Agilis.

The insight underneath Agilis is unglamorous: you cannot put a modern storefront, or a useful AI assistant, on top of messy data. So the company starts with the foundation - cleaning, structuring and centralizing commercial product data - and layers commerce and AI on top of it. That sequencing is the whole bet.

It is a vertical-software play rather than a horizontal one. Rather than sell a generic commerce engine and ask chemical companies to bend it to their needs, Agilis ships templates, taxonomies and workflows built specifically for how chemicals are described, regulated and sold. The result is measurable: suppliers using the platform report 98% faster access to product data and roughly 480,000 SKUs digitized across the customer base.

Chemical commerce is not just retail with bigger drums. Product data is fragmented across systems, heavily regulated, and full of technical attributes - grades, purities, polymer specs, ingredient data - that generic e-commerce platforms were never designed to handle. Buyers often land on a decade-old datasheet and email a rep to ask whether the product is even in stock.

That is the gap Agilis targets. Where horizontal platforms like Salesforce Commerce Cloud, SAP Commerce, Adobe Commerce, inriver or Akeneo offer general-purpose tooling, Agilis ships purpose-built data models, industry templates and compliance-aware workflows for chemicals out of the box. The alternative most suppliers face is a costly DIY build that takes 18 to 36 months - and frequently stalls.

The company's other differentiator is speed to value. Agilis structures engagements as short, paid pilots - on the order of 3 to 6 months - with measurable ROI, then expands module by module. Suppliers keep ownership of their brand and their data, a point Agilis emphasizes for an industry wary of handing customer relationships to a marketplace.

And because the platform normalizes messy master data first, it positions its customers for the thing everyone in the sector now wants: usable AI. Agilis frames its own product as the prerequisite - the structured foundation that makes AI search, virtual assistants and decision tools actually reliable in a regulated field.