Industry challenges
Lack of production efficiency
Many industrial enterprises lack efficiency in their production processes. Delays, errors and downtime often occur, affecting product quality and production costs.
Data management
The industry generates huge amounts of data, which is often unused or collected in an inefficient way. Lack of effective data management limits your ability to make informed decisions.
Quality monitoring and maintenance
Monitoring product quality and keeping equipment in good condition is a challenge. Production errors and machine failures can lead to financial losses and reputational damage.
Our solutions
Vision systems and error detection
Thanks to cameras and vision systems with AI, it is possible to automatically detect production errors and increase precision in assembly processes.
Predictive Maintenance
The use of AI to monitor the condition of machines allows you to predict failures and plan maintenance in advance, which reduces repair costs and ensures production continuity.
Automation of production processes
AI can be used to automate various stages of the production process. Industrial robotics driven by artificial intelligence can speed up assembly, packaging and other production activities, as well as increase workplace safety.
Natural language processing (NLP) and OCR systems
NLP-based solutions can analyze and interpret texts including service reports, customer reviews and messages. OCR solutions make it possible to read documents that previously existed only in paper form. Thanks to these solutions, companies can quickly respond to problems, identify market trends and analyze customer feedback. Moreover, AI-powered chatbots and voice bots can provide 24/7 customer support.
Reducing waste
AI can be used to minimize waste of raw materials and products by monitoring and optimizing production processes. AI systems analyze production data and help identify sources of losses and suggest ways to reduce them
Logistics optimization
AI helps optimize logistics by monitoring deliveries, managing inventories and planning transportation routes. Thanks to this, companies can reduce costs and delivery times, which contributes to increasing the efficiency of the entire supply chain.
Creating personalized offers
AI can analyze data about customers and their preferences, helping companies create personalized offers and products. This increases customer loyalty and increases sales.
Requirements
Even though AI solutions are the future in the industrial sector, companies that want to use this technology must demonstrate an appropriate degree of innovation. What are these requirements?
IT infrastructure
Initial work on the algorithm can begin even if the company has data in paper form. However, full implementation of AI algorithms requires integration with existing IT systems such as MES or ERP.
Data collected
Our solutions are created for the needs of a specific client, so the systems always require learning based on the collected data. This can be vision, process and machine data, including IoT data. The more data of various types collected, the more accurate the algorithm will be.
Implementation support
Implementing AI solutions is a process that requires the support and involvement of company representatives. The target solution often requires organizing and organizing processes in the company, as well as training the staff who will use AI tools.