Even though AI was founded more than 60 years ago, it has exploded very recently. This mostly has to do with the emergence of powerful hardware, cloud and mobile technologies that allow handling and processing of Big Data.
Lemberg team leverages these opportunities to develop Machine Learning (ML) algorithms that turn Big Data into meaningful information for the end users. Reach out to us to learn how your product can generate exceptional value powered by AI.
Our data science team combines excellent engineering skills and academic knowledge in machine learning and artificial intelligence.
Sensor data processing to track and analyze object behavior and location (e.g. people, animals, transport).
Sound recognition to process and analyze voices and sound patterns, and detect unusual or undesirable sounds in the environment.
Computer vision to locate, track and analyze object appearance and behavior on photo and video.
Natural language processing to build chatbots, content recommendation engines, and other tools that analyze a text in one or several languages.
Data science team
Experience in consumer, industrial and medical projects
Took part in academic and commercial research
Own tool-set for data analysis and cleanup
Data science team
How we work
Brief information on the experiments carried out during the research, their methodology, the result obtained and their interpretation
Implementation of developed algorithms in form of Prototype
A model obtained as result of data processing with machine learning algorithms in form of neural network, configured fuzzy logic controller, mathematical formula etc.
Tuning and optimizing of algorithm for better performance
Data sets contain the value of informational parameters of the modeling object and are used to construct and validate an information model of object or process.
Report with results of comprehensive Field testing of the prototype and their interpretation
Description of the principle of the functioning of solution
For the know-how found during the research, technical documentation for the registration of a patent for a utility model may be prepared.