Natural Language Processing

Making data more human

Today, around 70% of total enterprise data is available in the unstructured or more precisely textual form. This comes from information stored across enterprises and includes information of employees, company purchase, sale records, business transactions, the previous record of organizations, social media etc. While this data provides valuable context to enterprise performance areas, it is largely unused due to the inability of tool-sets to process it and huge effort needed to skim through it.

How It Works

We bring our expertise in Natural Language Processing (including Natural Language Understanding and Generation) and Text Mining to understand this textual information and generate insights. Traditionally, the challenges involved with processing data are related to understanding ambiguities and intents which are related to lexicons, syntax and reference. Using advanced techniques and machine learning based algorithms we create summaries which can be used for further insights.

We can process text from a wide variety of source formats like images, PDFs, web, social media etc. with varying resolutions using a variety of scalable and advanced machine learned based pre-processing techniques. The steps include:

Lexical Analysis

Syntactic Analysis

Semantic Analysis

Discourse Integration

Pragmatic Analysis

Use Cases

Entity recognition and summarization for legal and contracts

Text classification for a variety of use cases such as customer service, product insights etc.

Sentiment analysis

Intelligent Conversational interfaces, e.g. for customer service and decision support

Creating insightful summaries for researchers

Automating business processes such as claims and new business acquisition to focus human effort on complex and critical tasks