ZANUS AI FOR CONSUMER GOODS — COMPLIANCE
A wrong claim on a label costs recalls; a slow traceability answer costs worse. The architecture answers both: no source, no claim on every consumer-facing word, cited lot traceability in minutes, permissions to the field level, and a fully on-premises option for the formulations.
Private tenant or your own server · unlimited users · FDA-labeling-conscious wording

One record per user: role, tags, and granular permissions over every domain of the system.
Ingredient, nutrition and claim language comes only from documents your regulatory people approved and ranked — the AI cannot say what your library does not.
Lots, COAs, shipments and the questions asked about them live on a searchable audit trail — who saw what, who changed what, when.
Five-level workgroups separate brands, business units and co-pack partners; the on-premises option puts formulations on hardware you own, air-gap capable.
When the question comes — from a retailer’s QA team, an auditor or your own regulatory counsel — the answer is a search away: spec revision history, COA records, who approved which claim language, all in one place.

The architecture is built to support your obligations: approved-source-only answers, audit trail, redaction, on-premises custody. Regulatory specifics are reviewed with your team during onboarding — bring your regulatory or QA lead to the demo.
Yes — workgroups and field-level permissions let a co-pack partner see the specs and schedules for their lines and nothing else, enforced server-side.
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