Evaluation guide
Feature lists don't separate these platforms any more, because everyone's list is the same. Seven criteria do. Score each vendor out of five, on your own data, in their system rather than in a slide.
Last reviewed by the Worldover regulatory team.
Quick answer
Evaluate AI PLM software on seven things: whether the data model understands formulas, whether every AI output is traceable to source, whether approvals are recorded against named people, whether versions and rollback are real, whether you can export everything, what happens when a regulation changes, and what leaving costs. Demo appeal correlates with none of them.
How this connects to Worldover
Replacing five subscriptions with one system you actually run the business on?
Worldover is the AI operating system for chemicals, cosmetics and supplement businesses. One platform, one data model, custom-built around each team.
See how Worldover worksScore each vendor on your own products. Anything scored from a slide is scored from marketing.
| Criterion | What a one looks like | What a five looks like |
|---|---|---|
| Data model | Formula stored as an attached document | Formula is a first-class object with substances, percentages and versions the AI can read |
| Traceability | Output appears with no source | Every statement traces to the formula line, document or regulation behind it |
| Approvals | Anyone can edit a released document | Named approver, timestamp and a diff between draft and approved, held on the record |
| Versioning and rollback | Latest version only | Full history, side-by-side comparison and a genuine revert |
| Exports | PDF only, or a support ticket | Structured export of every object you put in, on demand |
| Regulatory change | A newsletter | Automatic re-check of affected products, with the impact list produced for you |
| Exit | Data hostage in a proprietary format | Documented export, agreed in the contract, tested during the pilot |
Use the PDF download in the sidebar for a printable copy to score against in the meeting.
Narrowly, and on your worst data. Pick three real products, including the one with the messiest supplier documentation, and ask the vendor to load them and produce one finished output: a dossier section, an SDS, a specification. Timebox it to two weeks.
A pilot on clean demo data tells you what the software does when nothing's wrong, which is never the state of a real product record. What you're buying is the behaviour in the awkward cases.
Four, reliably. Show me the audit trail for something the AI generated last week. Show me what happens when two supplier documents disagree. Export my data now, in front of me. And tell me what this costs in year three including the services line.
None of those are unfair, and all four are answerable in minutes by a system that works the way it's described. Hesitation on any of them is information.
Three vendors, not seven. Beyond three, evaluations stop being comparisons and become scheduling exercises, and the decision drifts to whoever presented most recently.
Head-to-head detail on the platforms most often shortlisted alongside us sits on the comparison hub, and the architectural question underneath the scoring is covered in AI-native versus AI bolted on.
Worldover for this
Head-to-head detail on the platforms most often shortlisted alongside us.
See Compare Worldover with the alternativesIf this has settled the question, the fastest next step is to look at what the work looks like on one record: Compare Worldover with the alternatives.
Not ready for a conversation? The talk it through with us scores your current position in about two minutes, with no gate on the result.
FAQs
A 20-minute working session. Your SKUs, your customers, your documentation. No slide deck.