The Technologies OXILATE Has Developed
Enterprise Content Management Platforms
& Process Automation Support
OXILATE has made strides in the field of artificial intelligence by successfully implementing the latest technologies to upgrade Process Automation Support and Enterprise Content Management Platforms on a European level. The global Enterprise Content Management market was valued at $6 billion in 2017 and is expected to grow at a CAGR of 10-19% in the coming years, with M-Files being named as a “Visionary” and “Leader” in the industry, amongst other notable participants including IBM, Hewlett Packard, Microsoft, Newgen Software, OpenText Corporation, Oracle, and Xerox.
One of the key ways OXILATE has achieved its goals is by integrating machine learning into automation systems. Machine learning algorithms allow newly developed systems to adapt and improve over time, which makes them more efficient and effective at automating processes. Furthermore, OXILATE has implemented natural language processing technology, which allows systems to understand and respond to human language, making it easier for users to interact with the automation systems.
One of the key aspects of OXILATE’s AI implementation is the use of deep learning algorithms. These algorithms are capable of analyzing large amounts of data and making predictions, which are essential for automating complex processes. Our systems are able to not only automate routine tasks, but also make decisions, identify patterns, and make predictions. We have also made significant investments in cloud-based AI and edge computing, which enables our systems to analyze data and make decisions in real-time, even in remote or disconnected environments. This has been especially important for industries such as manufacturing and logistics, which rely on real-time data to make critical decisions.
Overall, OXILATE’s successful implementation of the latest AI techniques has allowed us to provide cutting-edge process automation support to our clients across Europe. Machine learning, natural language processing, deep learning, cloud-based AI and edge computing have made our systems more efficient, effective, and adaptable, leading to increased productivity and cost savings for our clients.
Valmet, a leading global developer and supplier of technologies, automation, and services for the paper & pulp, oil & gas, and energy industries, has actively collaborated with M-Files to improve its current technologies, while M-Files provided intelligent information management solutions using metadata, open architecture, and AI to automate and simplify how users interact with information. Valmet’s goal of becoming a global champion in serving its customers throughout all key processes, from product development to commercialization of new solutions, is reflected in its comprehensive services that range from maintenance outsourcing to mill and plant improvements and spare parts.
Product Life-cycle Management Support Tools
OXILATE has precipitated the development and implementation of the latest AI technologies in Product Life-cycle Management Support Tools, which are designed to help businesses optimize their product development and management processes. This has resulted in cost savings and increased efficiency.
One of the key innovations OXILATE has implemented is the use of machine learning algorithms to analyze and predict product demand. By analyzing historical data and patterns, these algorithms can accurately forecast demand for a product, allowing companies to better plan their production and inventory levels. Significant cost savings have been achieved for businesses as they are able to avoid overproduction and wasted resources.
Another area in which OXILATE AI technologies have had a positive impact is in the optimization of supply chain management by using predictive analytics. Companies can identify and address bottlenecks in the supply chain, which will result in faster and more efficient product delivery. This not only benefits the company but also the environment as it reduces waste and the need for unnecessary transportation.
OXILATE has also developed AI-powered tools to improve the design and development of new products. By using generative design algorithms, companies can explore a wide range of design options, resulting in more innovative and cost-effective products.
In addition to cost efficiency, OXILATE’s AI technologies also have a positive impact on the environment. Optimizing production processes and reducing waste, businesses can significantly reduce their environmental footprint and can help them meet sustainability goals and comply with regulations.
A new generative engineering tool for OXILATE has been successfully implemented by the Siemens Industry Software portfolio, which provides advanced mechanisms for supporting engineers in early-phase system design. Through software-based methods, OXILATE reduces the need for expert support and reduces the adoption barrier for its products. Oxilate has developed an intelligent user assistant tool that allows users to design new systems with minimal use of traditional training, tutorials, and documentation.
OXILATE, in collaboration with Siemens Industry Software, has achieved this goal by developing a Studio Inspector demonstrator. Using this tool has enabled customers to become more autonomous in the use of the product, making it easier to master through the provision of active recommendations based on user intent. Additionally, the Studio Inspector provides real-time expert-level support through a digital assistant, which is more efficient than relying on human experts. User feedback in the Studio Inspector helps us understand the product’s behavior, making it a successful implementation.
