SYSTEM FOR AUTOMATED DATA ANALYSIS AND DECISION-MAKING FOR COMPLEX PRODUCT CONFIGURATION
Summary
The USPTO published patent application US20260099734A1 filed by Vertiv Corporation on October 7, 2025. The application covers an AI-driven product configurator that pre-processes data from multiple sources, extracts features, and infers results through ML models deployed on edge devices with dynamic resource allocation. Analytical reports with visualizations and alerts are generated based on detected anomalies.
What changed
The USPTO published patent application US20260099734A1 for a system enabling automated data analysis and decision-making for complex product configuration. The invention involves AI preprocessing data from various sources, extracting features, and using ML models deployed on edge devices with dynamic resource allocation. The system generates analytical reports with visualizations, summaries, and actionable insights, and triggers alerts based on predefined thresholds and detected anomalies.
For manufacturers and technology companies, this patent application establishes prior art in AI-driven product configuration and edge computing deployment. The publication date of April 9, 2026, and filing date of October 7, 2025, are relevant for freedom-to-operate analyses and competitive intelligence in the AI and edge computing product configuration space.
Archived snapshot
Apr 17, 2026GovPing captured this document from the original source. If the source has since changed or been removed, this is the text as it existed at that time.
SYSTEM FOR AUTOMATED DATA ANALYSIS AND DECISION-MAKING FOR COMPLEX PRODUCT CONFIGURATION
Application US20260099734A1 Kind: A1 Apr 09, 2026
Assignee
VERTIV CORPORATION
Inventors
Paren Arvindbhai MAKWANA, Girish KADAM
Abstract
The present invention relates to an AI-driven product configurator that pre-processes data collected from different sources, extracts relevant features from pre-processed data, infers results through usage of ML models, and verifies inferred results. Further, ML models are deployed on an edge device where computing resources are dynamically allocated. Detailed analytical reports include visualizations, summaries, and actionable insights are generated, and alerts or notifications are triggered based on predefined thresholds, detected anomalies, or critical conditions identified in the data.
CPC Classifications
G06N 5/04
Filing Date
2025-10-07
Application No.
19351580
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