Natural Language Processing
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
NLP empowers enterprises to decode unstructured textual data, unlocking insights from diverse sources like employee information, sales records, social media, etc., that were previously untapped due to data complexity.
Expertise in NLP allows for the extraction of meaningful insights by overcoming challenges related to ambiguities, intent, and references within textual information.
Capable of processing text from various formats (images, PDFs, web content, social media) and resolutions, using scalable machine learning-based techniques, ensuring adaptability to diverse data sources
Expertise in NLP allows for the extraction of meaningful insights by overcoming challenges related to ambiguities, intent, and references within textual information.
Offers diverse applications like entity recognition for legal documents, intelligent conversational interfaces for customer service, text classification for multiple industries, and automation of business processes, focusing human effort on crucial tasks
Provides insightful summaries for researchers and automates mundane tasks (like claims processing and new business acquisition), allowing stakeholders to focus on critical business aspects and complex problem-solving
Striking a balance between automation and human intervention, augmenting human abilities with automated data processing, aiding in more informed and efficient decision-making.