Field associates find and correct shelf problems on the first visit, and every visit leaves an auditable record for the brands served.
Order Fulfillment Risk Agents
In one quarter the agents flagged more than 40% of orders as likely hit by supplier delays and priced over $3M of related cost.
Agents on a reconciled order graph found over $3M of cost and named the orders at risk before customers saw a delay.
What the agents do
Checks every open order line against the supply that can reach it, lists the ones likely to miss their date and drafts the customer email.
- Brand
- Home furnishings brand and retailer
- Contributed by
- Ekyam (Knowledge graph, MCP server, and agents)
- Industry
- Retail
- Audience
- B2B, B2C
01
The problem
Why this exists
The brand sells home furnishings to trade customers at wholesale and to consumers at retail. Its purchase orders to suppliers and its sales orders to customers sat side by side with no link between them, so when a supplier pushed out a purchase order nobody could tell which customer orders depended on it.
Read more
Delays surfaced late, because a late purchase order became visible as a late sales order only when the ship date arrived and the goods had not. Teams could not prioritize, because a delay touching one small order looked the same as one touching a large trade account. Shortages also hid inside orders that looked ready, where one unit on one line waited on a late or short purchase order.
02
Outcomes
What changes when this is in place
- In one quarter the agents identified thousands of orders likely to be affected by purchase order delays, more than 40% of all orders.
- They priced over $3M of projected cost from customer service, cancellations, and make-goods.
- A forward list of sales orders likely to miss the date the customer was promised, across a 90-day window.
Read more
- For each affected customer, a proactive email drafted for customer service to review and send through Salesforce without leaving the tool.
03
How it works
Architecture
Ekyam reconciles the brand's data first. It pulls purchase orders, sales orders, customer-requested dates, returns, quality incidents, and pricebooks from the ERP, quality (VQMS) and returns (RMA) systems and the PIM, resolves the same order, customer, and SKU across systems, and loads the result into a knowledge graph that links each purchase order to the sales orders it supplies.
Read more
The graph is exposed through purpose-built tools on a Model Context Protocol server, and agents work only on that reconciled view. They price late orders, returns, and quality incidents for the quarter, separate a small set of high-cost orders from the long tail, check every open line against the supply that can reach it in time, and draft a customer email when a delay touches an order.
Results land in an ROI calculator and a risk dashboard that operations and finance use without writing a query. Because the graph sits apart from the agents, new agents can run on it without another integration project.
Open standards used
Model Context Protocol (MCP)
Tech stack
Ekyam knowledge graphEkyam MCP serverERPVQMS quality systemRMA returns systemPIMSalesforce
Resources
Next step
Request an intro
Ekyam is behind this solution. Ask about seeing which customer orders a late supplier will hit, and the MACH Alliance will put you in touch with the person who can answer.
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Everyone credited on this solution
- EkyamKnowledge graph, MCP server, and agents
Every organization named here has a page listing the rest of its work on the Hub.
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Verification
Contributor submission
The detail on this page comes from the contributor's own account of their own work. The MACH Alliance reviews a submission before publishing it and does not independently verify the figures in it.
Where this came from
Solution detail is drawn from Ekyam's submission to the hub, anonymized while Ekyam asks its client for permission to be named.
Status: Live in productionAdded Oct 26, 2026A listing is an editorial decision, not a MACH Alliance certification.
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