June, 5 2025
At Fenix Commerce, we’ve been thinking a lot about Generative AI — not just what it can do, but what it demands from your organization in order to deliver on its promise.
Everyone wants to plug LLMs into their workflows. But here’s a truth we’ve seen over and over again, especially in eCommerce:
Most data is not AI-ready.
If you’ve ever tried to do anything ambitious with eCommerce data — you already know.
Data from Shopify, BigCommerce, Salesforce Commerce Cloud, or Magento doesn’t just fall into your lap in a usable format. It comes through webhooks, APIs, and platform exports — often nested, unstandardized, or inconsistent in how it defines even the basics (like fulfillment status or timestamps).
Then there’s the relational chaos:
AI can’t guess its way through that.
The process of getting AI-ready isn’t just flattening JSON sor mapping columns. It’s about defining a data model that serves your current roadmap:
For most companies, this data model was built years ago — usually to serve BI dashboards or basic order tracking.
But now we want real-time predictions. Prompt-based interfaces. Auto-generated alerts. The old model can’t stretch far enough.
We see our GenAI development — including some very exciting new products we’ll share soon — not just as an opportunity to layer intelligence over existing data…
…but to rethink the entire foundation.
That means:
And yes — re-architecting the data model itself, from the ground up, to reflect the questions our customers are asking today (not the questions we thought they’d ask five years ago).
The potential of GenAI is incredible. But it can’t reason through chaos. If your underlying data isn't reliable, complete, and well-structured — the model will reflect that.
That’s why we treat data modeling as a product in itself.
And if you’re serious about building with AI, you should too.
🚀 Want to learn how we’re building prompt-native delivery intelligence and real-time fulfillment predictions?
Author: Tobi Konitzer, PhD
Chief Innovation Officer, FenixCommerce