Language Technologies play a central role at Gradiant because they enable intelligent interaction, content understanding, and the development of trustworthy AI systems. We focus on text generation and on Natural Language Processing (NLP) and analysis.
We develop tools for automatic information extraction and classification from linguistic sources. Our work addresses challenges such as Retrieval-Augmented Generation (RAG), AI-generated text detection, and jailbreak prevention in large language models. We also focus on identifying and mitigating bias in AI-driven language systems to ensure fairness and transparency.
By combining linguistic knowledge with advanced machine learning, we deliver solutions that support the deployment of powerful, controllable, and ethical language models. Our tools enable fast interpretation and comprehension of texts or requests, improving accessibility and the processing of relevant information.
Large language models offer enormous potential but also introduce risks associated with unwanted content, bias, and external manipulation. At Gradiant, we research and develop model control technologies that allow real-time supervision, auditing, and adjustment of AI system outputs. We apply methods such as AI-generated text detection, jailbreak attempt identification, and continuous bias monitoring to ensure that responses are safe, consistent, and transparent. Our approach combines linguistic expertise and... Continue reading
The explosion of digital information requires tools capable of organizing and making sense of large volumes of textual data. At Gradiant, we develop categorization technologies that automatically classify documents, messages, or records based on their content, context, or intent. Our solutions integrate Natural Language Processing (NLP) and advanced machine learning to segment information in real time, detect patterns, and facilitate the discovery of relevant knowledge. This capability... Continue reading
In an environment saturated with information, the key is not merely accessing data but extracting what is truly relevant to each need. At Gradiant, we research and apply information extraction technologies capable of identifying facts, entities, relationships, or attributes within large text volumes, both structured and unstructured.
Our solutions combine NLP, Natural Language Understanding (NLU), and deep learning techniques to turn documents, articles, or communications into actionable knowledge.
