These are the patterns we see in every enterprise. If you recognize yourself here, we should talk.
Multi-site Operations · Logistics · Manufacturing
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 They took 18 months, cost millions, and the result was outdated before it launched.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.
We map your entire operation to six universal entities using LEAPED. Not by replacing systems, but by creating a shared language above them.
plicai 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.
Enterprise AI · Data-Driven Organizations
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.
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.one 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.
Wholesale · Distribution · Logistics
Your customers mail orders as PDFs, spreadsheets, and free-text emails. They've done it for 20 years. They're not switching to a portal. And every order means manual entry, mistakes, and delays.
You've tried OCR templates: they break on every layout change. Portals? Your customers don't use them. The volume keeps growing, but the manual process doesn't scale.
UDF.one reads orders the way a person would (email, PDF, spreadsheet) and folds them into structured transactions in your system. Your customers change nothing.
LLM-powered extraction, validated against your own products and customers in the digital twin. Exceptions go to a human; the rest flows straight through, with the evidence attached.
We're selectively onboarding founding partners who want to shape the intelligence layer with us. Let's explore if there's a fit.