Traderbot, Inc.

Tao Automation Services Private Limited

Nagaraju Pappu

Tejpal Singh Chadha

Kenneth Allen Williams

Jawahar Bekay

Hariharamoorthy Theriappan

Amit Rajan

Embodiments of the present disclosure provide systems and methods for extracting entities from semi-structured enterprise documents. The method performed by a server system includes receiving an enterprise document in a semi-structured format. The method includes extracting document features from the enterprise document. The document features include structural, token-specific, and entity-specific features. Further, the method includes identifying candidate entities in the enterprise document based at least on a machine learning model which uses document features. The candidate entities include candidate tabular entities and candidate non-tabular entities. The method includes computing probability scores for the one or more tokens-corresponding to the candidate non-tabular entities and the candidate tabular entities, based at least on the machine learning model. The method includes extracting structured data from the enterprise document according to the candidate non-tabular and tabular entities based at least on the probability scores.

Machine learning methods and systems for extracting entities from semi-structured enterprise documents

A real-time financial search engine retrieves financial updates in real-time. A condensation memory in the real-time financial search engine stores financial data in a compacted space that allows computation of a smaller set of numbers. Real-time feed is converted into a two-dimensional (X, Y) location code for placement on a linear location code array of a security symbol. A single number of a location code efficiently represents (time, price) or (time, volume) in aD coordinate plane for real-time search of financial data.

Real-time financial search engine and method

Growing community of inventors

Bengaluru, India

Nagaraju Pappu