Turing is an AI-powered research and development platform that accelerates consumer goods formulation by utilizing in silico iteration and data-driven insights to optimize product development. This technology reduces the time from concept to market by up to eight months, enabling faster innovation and improved product performance.
Funding
$18.4M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Consumer packaged goods (CPG) companies face challenges in efficiently developing and reformulating products due to lengthy traditional research and development (R&D) processes. These processes often involve extensive lab work, physical prototyping, and iterative testing, leading to delays in bringing new or improved products to market. The ability to rapidly innovate and respond to changing consumer preferences is hindered by these time-consuming methods.
Solution
Turing offers an AI-powered R&D platform designed to accelerate the formulation and innovation of consumer goods. By leveraging existing product data, packaging material information, and process data, the platform builds an actionable knowledge base to guide product development. The platform enables in silico iteration, allowing R&D teams to visualize potential formulation outcomes and modify ingredients to assess their impact on sensory and consumer attributes. Turing's AI engine provides optimal formulation recommendations, enabling faster innovation, improved product performance, and reduced time to market.
Target Audience
The primary target audience includes R&D departments, formulation scientists, and marketing teams within consumer packaged goods (CPG) companies.
Features
- AI-driven formulation recommendations based on existing product and process data.
- In silico iteration to visualize formulation outcomes and assess the impact of ingredient changes.
- Digital Lab OS to manage and analyze data related to formulations, packaging, and processes.
- Identification of key drivers of consumer preference through data analysis.
- Optimization of formulations for specific target markets and sensory attributes.
- Prediction of shelf life based on ingredient composition.
- Cost reduction analysis while maintaining product quality.