Data recycling with AI: How new knowledge is created from old information
Munich start-up combats data chaos
Excel spreadsheets, PDFs, outdated databases - unstructured data sources are piling up in many companies, making it difficult to access valuable information. Technical specifications, standard documents and historical test reports often contain valuable findings, but remain hidden in inaccessible folder structures. As a result, specialists in research and development (R&D) and quality assurance lose valuable time every day searching for relevant data.
This is where artificial intelligence (AI) comes in: Upload files, search efficiently and extract relevant information. With the new feature of the AI-supported material intelligence platform LabV, a wide variety of files can be uploaded and used for further analysis or research. The AI recognizes content in documents, searches them specifically and links them to existing material and test data.
For example, material characteristics can be extracted from old test reports or technical specifications can be searched in seconds - without any manual effort. AI-supported analysis makes valuable information available and enables well-founded, data-based decisions in product development and quality assurance.
AI-supported document analysis is part of the LabV material intelligence platform, which supports R&D and quality engineers in working in a data-driven manner. By integrating test data, technical specifications, material characteristics and other data sources such as ERP, MES and CRM systems into a central system, LabV enables efficient and well-founded decision-making. The platform intelligently links information, automates analyses and optimizes workflows in R&D and quality assurance. LabV's customers include well-known companies from the plastics processing, mechanical engineering and paint and coatings industries, among others.
Note: This article has been translated using a computer system without human intervention. LUMITOS offers these automatic translations to present a wider range of current news. Since this article has been translated with automatic translation, it is possible that it contains errors in vocabulary, syntax or grammar. The original article in German can be found here.
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