Palantir Technologies. has been granted a patent for a method that involves launching virtual machines to instantiate machine learning model execution environments. Each model instance is linked to an API endpoint, enabling client devices to send input data and receive corresponding output data. GlobalData’s report on Palantir Technologies gives a 360-degree view of the company including its patenting strategy. Buy the report here.

According to GlobalData’s company profile on Palantir Technologies, Social media analytics was a key innovation area identified from patents. Palantir Technologies's grant share as of June 2024 was 66%. Grant share is based on the ratio of number of grants to total number of patents.

Machine learning model execution with api integration

Source: United States Patent and Trademark Office (USPTO). Credit: Palantir Technologies Inc

The patent US12045678B2 outlines a method and system for integrating machine learning models with application programming interfaces (APIs) to facilitate data processing and output generation. The method involves associating a loaded instance of a machine learning model with an API endpoint that receives input data from a client device and returns the corresponding output data. The API is designed to handle requests for configuration, allowing the identification of specific configuration information, including the model identifier and resource locator. The system also supports the processing of input data, which may include client identifiers linked to account information, and records audit information related to the requests and responses for validation and monitoring purposes.

Additionally, the patent describes mechanisms for ensuring quality of service by monitoring performance metrics and adjusting resources accordingly. The API endpoint is configured to handle HTTP requests and responses, enabling seamless communication between the client device and the machine learning model. The method also includes provisions for preloading datasets associated with the machine learning model, allowing for enhanced data aggregation and processing capabilities. Overall, the claims emphasize a structured approach to deploying machine learning models in a client-server architecture, focusing on configuration, data handling, and performance monitoring.

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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.