How DwyerOmega uses Akeneo MCP to manage product data
DwyerOmega uses Akeneo MCP Server to connect product data with Power BI, AI-powered content creation and the onboarding of acquired product lines. The company says the basic data model and related assets for a new product line can be loaded in as little as 40 minutes.
- DwyerOmega tracks product catalog quality in Power BI.
- Akeneo data cannot be edited directly from the Power BI report.
- An AI-powered process improves technical product descriptions.
- The basic model for an acquired product line can be loaded in around 40 minutes.
- The company says it loaded 82 product lines in the first few weeks.
Power BI shows where product data is incomplete
According to an Akeneo announcement, DwyerOmega's product management and marketing teams get a filterable view of catalog quality in Power BI. The company checks whether products meet defined targets for, among other things, hero and variant-level images, 360-degree product views, image alt text, short and long descriptions, unique SKU-level descriptions, accessories, product relationships, CAD files, and upsell and cross-sell assignments.
Users can filter by product manager or product model, then export products with missing or inadequate content. The Power BI interface functions solely as a report. Changes continue to be made in Akeneo or in import documents managed by trained PIM users.
Cyrus Grimes, DwyerOmega's director of product content management, put it this way: “No, this is just a report.” According to the company, the new approach allows teams to work from specific lists of products awaiting improvement instead of trying to address general completeness issues.
AI creates richer descriptions from technical documentation
DwyerOmega also uses a multi-stage, AI-assisted workflow built in Claude to improve product descriptions. The capabilities of technical products are often detailed in specification sheets and manuals, while the online catalog may feature only the most popular variants.
The process uses Akeneo product records to locate related manuals and specification documents. Local optical character recognition processes the technical content first, followed by a local language model. Quality control then takes place, and the system produces a structured description based on the product's capabilities, incorporating useful elements of the existing text. Product managers carry out the final review before uploading the material back into Akeneo.
Grimes said that previously, several product descriptions were “pretty weak. Literally just one paragraph, with some kind of marketing fluff.” According to the company, the new method helped maintain and increase organic search traffic even as broader declines were observed across the industry.
Product lines can be built in 40 minutes after acquisitions
According to DwyerOmega, one of the biggest opportunities presented by Akeneo MCP is onboarding products from acquired companies. These products are often organized differently, highly technical, expensive or available in so many configurations that they cannot easily be adapted to conventional cart-based sales.
The company has therefore created sales-assisted product families. These encourage customers to contact a salesperson while ensuring that product information is fully managed and published.
The MCP-based workflow connects multiple systems. Based on web data for a product line from an acquired company, related assets are placed in SharePoint, images are mirrored in AWS for web delivery, and the asset is then created in Akeneo with an automatically populated URL. The system subsequently builds the product line with a placeholder variant and basic information.
“We are able to acquire the assets, product images, specification sheets and manuals, and then load this simple product model into Akeneo in 40 minutes,” Grimes said. According to DwyerOmega, 82 product lines were loaded in the first few weeks.
Akeneo remains the source of truth for product information
A common element of the use cases presented is that Akeneo remains the governed, authoritative source of product information. According to the company, MCP reduces friction between Akeneo and the systems where product data is actually used.
This allows DwyerOmega to integrate products from acquisitions more quickly, make data quality information available in Power BI to product, marketing, SEO and sales operations, and target improvement tasks more precisely. Technical documents can serve as the starting point for a repeatable, verifiable content creation process.
Under the company's operating principle, repeatable discovery and preparation steps are automated, while human review remains in place for important changes. DwyerOmega plans to add more Power BI views in the future and is also exploring a data quality view that would identify discrepancies between SAP Commerce Cloud, Akeneo and the source system.
