Are fragrance composition datasets for ML unattainable? – Machine learning, data science, and chemistry

Aromatune perfume creation app by Innosol prompt engineered perfume

Are fragrance composition datasets for ML unattainable? – Machine learning, data science, and chemistry

In the past, perfumers experimented with various combinations of molecules and accords to create unique fragrances for their clients. Today, Innosol and virtually all leading F&F Houses have developed AI-driven tools, such as aromatune.ai, allowing perfumers to create in minutes what historically has taken days with faster and more accurate results. While this new technology clearly offers fellow fragrance houses a strategic competitive advantage, we all depend considerably on in-house proprietary technology and formulation datasets which historically have been untouchable.

Most manufacturers have never had access to fragrance compositions or their datasets as they are owned by us and fellow fragrance houses. It is also extremely expensive for most brands to develop in house datasets which makes it more difficult to use the new machine learning resources and be truly competitive.

Innosol Fragrances has changed the rules, and we are doing the exact opposite: We now license our datasets and lower the barrier to entry for manufacturers. Our clients advise it is orders of magnitudes cheaper to buy a software license from Innosol than it is to create your own proprietary AI systems & fragrance formulation datasets. And most importantly: it is much, much faster.

Innosol’s datasets allow any company, even startups, to grow their brand while enhancing their marketing, ingredient, and fragrance creation process and improve their bottom line with the latest AI breakthroughs.

What is possible using Innosol’s datasets?  Aromatune.ai (beta)

Interested? Let’s schedule a meeting.

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