The development of paints, coatings, and other complex formulations is a multidimensional challenge: color, raw materials, product properties, process parameters, costs, and regulatory requirements all influence one another.
Traditional development processes often require numerous laboratory tests and extensive expert knowledge. Valuable data and experience are available, but are often not systematically utilized to make better decisions.
Typical challenges
Our solution: Turning knowledge into informed decisions
ai-predict combines measurement data, physicochemical models, expert knowledge and AI to create customer-specific decision and optimization solutions.
Our approach to Deep Knowledge Integration (DKI) makes it possible to model complex relationships, virtually simulate formulations and processes, evaluate alternatives, and calculate suitable formulation proposals.
Instead of purely “black-box” results, users receive transparent analyses, recommendations for action, and information about technical limitations and conflicting objectives.
This makes expert knowledge accessible and scalable for different user groups: from development through the laboratory to production. The underlying models and solutions can be adapted step by step to new requirements and areas of application.
For paints, coatings, and complex formulations—and much more!
Systematically analyze and integrate existing measurement data, formulas, and expert knowledge.
Simulations, transparent recommendations, and optimization of multiple properties.
Fewer laboratory tests and more targeted development through virtual evaluation of formulations and processes.
From the initial specific question to complex, interconnected decisions regarding wording.
Together, we’ll explore how simulation, physical models, and AI can improve your development and decision-making processes.
Dr. Mathias Huck
Head of Marketing & Sales
Phone: +49 170 3281 473
Email: mathias.huck@ai-predict.de
Complex formulation issues can be solved particularly efficiently when data, process understanding, expert knowledge, and suitable models come together. This is precisely where ai -predict helps.
Our current focus areas include paints, varnishes, and coatings—particularly in cases where color, other product properties, and process conditions must be considered together.
Our modular approach is designed for scalability and allows solutions to be expanded step by step to include additional features, processes, and areas of application.
.
Gemeinsam analysieren wir die Ausgangssituation: Welche Herausforderung soll gelöst werden? Welche Ziele, Randbedingungen und Prozesse sind relevant? So entsteht ein klares Verständnis des Anwendungsfalls und des erwarteten Mehrwerts.
Wir sichten vorhandene Messdaten, Rezepturen, Prozessparameter und Expertenwissen und bringen diese in eine nutzbare Struktur. So werden Datenqualität, Zusammenhänge und Potenziale sichtbar: Die essentielle Grundlage für fundierte Entscheidungen.
Based on the objectives, we select the appropriate approach: from analysis and simulation to decision support and optimization. In doing so, we combine data, physicochemical models, and domain expertise to develop a practical solution.
In einem ersten Pilotprojekt zeigen wir, wie sich konkrete Fragestellungen effizient bearbeiten lassen – zum Beispiel bei Formulierungen, in denen Farbe, weitere Eigenschaften und Prozessbedingungen zusammenwirken. So wird der praktische Nutzen früh sichtbar und bewertbar.
You can build on a successful initial solution in a targeted way: by addressing additional questions, incorporating new data sources, defining new metrics, or expanding to include more user groups. This way, the solution grows along with your needs—from initial decision support to a scalable application.
ai-predict combines the power of an existing software platform with the flexibility of customized solutions. Our ai-core platform forms the technological basis for the analysis, simulation, and optimization of complex formulations and processes.
Existing, reusable software and model components —such as those for data preparation, physicochemical color models, property predictions, and optimization methods—make it possible to build on proven technologies.
Depending on the specific application, we combine and configure existing building blocks, adapt models to customer-specific data and processes, or develop additional specialized modules. In doing so, we can incorporate multiple characteristics and technical constraints into the decision-making process.
This results in transparent simulations, optimized formulation suggestions, and concrete decision-making tools for various user groups—from specialists to production personnel.
A shared platform. Reusable modules. Customized solutions that grow with your needs.
Protecting your data and your company’s proprietary know-how is a central component of our approach.
ai-predict develops customized models and decision-making processes that strategically utilize existing measurement data, recipes, process information, and expert knowledge. In doing so, we take into account the requirements for data sovereignty, confidentiality, and the protection of sensitive company information.
Our architecture makes it possible to design data sources, models, and analysis processes in accordance with the specific project requirements and to incorporate appropriate security and access policies.
Your knowledge remains your competitive advantage. Our technology helps you systematically put it to use.