If one had to list three keywords that characterize our Data Science Team, they would be Artificial Intelligence, Machine Learning and Natural Language Processing. AI-related projects are handled with high expertise in their complexity – what makes our team unique is that we are able to carry out each element of an NLP project from data gathering and processing to data analysis thank to the rigorous work of our statisticians and linguists. In addition, we focus not only on one aspect of NLP, but have a holistic view of it.
Every customer desires a product without bugs. Although we are aware of the fact that there is no faultless product on Earth, we constantly test our solutions to be able to provide our customers with high-quality products. Reliability is ensured by meeting international standards (ISTQB), by running both manual and automatic tests. We believe, the earlier stage QA is introduced to the lifecycle of a project, the better the performance of our products are and the costs are reduced.
What differentiates our solution from other search services available on the Internet is the expertise of our search team. We have already built searches on Lucene-based search solutions, Solr and Elastic Search and developed plugins to them. We are able to take the linguistic features into consideration while search building, to provide access control in enterprise environment and to build scalable search systems. Our efficient searches aim to support the business processes of your company.
Our front-end developers work hard to realize what our customers imagine, namely to develop software that provides the best user experience. We do not only bring your initial sketches of ideas into life, but we also suit our software to your needs in every step of the process, being committed to the agile approach. The task that is performed when you click on any item is programmed by our back-end developers. They are also responsible for the smooth and quick performance of the software, co-operating with the Operations Team.
Supervised Machine Learning (ML) cannot be implemented without annotators, since – in opposition to unsupervised ML – training data is provided with meta-data by human experts. Statistic methods learn on the basis of this data and their performance is measured in line with it, too. Our team has 5 years of experience in well-known annotation tasks, like classification, scoring, named entity recognition, emotion and sentiment analysis. They are engaged both in internal and external projects.
Whenever you have an innovative idea that can be accomplished within the framework of TAS, our Business Analysts help you take the first steps towards solution. We are at your disposal to articulate a clear project goal, the requirements that have to be met by the solution that is ordered, the desired outcomes and the tasks that lead to the success of the project. Moreover, we also undertake the role of a mediator who mediates between customer and technical specialists.
