Not the model. Everyone uses much the same frontier models, and the good ones are largely interchangeable for this work. The difference is what the model is standing next to.

If the formula lives in one database, the supplier documents in a folder, the specifications in a second system and the batch records in a third, then a model attached to any one of them can only see a quarter of the product. It can summarise. It can't check anything, because the thing to check against is in a system it can't reach.

That's the whole argument, and it's an architectural one. It also explains why bolted-on AI consistently produces summarising and searching features: those are the only jobs available to it.

Ask for a change impact. Change one raw material on a real product and ask what else is affected: which finished products, which markets, which specifications, which dossiers, which open batches. A connected system answers immediately because it's a query. A bolted-on system produces a thoughtful paragraph about what you should probably check.

Second test: ask where an answer came from. A grounded system points at the record. A model with no record to point at will describe its reasoning instead, which is a different thing wearing similar clothes.

No, and it's worth being fair about it. Search over your own documents is genuinely useful, and a summarising assistant saves real time in a business drowning in PDFs. If your systems work and the complaint is that nobody can find anything, that may be all you need.

It just isn't the thing that removes the reconciliation work. That requires the underlying record to be shared, which is an integration project rather than a feature. The full version of this argument, and what the alternative looks like, is set out in why an AI operating system.