SPS Commerce presented its intelligent supply chain network agent at DynamicsCon 2026, exploring how AI changes the role of EDI in modern supply chains.
What DynamicsCon Is and Why It Matters
DynamicsCon 2026 brought together 2,000 customers, partners, and industry experts in and around the Microsoft Dynamics ecosystem. It's one of the major annually recurring Microsoft tradeshows in North America which SPS attends. SPS supports thousands of Microsoft customers, and one of our eight strategic ERP markets, as it remains a critical platform for supply chain operations.
The conference typically focuses on migration strategies and cloud adoption. This year, the conversation shifted. The real discussion centered on where AI fits into supply chain architecture and how it changes the relationship between transaction processing and decision-making.
The EDI Problem
EDI has handled supplier connectivity and order processing for decades. It does one thing well: standardize and transmit structured data between systems. But standardization doesn't create visibility.
When an EDI message fails, discovery takes days. A deduction arrives with minimal supporting data, forcing manual investigation. A rebate eligibility gap goes undetected. An invoice discrepancy slips past because the processing layer never sees context, only the message itself.
Most supply chain operations have adapted to these limitations. Teams optimize their EDI implementations, add API layers for real-time connectivity, build dashboards for monitoring. The result is better throughput and faster processing. But the underlying architecture hasn't changed: EDI remains a transaction processor, not an intelligent system.
If you're evaluating EDI vendors or considering build versus buy approaches, the technical, contractual, and operational criteria that actually matter haven't shifted either. The question becomes whether optimizing that layer is enough.
How MAX Works
MAX is SPS Commerce's intelligent supply chain network agent. It's designed to operate alongside EDI, not replace it, using EDI-processed data as one input among many.
The architecture matters here. While EDI handles order transmission and invoice processing, MAX pulls from multiple data streams: historical transaction patterns, supplier performance metrics, customer deduction history, compliance records, demand forecasts. It analyzes relationships between these datasets, patterns humans don't catch because the data lives in separate systems.
When a deduction arrives, MAX doesn't just log it. It cross-references it against:
Historical patterns from that supplier and customer
Whether similar deductions resolved favorably before
What documentation supports or contradicts the claim
Whether the deduction aligns with contractual terms
This changes the decision calculus. Instead of disputing based on intuition or a quick spreadsheet check, you have a system that spots which deductions are worth fighting and why.
The same principle applies to margin protection. Most supply chain teams react to problems after they've cost money. A shipment arrives damaged. A supplier suddenly raises pricing. Demand patterns shift unexpectedly. MAX flags these scenarios before they impact operations by analyzing leading indicators across your network.
Three Concrete Problems MAX Addresses
Deduction accuracy. Suppliers and retailers exchange thousands of deductions monthly. Many are valid. Many aren't but remain hard to dispute without comprehensive data. MAX creates a decision-support layer that identifies which deductions warrant a response and surfaces the evidence needed to support that response.
Revenue leakage detection. Broken orders, invoice errors, rebate eligibility gaps, and compliance violations create revenue loss that traditional systems don't flag. They're not transaction failures, the systems processed everything correctly. The problem is that no layer connects order data, invoice data, rebate rules, and historical outcomes to spot the gap.
Visibility into margin erosion. Cost changes, demand shifts, and supplier performance issues cascade through a supply chain before anyone notices them. Early detection matters because response time directly impacts margin. MAX creates a monitoring layer that connects data points most teams keep separate.
Where This Fits Into Modern Supply Chain Architecture
At DynamicsCon 2026, we showed MAX working within Dynamics environments because that's where most attendees operate. But the architectural principle is universal: clean ERP data, connected through middleware, becomes more valuable when you layer intelligence on top.
This isn't about replacing EDI or transaction processing. EDI is still how you move orders and invoices. The question is what you do with the data after it moves. Traditional approaches focus on visibility: dashboards that show what happened. Intelligent approaches focus on actionability: systems that highlight what to do about it.
Implementation Reality
Adding MAX to an existing supply chain tech stack is a breeze, but stakeholders should have three things prepared beforehand:
First, data quality. If your ERP data is inconsistent or your EDI feeds are incomplete, an intelligent layer amplifies that problem. Clean data becomes more important, not less.
Second, system connectivity. MAX needs access to order data, transaction history, supplier metrics, and deduction records. If these live in separate systems with no integration, you can't build intelligence on top. The infrastructure to connect them has to exist first.
Third, clear decision criteria. What makes a deduction worth disputing? What constitutes margin erosion worth acting on? What demand shifts warrant operational changes? Before you implement MAX or any intelligent layer, it is important for operations, finance, and IT to get aligned on these questions. You need to define these before an intelligent system can help you apply them consistently.
These are infrastructure questions, not product questions. The technology works when the foundation is ready.
If You Missed It
If you didn't catch the session at DynamicsCon 2026 or want to discuss how MAX could work in your supply chain environment, reach out to SPS Commerce. We can walk through how this applies to your specific data architecture and operational challenges.
