PrincipAI

Excels in sequential decision making and time series prediction

Helping businesses solve their real-world problems.

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PrincipAI

Principles of Applied Artificial Intelligence

Our Vision

 

PrincipAI’s team of researchers undertake R&D for novel artificial intelligence algorithms that are applicable to financial trading, demand prediction, price forecasting and dynamic pricing including natural language processing in both English and Turkish languages. Besides, PrincipAI develops solutions not limited to some specific AI tasks, but also performs research on the development of next generation AI based solutions that learn how to learn.

PrincipAI’s novel product, NB-FT, which is recently funded by TÜBİTAK and supported by Boğaziçi University, is a one of its kind automated financial price and movement prediction platform. We have been gathering and analyzing large amounts of numerical and textual data both in English and Turkish languages to generate trading signals. NB-FT combines state of the art machine learning well-engineered models to make sequential financial trading decisions and take actions accordingly without human intervention so to maxim ize the long-term financial gain.

 
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Our Services

 
  • PrincipAI develops language understanding models to perform emotion and sentiment analysis of natural language data used for various purposes.
  • NB-FT is our financial forecasting and trading platform that incorporates the state-of-the-art AI models.
  • As PrincipAI, we build and deploy well engineered AI models that are customized to our customers’ needs. This way, we help them to improve their business processes and reduce costs through an end-to-end integration together with the power of cloud computing at the back office.
  • PrincipAI provides consultancy on data science related projects such as churn analysis, customer segmentation, new product valuation, building recommendation systems.
  • PrincipAI augments the machine learning approaches with social network analytics to exploit information obtained from network structure.

Follow our projects on Github:

 

Our Team

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