Digital Expert Decision Support Systems
Through international collaboration in the field of artificial intelligence, OXILATE has developed digital expert decision support systems over the past three years that are now being used in a variety of industries, including healthcare, finance, and manufacturing.
One key area in which OXILATE has made significant progress is the development of machine learning algorithms that can analyze large amounts of data and make accurate and reliable predictions. These algorithms are being used to improve decision-making processes in a variety of industries, from predicting patient outcomes in healthcare to identifying fraudulent financial transactions. A focus has been on the use of natural language processing to improve communication and collaboration between humans and AI systems OXILATE has developed NLP-based systems that can understand and respond to spoken and written language, making it easier for people to interact with AI-based decision support systems.
Besides these technical advancements, OXILATE has also worked to ensure that its systems are secure and compliant with data privacy regulations. It has implemented strict security protocols and obtained certifications from leading industry standards bodies. Through international collaboration and a commitment to staying at the forefront of AI development, OXILATE has been able to create cutting-edge digital expert decision support systems that are making a real impact in a variety of industries, and as a result, is opening up a new market surplus. By partnering with top research institutions and technology companies from around the world, OXILATE has been able to stay at the forefront of AI innovation and development.
TYP and SII Concatel have successfully implemented an AI-enabled collective intelligence solution for traditional SMEs in the insurance sector. It addresses the need for SMEs to adapt to a changing market, where traditional commercial channels are decreasing and competition is leading to margin reduction. Additionally, the solution addresses the challenge of constantly optimizing existing processes and providing added value throughout the service and product lifecycle.All company knowledge is dynamic and depends on different data sources, representations and experts throughout the lifecycle. This is particularly important in the insurance industry because it is facing a significant challenge with 25% of its workforce retiring from 2018.
The solution leverages machine learning and artificial intelligence to provide enhanced techniques for building, populating, and managing data, while neural reasoning and knowledge graphs provide key insights. Database technologies provide a trustworthy guarantee that records have maintained their integrity since publication, which helps to comply with regulations. TYP and SII CONCATEL implemented a solution that has generated GDPR compliant services such as Auditable, Enhanced onboarding, Better KYC capabilities, Churn rate improvement, Upselling and Cross-selling opportunities, and new services and products. TYP and SII CONCATEL are confident that this successful implementation will provide new opportunities in the insurtech domain.
Process Automation in Digital Twin Applications
OXILATE, our international innovation project that has been making waves in the field of process automation through the development of advanced artificial intelligence technologies, focuses on using digital twin applications to enhance the efficiency and effectiveness of various industrial processes.
One of the key technologies developed by OXILATE is the use of machine learning algorithms to optimize process control systems. These algorithms are able to learn from historical data and make predictions about future performance, allowing for real-time adjustments to be made to the process. This leads to increased efficiency and reduced downtime, resulting in cost savings for the industry. Another important technology developed by OXILATE is the use of digital twin models to model industrial processes. These models are capable of replicating the behavior of real-world systems, allowing for virtual testing and optimization before implementation. This can lead to significant cost savings, as well as the ability to identify and address potential issues before they occur in the real world.
OXILATE’s technologies are already being implemented in a variety of industries, including manufacturing, energy, and healthcare. For example, in the manufacturing industry, the use of digital twin models is allowing companies to optimize their production lines and reduce waste. In the energy sector, machine learning algorithms are being used to optimize the performance of power plants and reduce emissions. And in healthcare, digital twin models are being used to simulate the human body and aid in drug development.
TurkTraktor has successfully implemented a cutting-edge technological innovation project that focuses on energy efficiency in the paint shop process. The new system has reduced energy consumption by monitoring and analyzing key parameters, and using this data to guide improvement initiatives. Through the use of a Digital Twin Application, we were able to centralize data collection and analysis, streamlining the process and saving valuable time for our experts. Furthermore, we were able to identify key relationships between parameters and energy consumption, and use this information to guide the development of more effective improvement projects.
The success of this project has demonstrated the potential for the Digital Twin Application to be expanded to other paint shop processes in the automotive industry, as well as other critical processes across various industries. We are looking forward to further exploring the potential of this innovative technology to drive energy efficiency and cost savings for our clients, and with continued research and development, we can expect to see even further advancements in the near future.