Artificial intelligence
Artificial Intelligence for Industry

WHAT WE OFFER YOU
Artificial intelligence is a strategic lever for optimizing industrial processes, improving quality, and automating repetitive tasks.
KyberEdge designs tailored AI solutions, ranging from the development of predictive models to the implementation of conversational agents (Copilot, ChatGPT) to streamline operational workflows.
We use AI to process large volumes of data, detect anomalies, support decision-making, and generate automatic insights.
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WHAT WE SOLVE
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Manual or repetitive processes that consume resources
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Difficulty analyzing large amounts of industrial data
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Lack of advanced tools for analysis, decision support, or operational assistance
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CUSTOMER BENEFITS
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Greater operational efficiency and intelligent automation
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Instant and personalized insights from your data
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Reduce operating costs and increase quality
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Seamless integration with existing systems (ERP, MES, CRM)
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WHAT WE DO
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We design customized industrial AI solutions
We integrate machine learning and deep learning models into production processes to turn data into operational value. -
Advanced operational data analysis
We collect and prepare data from sensors, machinery, and ERP/MES systems to train robust predictive models. -
AI model development and deployment
We implement ML/AI models (e.g., anomaly detection, demand forecasting, process optimization) on cloud or edge environments. -
AI integration into production systems
We connect AI model outputs with SCADA/MES/ERP systems to trigger automated actions or intelligent recommendations. -
Model monitoring and continuous improvement
We measure performance, retrain, and adapt models based on feedback, operating conditions, and new data.
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TECHNOLOGIES AND APPROACH
EXPECTED OUTPUT FOR THE CUSTOMER
TECHNOLOGIES AND APPROACH
Development of AI solutions on Azure ML, Azure OpenAI, Azure Foundry, and OpenAI for process automation and data processing
Use of Copilot Studio and ChatGPT to create conversational agents that integrate with business processes
Cloud-native architectures and microservices for scalability and reliability
Simplified integration with ERP, MES, CRM for centralized data governance
Application of generative AI to synthesize complex data, generate content, and automate decisions
Phased approach: rapid Proof of Concept leading to industrialized solutions

EXPECTED OUTPUT FOR THE CUSTOMER
Advanced KPIs and analyses produced by AI models, unattainable with traditional tools
Automation of high-impact operational tasks: document classification, event response, report generation, and summarization
Automatic and actionable predictive insights: operational suggestions generated from collected and processed data
Intelligent interfaces to reduce human intervention: dashboards and conversational agents that understand context and guide users
Automation of high-impact operational activities: reduction of repetitive tasks, automatic exception handling, real-time analysis, and reporting
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Interfaces for customers and suppliers
Communication with customers or external stakeholders
Interfaces for customers and suppliers
Communication with customers or external stakeholders
Interfaces for customers and suppliers
Communication with customers or external stakeholders