Fragrance AI runs on data: what customers search for, what they photograph, what they choose. Used well, that data makes recommendations better for everyone. Used carelessly, it erodes trust. Brands adopting AI should treat privacy as a feature, not a footnote.
What fragrance AI typically uses
- Search and chat text: “oud without leather”.
- Photos of perfume bottles for identification.
- Feedback: “yes, correct” or “not for me”.
- Purchase and sample history.
Principles worth following
- Collect the minimum. A bottle photo does not need to be stored after the label is read; a fingerprint of the image or the extracted text is often enough.
- Be transparent. Tell customers what is saved and why.
- Give control. Make it easy to clear stored preferences.
- Aggregate for insight. Trend analysis works on anonymous, grouped data; it rarely needs individual identities.
- Secure what you keep and follow local data-protection law, including India's Digital Personal Data Protection Act as its rules take effect.
How Haveli AI approaches it
Our Perfume Decoder does not keep your photos. Its memory of confirmed answers lives in your own browser, and you can clear it at any time. We use aggregate patterns to improve our library and recommendations.
This article is general information, not legal advice.