Why not upload formulas to public AI?
Public AI tools can help with general explanations, but confidential chemistry is different. Real company value often lives in the private details: failed formulations, supplier choices, raw-material substitutions, customer complaints, field failures and technical service history.
Formula exposure risk
Even partial formulas and test histories can reveal proprietary know-how when combined with product claims and customer context.
Customer confidentiality
Complaints, field photos, warranty issues and application problems may include customer-sensitive data.
Competitive knowledge
Pricing, technical objections, raw-material preferences and competitor comparisons are part of the company’s commercial intelligence.
ACRAZO’s position: client-owned data stays client-controlled.
The private Science LLM workflow is designed so confidential files are uploaded into the customer’s private environment, not into a public chatbot or shared AI playground.
Good first policy
If it would hurt the company if a competitor saw it, it should go into private AI — not public AI.