Ai-native materials-informatics platform for fragrance stability
Polymerize offers an AI-native materials-informatics platform that models and optimizes the composition-rheology-volatility relationship to enhance fragrance stability. The platform provides a reusable predictive model and ready-to-test formulations that remain stable for 3 months at 40C/75%RH.
Overview
Polymerize introduces an AI-native materials-informatics platform designed to revolutionize the development of stable, long-lasting volatile-active delivery systems. This platform models the complex composition-rheology-volatility relationship to design systems capable of carrying over 10% fragrance oil, maintaining phase stability for three months at 40C/75%RH. It integrates a lab prototyping and testing network, allowing for rapid formulation and validation of fragrance delivery systems.
Technical specifications
- Predictive Modelling: Utilizes active-learning DoE to design fragrance systems with high oil loading and stability.
- Screening and Optimization: Conducts in-silico screening for encapsulation and stabilizer options, synthesizing and characterizing top candidates through a lab network.
- Performance Metrics: Targets viscosity between 80,000-100,000 cP for ointments while ensuring release kinetics and accelerated stability.
- Reusable Model: Provides a validated predictive model that can be reused and adapted for future projects.
Technology readiness level
The platform is currently at TRL 4, having been physically validated in-lab with key performance metrics confirmed. The process includes a structured validation pathway from scoping to down-selection, ensuring that the technology meets critical benchmarks for commercial readiness.
About Polymerize
Polymerize is an AI-native platform specifically engineered to transform materials research and development. It operates as a system of intelligence that integrates a unified data foundation, domain-specific AI models, and explainable insights to accelerate the discovery, development, and scaling of new materials. By digitizing experimental workflows, the platform replaces manual, spreadsheet-based processes with a centralized, data-driven backbone. The solution features over 35 domain-guided models trained on polymers, chemicals, and advanced materials, which allow R&D teams to predict material properties, optimize formulations, and gain scientific explanations for AI-driven recommendations.
The platform serves global R&D teams across industries such as automotive, specialty chemicals, coatings, and packaging, helping them reduce failed experiments and shorten go-to-market timelines. By capturing and leveraging institutional knowledge, Polymerize enables organizations to turn years of trial-and-error into targeted innovation, ensuring that data from past experiments informs future research. Customers use the platform to achieve significant ROI through increased discovery speed and streamlined operational forecasting, with security compliance standards like SOC 2 and ISO 27001 integrated to protect sensitive intellectual property. Founded in 2020 and headquartered in Singapore, the company maintains a global presence with offices and strategic collaborations spanning Asia, Europe, and the United States.
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