C3.ai, Inc. patent applications on 2025-06-19
Patent Applications by C3.ai, Inc. on June 19th, 2025
C3.ai, Inc.: 3 patent applications
C3.ai, Inc. has applied for patents in the areas of G06F16/213 ({with details for schema evolution support}, 1), G06F16/24568 ({Data stream processing; Continuous queries}, 1), G06F16/2477 ({Temporal data queries}, 1)
With keywords such as: schema, management, method, aspects, disclosed, herein, system, computer, program, product in patent application abstracts.
Top Inventors:
- Edward Y. ABBO of Woodside CA US (1 patents)
- Nikhil KRISHNAN of Los Altos CA US (1 patents)
- Romain JUBAN of San Francisco CA US (1 patents)
- Louis POIRIER of Paris FR (1 patents)
- Franklin Q. YE of San Francisco CA US (1 patents)
Patent Applications by C3.ai, Inc.
Abstract: disclosed herein are system, method, and computer program product aspects for a schema management platform. an aspect operates by leveraging artificial intelligence for generating and executing schemas. an aspect operates by also providing functionality for generating code for a schema. the schema management platform may be used to assist real-world workflows and procedures performed in particular contexts. in some aspects, the schema management platform can utilize a schema to instruct a multimodal model on how to respond with verifiable subject matter expertise to various types of inputs and use cases. as such, the schema management platform may provide more accurate and reliable results compared to conventional systems.
20250200050. MODEL-ENABLED DATA PIPELINE GENERATION (C3.ai, .)
Abstract: disclosed herein are system, method, and computer program product aspects for generating a data pipeline. a model prompt including a received natural language description and a prompt template is generated. the prompt template includes action labels and a processing example. each action label indicates a respective data processing action, and the processing example includes a sample query and a sample answer comprising one or more sample action labels associated with a sample natural language description of a sample data pipeline. a multimodal model (mm) is queried with the model prompt. the mm response includes one or more action labels corresponding to the natural language description of the requested data pipeline in a format guided by the prompt template. a data pipeline project template can then be generated using one or more executable nodes corresponding to the action labels.
20250200057. FOUNDATION MACHINE LEARNING MODELS SENSORY OR OTHER TIME-SERIES DATA (C3.ai, .)
Abstract: a method includes obtaining time-series data of at least one type and at least one textual description of the at least one type of time-series data and processing the time-series data and the at least one textual description using a foundation machine learning model. processing the time-series data and the at least one textual description using the foundation machine learning model includes generating at least one embedding of the at least one textual description, combining the time-series data and the at least one embedding of the at least one textual description to generate combined data, and generating embedding vectors using the combined data.