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TRADE · 2025

For two trade firms, an intelligence layer that reads demand and relationship signals from historical data

For two firms operating in trade networks where the same counterparty is often both supplier and client, we built a custom application that reads historical transaction data and surfaces demand and relationship signals. The product's specific logic is our clients' competitive edge; this page describes the methodology, not the internals.

The problem

In trade, decisions usually depend on reading past data correctly. But that data is fragmented in most firms: part of it in the ERP, part in email threads, the rest in someone’s head. And when the same name is both a supplier and a client, classical CRM logic models the relationship wrong.

The result: you’re either late to a market move, or reacting to the wrong signal.

Approach

First we watched the real decision moments at both firms: which sheets people open, which questions get asked at which frequency, how intuitive queries like “we haven’t heard from this client in a while — what do we do” actually get answered.

We turned that map into an application that reads each firm’s historical transaction data and translates demand research and supplier-client relationship dynamics into actual data signals — instead of intuition.

Why we don’t share the internals

The logic we build for a client is their market edge. What you should be able to see on this page is how deeply we go — not the specific business rules. We extend the same discretion to you: a private logic we will never share with your competitor.

How we worked
On-site decision analysis Historical data interpretation Supplier–client relationship modelling Confidentiality-first build

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