Product innovation

Solenne accelerates AI-assisted formulation with Selective Cloud

Scientists use an intelligent formulation workspace built on SelectiveDB to explore ingredient relationships, evidence and alternatives with near-instant feedback.

SelectiveDBSelective Cloud
Abstract artwork for Solenne Beauty Group

The challenge

Complex simulations required data from many scientific sources and too much custom backend code, slowing every product experiment.

The solution

Solenne consolidated formulations, ingredient properties, laboratory evidence and semantic indexes in an AI-native data model.

The outcome

Researchers receive interactive results in milliseconds and development teams maintain a simpler, more scalable application.

Industry
Beauty and consumer products
Products
SelectiveDB, Selective Cloud
Use case
AI-assisted research
The challenge

Scientific exploration slowed by application plumbing

Solenne’s innovation studio builds digital tools for product scientists and brand teams. One application helps researchers remove or replace ingredients while preserving performance, texture, fragrance, cost and regulatory constraints.

The original application pulled from several warehouses and document repositories, then performed extensive restructuring and calculations in backend scripts. A single investigation involved many interactive steps, making even small delays visible to scientists and difficult for developers to optimise.

The solution

Formulations, evidence and AI context in one model

The team moved formulation records, ingredient properties, experiment results and regulatory references into SelectiveDB. Flexible documents represent evolving scientific structures, while vector indexes connect laboratory notes and published evidence to operational formulation data.

Selective Cloud runs the platform across research centres and automatically scales simulation workloads. Developers use database-side aggregation and retrieval instead of maintaining large amounts of bespoke calculation and synchronisation code.

The outcome

More experiments in every research session

Interactive query latency fell to 12 milliseconds and formulation retrieval became 32 times faster. Researchers can now test alternatives continuously rather than submitting a request and waiting for a batch result.

The new model removed 45% of custom calculation code and indexes more than 700,000 formulation and ingredient relationships. Teams can extend the application to new brands and regulatory datasets without redesigning the database.

Measured impact

A data foundation designed for the moments that matter

12 ms
interactive query latency
32×
faster formulation retrieval
45%
less calculation code
700K+
indexed relationships

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