically rich data foundations that let AI move from experiment to production with far less risk.

Faster onboarding, fewer bottlenecks

Enable early SKU creation, faster customer activation, and parallel enrichment workflows so the business can act sooner.

Executive lens

Why this matters to a support services president

The objective is not simply better master data. It is better operating leverage, faster decision cycles, and a stronger foundation for growth without adding avoidable complexity.

Less manual reconciliation across the enterprise
Faster onboarding for customers and products
More credible AI investments with less governance risk
A platform that scales with the business instead of slowing it down
Why Aevah

Built for distributed enterprises that want to own their technology stack.

Aevah was built for teams that need enterprise intelligence, not another expensive layer of customization on top of legacy MDM.

01
Replace legacy MDM, do not supplement it

Automated migration ingests existing schemas, business rules, and governance logic. What once took months of consulting can happen in days.

02
Respect the architecture you already own

Aevah works with homegrown systems rather than forcing a rip-and-replace program or a new vendor dependency.

03
Prove value in 90 days

The goal is not a roadmap or a proof of concept. It is measurable business progress in the first quarter.

04
Start with the highest-value use case

First domain migration completes in weeks, then the platform scales from there with less friction.

Next step

See how Aevah maps to your environment, your systems, and your timeline.

No pitch deck. No generic demo. Just a working session focused on your distributed enterprise model and the unified intelligence your team is building toward.