AI/Machine Learning

At Endora, we help companies leverage the potential of AI and machine learning in e-commerce and online business. We create and implement solutions that automate processes, personalize offers, increase sales, and provide a competitive advantage.

• Experience in designing and implementing AI solutions for e-commerce and B2B/B2C
• Automation of repetitive tasks and business processes
• Offer personalization, product recommendations, and dynamic pricing
• Data analysis, trend prediction, and customer segmentation
• Increased conversion, loyalty, and user satisfaction
• AI integration with existing systems (ERP, PIM, CRM, sales platforms)

Natural Language Processing is a subcategory of artificial intelligence technology that allows a machine to recognize and decipher the nuances of human language. It organizes unstructured data, analyzing it for relevance, spelling differences, correlations, and semantic meaning. It attempts to understand various lexicons, grammatical syntaxes, and relationships between words and phrases, just as a human does. Natural language processing technologies include:

• Question answering
• Creating chatbots or personal assistants
• Sentiment analysis – determining if data is positive, negative, or neutral
• Text analytics

and much more.

Machine learning-based recommendation systems are powerful engines that use machine learning algorithms to segment customers based on their user data and behavioral patterns (such as purchase and browsing history, likes, or reviews) and target them with personalized product and content suggestions. Recommendation systems help replicate in-store customer service and personalized shopping offered by a real salesperson, providing expert guidance to an indecisive buyer in a virtual environment. Benefits of recommendation systems:

• Better user experience
• Focus on the right product
• Driving sales
• Data-driven decision making

1. AI analysis and consulting

• Audit of AI implementation possibilities in your company
• Workshops and consulting on AI strategy
• Identification of processes for automation and optimization

2. AI solution implementations

• Product recommendation systems (cross-selling, up-selling)
• Content, offer, and customer communication personalization
• Dynamic pricing and promotions
• Customer service automation (chatbots, voicebots, automated responses)
• Data analysis and customer behavior prediction

3. Integrations and development

• AI integration with e-commerce, ERP, PIM, CRM platforms
• Development of dedicated machine learning models
• Automation of reporting and business analytics

4. Support and development

• Monitoring AI model performance and optimization
• Team training on using AI tools
• Ongoing technical support and development of implemented solutions

• Designing and implementing machine learning pipelines for model training, evaluation, and deployment (TensorFlow Extended, PyTorch, etc.)
• Designing and implementing dedicated models in the fields of Artificial Intelligence, Machine Learning, Mathematics, and Statistics
• Deploying technical environments for implemented models in the form of dedicated APIs and integration with currently operating software
• Research and development in AI/Machine Learning
• Designing entire architectures – databases, servers, clusters – for Big Data needs