Extract knowledge from the data and make better decisions
Raw data is not enough. In order to better understand your business and be able to improve it, you need the right answers to specific questions. We know how to implement systems that find such answers in large data sets. This is Machine Learning.
Why should I use Artificial Intelligence in my business?
Artificial Intelligence technologies aim to reproduce or surpass abilities in computational systems that are generally deemed intelligent if performed by a human. Many businesses use AI technology to try to reduce operational costs, increase efficiency, grow revenue and improve customer experience.
Use insight to predict customer preferences and offer them a better, personalized experience
As your business grows the data surrounding it also grows in volume. However, as the volume of data surpasses the ability for humans to make sense of it, we can use machine learning to learn from that data and changes in the data to provide valuable insights.
Not so long ago the use of machine learning was considered novel. Nowadays it’s rapidly becoming an expected feature. Just as we expect companies to have websites that work, the time will come when it will be expected that technology will be personalized, insightful and self-correcting.
Don’t fall behind other companies and learn today how Artificial Intelligence may help with your business!
Natural Language Processing (NLP)
Natural Language Processing is a subcategory of an AI technology that allows a machine to recognize and decipher the nuances of human language. It organizes unstructured data by analyzing it for relevancy, differences in spellings, correlation, and semantic meaning. It tries to understand different lexicons, grammatical syntaxes, and the relation between words and phrases, just as a human does.
NLP technologies include:
- Question answering
- Creating chatbots or personal assistants
- Sentiment analysis – determine whether data is positive, negative or neutral
- Text analytics
and many more.
Machine learning-based recommendation systems are powerful engines using 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 the in-store customer care and personalized shopping experience, offered by a real salesperson who provides an undecided purchaser with expert guidance, in a virtual environment.
Benefits of recommendation systems:
- Better user experience
- Focus on the right product
- Sales drive
- Data-driven decision-making
We can provide different ways of cooperation. We can work as an extension of your team or take the entire project.
Our highly skilled employees cover a wide range of capabilities. Whether you need AI components for your application or non-AI we can take care of it.
We can build whole “ecosystems” of applications.
A nearly decade of experience in e-commerce and various other business fields helps us better understand your field and respond to your needs.
Our area of expertise includes:
- Designing and implementing a Machine Learning pipeline for learning, assessing, and deploying models (TensorFlow Extended, PyTorch, etc.)
- Designing and implementing dedicated models from Artificial Intelligence, Machine Learning, Mathematics, and Statistics area
- Implementing technical environment for the implemented model such as dedicated API and integration with currently working software
- Research and development work regarding AI/Machine Learning
- Designing whole architecture – databases, servers, clusters – to fit Big Data needs