Boomi, Inc.

Prakhar Amlathe

Swagata Ashwani

Chris Cappetta

Michael Bachman

Eric Fennell

Ravikiran Krishnan

Currently, technical expertise is required to construct data objects within integration processes. Disclosed embodiments enable automated generation of data objects using semantic comparisons and artificial intelligence. In particular, data may be converted into reference vector embeddings that define a semantic location of the data within a multi-dimensional vector space. User requests may be converted into input vector embeddings. The input vector embeddings may be semantically compared to the reference vector embeddings to identify semantically similar data, and related data may be identified using a graph database. This semantically similar and related data may then be used to generate a prompt, which may be input to a generative language model to automatically produce a data object for use in an integration process.

Automated generation of data objects using semantic comparisons and artificial intelligence

An information handling system operating a personal identifiable information (PII) recommendation system may comprise a GUI modelling with visual integration elements, an integration process flow for migrating field values comprising PII data, wherein the integration process applies a security measure to migration of PII data, a processor executing code instructions to generate a migrating field value term frequency vector describing a weighted frequency with which a metadata term for the migrating field value appears within a metadata for a migrating dataset comprising the migrating field value, input the term frequency vector into a trained neural network to determine the migrating field value includes PII data, label the migrating field value as PII data, such that the modeled integration process applies the security measure to the migrating field value, and a network interface device transmitting a set of connector code instructions for performing the modeled integration process for remote execution.

System and method for recommending secure transfer measures for personal identifiable information in integration process data transfers

Currently, technical expertise is required to construct data maps between data sources and targets within integration processes. Disclosed embodiments enable automated generation of data maps using semantic comparisons and artificial intelligence. In particular, data may be converted into reference vector embeddings that define a semantic location of the data within a multi-dimensional vector space. User requests may be converted into input vector embeddings, based on source and target information. The input vector embeddings may be semantically compared to the reference vector embeddings, potentially using a graph database, to identify semantically similar data. This semantically similar data may then be used to generate a prompt, which may be input to a generative language model to automatically produce a data map for use in an integration process.

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Santa Clara, CA, United States of America

Prakhar Amlathe