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In a world where education is becoming increasingly individualized, we cannot afford to treat learning materials as an indivisible mass. When all books, videos, and tests are lumped into one "pile", without specifying the topic, level, or the skills they develop, this is unstructured content for an intelligent

Automation of waste sorting processes is becoming increasingly important in the context of the development of computer vision technologies and the need to increase recycling efficiency. The creation of high-quality image sets is a key element for systems that perform material classification, contamination detection and object analysis in conveyor vision

In the modern world, investors and society demand transparency from companies not only regarding profits but also regarding their impact on the environment, society, and governance. These aspects are united under the concept of ESG. The problem is that companies present their ESG reports as long, unstructured texts, such as

Deforestation Monitoring for AI-powered Tagging utilizes a decadal set of satellite-derived climate data and related information to detect habitat loss over multiple years. It combines programmatic access, standard frameworks, and native Python tools to enable teams to quickly discover and process information. This approach reduces noise and seasonality by utilizing

Effective carbon footprint calculations begin with robust data annotation, which forms the backbone of AI models. In an era where transparency and accountability for greenhouse gas emissions are essential for businesses and government organizations, well-organized and structured data labeling not only facilitates accurate climate impact assessment but also streamlines internal

Today, any large company or state institution, whether a bank, a pharmaceutical company, or an environmental agency, constantly faces an avalanche of new laws and regulations. The problem is simple but massive, as information about all these updates is scattered everywhere. It is contained in a vast number of sources,

Legal investigations increasingly rely on automated tools that can process thousands of emails and documents in a matter of hours. Machine learning enables systems to quickly identify patterns, highlight relevant information, and reduce the workload on analysts. Manual verification remains a crucial step, ensuring the accuracy and contextual relevance of