AI AUTOMATION
Artificial intelligent¹ and machine learn² are not magic, but a tool.
Today, it is a practical way to speed up business processes, remove routine from people, and make decisions based on data rather than intuition. We mean applied technologies that learn from examples, look for patterns and help to see what a person does not have time to notice.
A well-chosen solution provides a competitive advantage: you react faster to market dynamics, reduce costs and increase forecast accuracy.
The main thing is to understand where it really benefits the business and where it remains an expensive toy.
Today, it is a practical way to speed up business processes, remove routine from people, and make decisions based on data rather than intuition. We mean applied technologies that learn from examples, look for patterns and help to see what a person does not have time to notice.
A well-chosen solution provides a competitive advantage: you react faster to market dynamics, reduce costs and increase forecast accuracy.
The main thing is to understand where it really benefits the business and where it remains an expensive toy.
¹ AI (artificial intelligence) is a general term for systems that solve problems that require "human" thinking: data analysis, language understanding, and decision-making.
² ML (machine learning) is one of the approaches within AI, where the algorithm is not hard-coded, but learns from examples and gradually improves its predictions.
² ML (machine learning) is one of the approaches within AI, where the algorithm is not hard-coded, but learns from examples and gradually improves its predictions.
WHAT IS AI/ML
USEFUL FOR
- REPETITIVE TASKS WITH A LARGE
AMOUNT OF DATAClassification of letters and applications, automatic moderation, document recognition, working with images or videos. - FORECASTING
AND PLANNINGInventory balances, dynamic pricing, demand forecast, predictive maintenance of equipment. - PERSONALIZATIONProduct recommendations, adaptive mailing lists and smart chatbots that adapt to user behavior.
- ANALYSIS OF SIGNALS
AND ANOMALIESFraud detection in transactions, security monitoring and quality control in production. - NATURAL LANGUAGE
PROCESSINGMultilingual support, text summarization, intelligent internal database search.
THE APPLICATION
IS ADVISABLE
- AMOUNT OF DATABusinesses with chaotic or fast-growing data flows: e-commerce, logistics, fintech, media.
- ACCURATENESSIndustries with a high cost of error: medicine, production, energy.
- VELOCITYCompanies where reaction velocity is critical: customer support, exchange operations, supply management.
Automation requires:
■ structured information from CIS, archives, sensors;
■ clearly defined targets: reduction of waste, energy savings, reduction of downtime or others.
■ structured information from CIS, archives, sensors;
■ clearly defined targets: reduction of waste, energy savings, reduction of downtime or others.
Automation is a gradual process. It is advisable to implement it on one site, rather than the entire enterprise at once.
This approach allows you to recoup the project by reducing defects and downtime even before scaling to the entire line.
This approach allows you to recoup the project by reducing defects and downtime even before scaling to the entire line.
AI automation is not about "making it beautiful". We need high-quality source data, a clear metric of success and thoughtful integration into processes.
Sometimes conventional automation or well-configured rules are cheaper and more reliable.
Contact us and we will figure out the problem and advise you!
Sometimes conventional automation or well-configured rules are cheaper and more reliable.
Contact us and we will figure out the problem and advise you!
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