OSI is a part of the AI movement.

With the global digital therapeutics market size anticipated to reach $9.4 billion by 2025 and increasing awareness in preventive medicine, personal health and wellbeing, costs saving, the time to take advantage of this growing market is now.

Our deep experience in behavioral analytics and AI-powered software is focused on creating better patient care, increasing treatment efficiencies, and improving the clinical outcome for both patients and practitioners. We achieve that by building products to manage, monitor and prevent eating disorders, mental health and enhance personal fitness. In combination with our vast experience in mobile, web and user experience, we are able to offer you the complete solution in leveraging the AI opportunities that can best work for your unique needs.

Machine Learning in Chatbots

A subdivision of AI, the goal of machine learning is to enable computers to learn on their own.

Machine learning algorithm enables it to identify patterns in observed data, to create models that explain the world and predict things without being explicitly pre-programmed.

One of the most popular and fast-growing uses of machine learning is in chatbots. The global chatbot market is expected to reach $1.25 billion by 2025. According to research, more consumers now prefer communicating with chatbots for customer service issues. Chatbots are about to become fully capable of simulating human-like conversations and delivering improved customer experience across various text and audio platforms.

We at OSI don’t see chatbots as a novelty but as a future entry point for any and all digital content. Chatbots can act as a guide to help people easily and comfortably navigate any complex tool seamlessly. Chatbots are also extremely engaging. OSI has built a proprietary chatbot platform so we can help companies take their current apps and content and turn them into chatbot-guided experiences which can dramatically improve engagement and lower costs.

Natural Language Processing in Digital Humanities and Computational Social sciences

Knowing not just the text, but the meaning of the text allows us to classify and process large sets of free form text in ways that have not been possible until now, presenting organizations with huge opportunities to explore and benefit from it.

Text mining is the process, which gives us ‘’access’’ to that high-quality information. Text mining refers to a specific Data mining area, which is characterized by the fact that the primary data is not presented in a structured form such as tables, records etc, but as a free form text i.e. unstructured. In fact, as researchers note, this is the data in over 90% of available information sources, containing extremely valuable information and huge potential for extracting useful knowledge.

In essence, Text mining tasks are very close to the Data mining tasks (classification, clustering, associative rules, etc.), but the main problem in solving them is related to the unstructured representation of the data in free text and the variety of forms of expression as well as the intrinsic morphological structure and richness of the natural language.

When dealing with natural language texts, the most critical problem is ambiguity and uncertainty issues, which makes semantic extraction a challenging task. The main approaches to overcome this comes in the form of (1) Natural Language Processing (NLP) and (2) Methods based on the statistical analysis of the content of the text and the discovery of its determinants and links between them which may serve to identify and categorize it.