Importers and trading groups
Regional groups importing from international suppliers across several entities, currencies and countries.
- Landed cost and true SKU margin
- Multi-currency purchasing and payables
- Consolidation across entities
Know what you really earn.Know where your stock is.Know who owes you.Then act on it.
Data Semantics shows importers and distributors what they really earn by principal, product and customer, where their stock is and who owes them, and puts AI agents to work on orders, collections and supplier invoices, on the systems you already run.
For importers, regional trading groups, brand representatives, wholesalers and distributors.
Data Semantics provides analytics, automation and AI agents for importers, regional trading groups, distributors and diversified trading companies. We connect principals, purchase orders, landed cost, stock, routes, customers and finance into one view of margin, inventory and receivables. AI agents then take customer orders from email and portals into the ERP, follow up overdue trade accounts and process supplier invoices, with people approving what matters. Start with either analytics or automation.
Procurement, logistics, warehouses, sales, credit control and finance each run on different systems. Every gap between them is where margin, stock and cash leak.
Four operating models, one foundation: connect the data, model the business, then automate the decisions that matter. Selling to shoppers in stores or online? See retail.
Regional groups importing from international suppliers across several entities, currencies and countries.
Companies representing international brands, measured on targets and accountable to principals.
Wholesalers selling to retailers, dealers and businesses on credit and negotiated terms.
Distributors serving retailers, dealers and HoReCa accounts through warehouses, van sales and key accounts.
We combine industry understanding with the technical know-how to build what you need, from analytics and automation to AI agents that act. These are the most common starting points, and the last card in each row covers everything else.
Landed cost and margin intelligence brings purchase cost, freight, duty, FX, rebates, discounts, returns and cost to serve into one view of what each SKU, brand, customer and route really earns.
Principal and supplier intelligence connects agreements, purchase prices, rebates, lead times, fill rates and claims to show which principals and suppliers add value and which cost you margin.
Inventory and fulfillment intelligence combines sell-out, stock positions, lead times and open orders to balance stock across warehouses, depots and vans, with less capital tied up.
Sales and territory intelligence connects orders, routes, salespeople, customers and targets to show where volume and margin are won and missed.
Need something else analyzed or automated? Talk to an expert →
Order processing automation reads orders from customers and distributors, whether they arrive by email, PDF, portal or spreadsheet, checks them against price lists, credit and stock, and creates sales orders in your ERP.
Collections automation predicts which trade customers are likely to pay late, then uses AI agents to remind, follow up, resolve deductions and reconcile payments.
AP and procurement automation captures, matches, approves and posts supplier, freight and service invoices into your ERP, with a full audit trail.
Tell us where your teams lose the most time today. We’ll show you what we would fix first, on the systems you already run.
A distribution ontology is a shared model of your business: the principals, SKUs, shipments, warehouses, routes, customers, orders, invoices and payments, how they relate, and which system each lives in. Your ERP knows the invoice, your van-sales system knows the delivery and your bank knows the payment. The ontology knows they're the same order for the same customer.
Two workflows trading and distribution teams often start with.
Trade credit handled consistently, for every account, every month.
Some of your biggest customers may be costing you money.
We don’t borrow results from other industries. Every trading and distribution engagement starts by measuring today’s baseline, and success is proven against it. These are the measures we track most often.
Sales, inventory and finance data brought together, so sales, supply chain and finance work from the same numbers.
Invoices from many suppliers and operating companies captured, matched and posted, with one view of exceptions for shared services.
Each is a fixed-scope engagement on your own data, measured against today’s baseline.
True margin by principal, SKU and customer once freight, duty, FX, rebates and cost to serve are counted.
Business Intelligence & Analytics →AutomationAI agents take customer orders into the ERP, or follow up overdue trade accounts, for one business unit.
Zebo →AutomationPrincipal and supplier invoices captured, matched to orders and receipts and posted to the ERP.
Serina →Every engagement follows the same path: measure today’s baseline, connect and model the data, prove it on a real workflow, then scale.
About distribution AI
A distribution ontology is a shared model of your business: principals, SKUs, shipments, warehouses, routes, customers, orders, invoices and payments, and how they relate, mapped to the systems where each lives. It gives every report and every AI agent the same definitions and full context, which is what makes their answers and actions trustworthy.
Margin, orders and cash
Landed cost and margin intelligence brings purchase cost, freight, duty, FX, supplier rebates, discounts, returns and cost to serve into one view, so you can see what each SKU, brand, customer and route really earns, not just what it sells.
Yes. Zebo, the Data Semantics order-to-cash agent, reads customer orders from email, PDF, portals and spreadsheets, checks them against price lists, credit and stock, and creates sales orders in your ERP, cutting manual order entry by 90% or more.
Collections intelligence predicts which trade customers are likely to pay late, then uses AI agents to send reminders, make calls, track promises-to-pay, resolve deductions and disputes, and apply payments in the ERP.
Yes. Data Semantics models your business as it actually runs, including van sales, consignment and depot stock, principal rebates and claims, customer deductions and multi-entity operations.
Systems and data
SAP, Oracle Fusion and EBS, Microsoft Dynamics 365 and AX and Salesforce are the most common, plus warehouse, van-sales, distribution-management and banking systems. If your data is in a system, we can usually connect it.
No. Data Semantics builds on what you run today, including Microsoft Fabric, Databricks or Snowflake if you already use one. Where item, principal or customer data needs cleaning or moving, DataPrep 360 handles it as part of the work.
Our solutions run on Microsoft Azure and can be deployed in your own tenant and preferred region, so your data stays under your control.
Getting started
Yes, and we recommend it. Common starting points are trade collections, supplier invoice automation, landed cost and customer margin, and stock balancing across warehouses. Each new use case reuses the same ontology, so it goes live faster.
AI agents score credit risk, follow up on payments, match invoices, flag margin leaks and recommend next steps within guardrails you set. Business-critical decisions such as credit holds, price changes and write-offs stay with accountable people, and every action is logged.
Collections, landed cost, stock or supplier invoices. We'll show you what it looks like automated, on your own data.