Saama Technologies, Inc.

Vidya Sagar Anisingaraju

Haranath Gnana

Suresh Katta

Rajeev Dadia

Krunal Patel

Prashanth Talanki

Anil Nair

Ghananeel Gondhali

Methods and apparatuses for generating insights for improving an organization from unstructured and structured data. Natural language processing is employed to process the aggregated data from various data sources to create topics and the features that impact the topics. These topics are then used to generate recommendations to improve customer satisfaction with the organization.

Data analysis using natural language processing to obtain insights relevant to an organization

Methods and apparatuses for creating data analysis (DA) systems for generating insights (also known as results) from a plurality of data sources without requiring the designer/implementer of the DA system or the user to understand complicated technology details such as for example coding, big data technology or high-end business analytics algorithms.

Abstractly implemented data analysis systems and methods therefor

The present invention relates to systems and methods for cloud based consumer sentiment analysis with social insights. Data is integrated from a plurality of data sources, including a structured data source, an unstructured data source, a social data source, and a syndicated data source. Key attributes are selected from the integrated data, and may be name value pair requests. From these key attributes, consumer segments, sentiments and attribute correlations may be generated. The segments are generated from the social data. The correlation is generated using clustering algorithms. In some embodiments, generating sentiment and generating correlations dynamically utilizes models according to attributes of the integrated data. Polarity, emotion and topicality may be calculated for the generation of visualizations.

Systems and methods for analyzing consumer sentiment with social perspective insight

Methods and apparatuses for organizations to monitor, analyze and respond to unstructured and structured data that is related to their Governance, Risk, and Compliance (GRC) programs. Embodiments of the invention generated mapped Risk Control Matrices (RCMs) and/or insights for improving the GRC process from unstructured and structured data. Natural language processing is employed to process the aggregated data from various data sources to create attributes and contributors. The attributes and weighted contributors are processed to form mapped RCMs and/or GRC-related insights.

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San Jose, CA, United States of America

Vidya Sagar Anisingaraju