The project aimed as an innovative app, that can help doctors to receive targeted newsletters, build communities and organize events. Muteki Group has developed an AI-powered mobile application. The medical news app analyzes unique personal preferences and AI technologies help doctors to get the news with a high level of personalization. Application: Analyzes all collected data; Gives targeted news; Invites doctors to join special communities in accordance with their specialization and common interests.
Muteki Group
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4.6★★★★★1 reviews8 Portfolio
Muteki Group Portfolios
Web platform for tracking and analyzing stock price changes on the stock exchange
Mobile application that shows personal analytics and analyses data. Can be connected with different devices, such as fitness trackers, or show social networks activity.
Web solution and a chatbot to assist entrepreneurs through the steps of starting a business. The main requirements were to develop a system that can help entrepreneurs crystallize the idea, lead them on where to go for business consultation, guide them on how to get financial support, and guide them on how to set up a company.
Our client approached us with the challenge of analyzing large volumes of research articles in their field. They needed a solution that could extract important terms, establish relationships between them, and create a summary and knowledge graph of connected terms. Problem: The problem was that the amount of research being published is increasing rapidly, and manually analyzing and extracting key information is time-consuming and error-prone. Our solution was to develop an AI-powered system that could automate the analysis process and provide more accurate and efficient results. Solution: Our team of experts developed a deep learning and natural language processing (NLP) system that could extract important terms from the articles, establish relationships between them, and create a summary and knowledge graph of connected terms. The system uses advanced NLP techniques, including Biobert and Scispacy, to accurately analyze the biomedical text. Result: The result was a system that could automatically analyze and extract key information from biomedical research articles, providing our client with a more efficient and accurate way to process large volumes of data. This allowed the client to focus on the most important findings and make informed decisions faster.
Project short description: This project focuses on leveraging AI technologies to optimize warehouse and inventory management processes. Problem: The client encountered challenges in attaining customer satisfaction, controlling operational expenses, preventing stockouts, and optimizing procurement processes. These obstacles impeded their capacity to promptly deliver superior products and efficiently meet customer demands. Solution: Muteki Group developed an AI-powered system for inventory and warehouse management. The solution involved utilizing AI algorithms to detect defective products and packaging, implementing predictive inventory alerts for automated replenishment and supply network adjustments, analyzing historical data to forecast demand, and automating procurement through vendor matching and anomaly detection. Result: The implementation of the AI-driven warehouse management system yielded several positive outcomes for the client. These included reduced customer complaints and returns due to improved quality control, enhanced operational efficiency, cost savings from optimized inventory levels, minimized stockouts, and streamlined procurement processes.
The project involved digital transformation using Computer Vision and NLP technologies to recognize various types of documents and extract necessary information. Problem: The client faced the challenge of using multiple document types for various business scenarios, which led to the need to digitize all paper documents and organize them based on client details. Solution: The client collaborated with Muteki Group to develop an AI solution using Computer Vision and NLP technologies to recognize various types of documents and extract necessary information by fields.The solution aimed to convert paper documents into digital format and sort them according to client specifications. It had the ability to identify different document types and extract relevant information from specific fields, which led to a significant improvement in the accuracy and efficiency of the extraction process. Result: The project was completed successfully within the designated timeline, achieving an accuracy rate of 87% in the text extraction process. The client was satisfied with the outcomes and expressed positive feedback.
Fashion retail, both physical and online has hardly any personalization and uses very little data and technology when offering products. At the same time, over 70% of consumers expect personalized shopping experience. We want to offer personalization and at the same time the shopping convenience for people that dont like shopping or dont have time for it. Muteki Group developed a scalable web system using AWS services. Our AI solution analyses 100 data points and suggests outfits for customers taking into consideration their preferences, previous purchases and matching them with latest fashion trends. The system can generate hundreds of outfits in several minutes.