Your fast-track to AI
To simplify this, we are orchestrating GFT's AI and data expertise and solutions at the GFT AI.DA Marketplace.
Discover selected solutions and use cases
High-resolution cameras capture detailed images of machines and products in the manufacturing process. These images are then analyzed by image processing algorithms based on artificial intelligence (AI) and machine learning (ML) to detect the smallest defects or deviations with extreme precision. This data-driven approach, hosted on a cloud platform, provides real-time insights and ensures accurate quality control.
- Increased quality
- Reduced reworks and rejects
- Increased throughput in production
- Increased customer satisfaction
Virtual assistants and tools to automate customer interactions, understand and resolve common queries, free up customer service employees for more complex issues and human interaction.
- Increased customer satisfaction through faster response times
- Overall improved customer experience
- Freeing up staff to deal with more complex issues
Generative AI techniques are used to optimize the way code is created. It massively accelerates the entire development life cycle, intelligently automating and supporting everyday tasks. This spans from pure coding to documentation, vulnerability assessments and test case generation.
- Productivity increase*: Free up software development experts to take on more vital parts of the digital transformation journey, i.e. platform modernization
- Quality improvements: Decrease in bugs and vulnerability gaps, mitigation of risk for technical debts
- Supports staff training and increases motivation
- Enhanced focus on sustainability (GreenCoding)
* own analyzes: coding up to 45%, reviewing code up to 30%
In today’s manufacturing facilities, IoT is a vital element. Machines and logistics equipment are connected by sensors to a digital shop floor management system. It visualizes real-time data on production status as well as key performance indicators on a central dashboard.
Real-time transparency, automated reporting and documentation lead to
- Increased operational efficiency
- Improved decision speed
- Better decision quality
- Increased staff motivation
Utilizing AI in energy management, the system anticipates energy consumption patterns and recommends adjustments based on historical data, weather forecasts and real-time demand.
- More accurate energy distribution
- Reduced operational costs
- Minimized environmental impact
- Enables management of potential energy inefficiencies before they escalate
Leveraging advanced algorithms and pattern recognition, fraud detection systems analyse vast amounts of transactional data to identify and flag suspicious activities in real-time.
- Enhancing trust and security for users
- Minimize expenditure for unjustified transactions
- Ensuring compliance with prudential standards relating to fraudulent activities
Manufacturing Analytics utilizes data-driven insights to enhance and streamline production procedures. Through data from IoT sensors in equipment and machinery, both real-time and historical information on performance, quality and efficiency metrics can be accessed and visualized. Advanced data analytics tools, fused with artificial intelligence (AI) and machine learning, delve into this extensive data, pinpointing inefficiencies, forecasting possible disruptions and recommending enhancements. Situated on cloud platforms, these analytics present manufacturers with an all-encompassing view of their operations, facilitating profoundly informed decision-making.
- Enhanced operations efficiency
- Proactive problem-solving
- Data-driven decision making
Voice-assisted workflows harness the power of speech recognition and natural language processing (NLP) to streamline operations. By integrating smart devices and cloud-based platforms, users can interact, issue instructions and receive feedback through purely verbal commands. These voice commands, processed by advanced AI algorithms, facilitate real-time task management, data retrieval and system control.
- Hands-free and more intuitive user experience
- Increased productivity
- Reduced manual input errors
- Enhanced ability for multitasking in dynamic work environments
Using AI, knowledge acquisition gathers and organizes expert information from various sources. This allows almost anyone to easily and quickly answer even the most complex queries. Not just pulling existing knowledge, the technique also discovers new insights through generative AI models.
- Quick access: Effortless and rapid retrieval of complex information
- Continuous update: Always up-to-date through regular knowledge expansion
- Competitive edge: Informed decisions provide a market advantage
Predictive maintenance utilizes data-driven techniques to forecast equipment failures, enabling timely maintenance and preventing unplanned downtime. AI's significance lies in its capacity to rapidly analyse vast amounts of data from sensors and logs. Through machine learning, AI identifies patterns and anomalies, predicting impending equipment failures with increasing accuracy over time.
- Reduction of unplanned downtime and maintenance costs
- Optimized production schedules and increased operational efficiency
- Extended machine life
Design and implementation of production-ready AI and data platforms, empowering clients to create, host, and manage their bespoke AI applications and use cases efficiently. Deployment, monitoring, and serving of machine learning models, complete with MLOps implementation for seamless performance and optimisation.
- Standardized methodolgies and tools
- Documented and transparent platform
- Streamlined AI integration into existing infrastructures
- Ability to adapt swiftly to evolving business needs
Project Portfolio Management
Project Portfolio Management
Project Portfolio Management (PPM) leverages cutting-edge technologies to strategically organize and oversee an organization's suite of projects. By integrating data analytics, cloud computing, and AI-driven insights, PPM provides a holistic view of all projects, ensuring alignment with business objectives. This approach enables prioritization of initiatives, resource allocation, and risk assessment in real-time.
- Strategic focus: Align projects with business goals
- Lean budgeting
- Cost reduction