State-of-the-art artificial intelligence technology applied towards practical applications

Natural Language Processing

We are heavily invested in Natural Language Processing research and development. We know from experience working with clients in various industries that key decision signals are locked within massive amounts of information that cannot be processed manually.

Hence, our research leverages NLP techniques to unlock those signals and streamline the decision making processes.

  • Overview
  • Use Cases

Data Aggregation

Data is found in structured and unstructured formats. A well performing Natural Language Understanding algorithm can only be built when we choose the right training set. Our data aggregation process is the first step towards identifying right data set to train an NLU model which is followed by pipeline development to extract and collect that data in high volumes.

Data Processing

This is very important step in building NLU models. Once we collect the text data, we convert it to a format that a machine can understand. In NLP, we call it a vector representation of a text. A bulk of our R&D goes into finding ways to vectorize text for any specific domain rather than relying on readily available embedding techniques.

Model Development

The final step after vectorization is developing NLU models for specific use cases. For example, if we are doing a Risk Analysis on an entity, we want our model to identify the relation between a specific risk and how it pertains to multiple other entities. We do this through various statistical scoring mechanisms.

Technology Risk

Technology risk posses biggest threat to any businesses. Ranging from badly written code to improper architecture, any small vulnerability can bankrupt a business. We conduct a thorough research to identify technology risk in mobile application deployed in app store so you can take necessary precautions before it is too late. 

Trade Risk

Multinational trade poses a unique challenge in risk management. When goods and services are exchanged between two parties who have never met face to face, there is always an inherent financial risk. We use different data aggregation and verification method to identify financial risk in global trade.

Economic Risk

Political instability, pandemic and natural disaster pose a great economic risk for any business. Macro-economic factors like these bring about changes in government regulations, and fluctuation in exchange rates. Identifying these signals earlier through various public and private information sources can help businesses hedge against impending risk.