Use Cases

Does this sound familiar?

These are the patterns we see in every enterprise. If you recognize yourself here, we should talk.

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Multi-site Operations · Logistics · Manufacturing

"Every location runs its own system"

The Problem

50+ locations, each with their own definition of "customer", "product", and "order." Every integration is custom-built. Every report is a reconciliation exercise.

You've tried master data management projects before. They took 18 months, cost millions, and the result was outdated before it launched.

Meanwhile, your AI initiatives stall because there's no clean, unified data foundation to build on.

Our Approach

We map your entire operation to six universal entities using LEAPED. Not by replacing systems — by creating a shared language above them.

IntelWeaver scans your existing data landscape and proposes mappings automatically. What used to take months of workshops takes days.

The result is a living digital twin that evolves with your operation — not a static model that's dead on arrival.

3–6×
faster data modeling
60%
less integration rework
<12w
pilot to production
LEAPED IntelWeaver UDF
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Enterprise AI · Data-Driven Organizations

"Our AI projects keep stalling"

The Problem

You've invested in AI tools, hired data scientists, launched POCs. But nothing makes it to production. The models are great — the data isn't.

Every AI project starts with 3 months of data cleaning. Different teams use different definitions. There's no shared context for the models to reason over.

Your board is asking for ROI. Your team is burning out on data plumbing instead of intelligence.

Our Approach

AI doesn't fail because of bad models. It fails because of missing context. We build the intelligence layer your AI needs — a unified, semantically rich data foundation.

LEAPED gives your data shared meaning. UDF makes it accessible. Your AI initiatives finally have something solid to build on.

We start with the data layer (Layer 5 of the ARERO Method), but we address all seven — because AI without people, process, and governance is just expensive experimentation.

80%
less data prep time
1
unified truth source
POC to production
LEAPED ARERO Method Layer 5: Data Layer 6: AI
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Wholesale · Distribution · Food Service

"Half our orders still come in by phone"

The Problem

Your customers prefer to call. They've been calling for 20 years. They're not switching to a portal. And every call means manual order entry, mistakes, and delays.

You've looked at chatbots. They don't work for your customers. IVR systems frustrate everyone. The human touch matters — but the manual process doesn't scale.

Our Approach

AI Voice Order lets your customers keep calling — nothing changes for them. But behind the scenes, every call is transcribed, understood, and converted to a structured order in seconds.

Enterprise-grade speech recognition, LLM-powered extraction, validation against your product catalog. Orders go straight into your system. No retraining, no new hardware, works with regular phones.

90%
less manual entry
~0
customer disruption
sec
call to system
AI Voice Order AWS Transcribe LLM Extraction
Is This You?

Signs you need the intelligence layer

Every new project reinvents the data model from scratch
Integration projects take 6+ months and still feel fragile
Your AI team spends more time on data plumbing than intelligence
Nobody can answer "how many customers do we actually have?"
You have 10+ definitions of "product" across your systems
Reports require manual reconciliation across multiple sources

Recognize your situation?

We're selectively onboarding founding partners who want to shape the intelligence layer with us. Let's explore if there's a fit.