# US20250217680A1: Autonomous Orchestration System For Decision Lifecycle Management With Integrated Traceability

- Kind: Published application
- Family: Autonomous Orchestration System For Decision Lifecycle Management With Integrated Traceability (https://www.intellectualfrontiers.com/patents/autonomous-orchestration-system-for-decision-lifecycle-management-with-integrated-traceabi)
- USPTO status: Docketed New Case - Ready for Examination (as of 2025-04-03; record read 2026-09-27)
- Application: 19081752
- Filed: 2025-03-17
- Published: 2025-07-03
- Inventor: Shahid N. Shah
- Rights holder: Intellectual Frontiers LLC
- Classifications (CPC): G06N 5/043, G06N 20/00

## Licence or acquisition

Available for an exclusive or non-exclusive licence, field-of-use licences included, or for acquisition. Terms on inquiry. Write to hello+ip@intellectualfrontiers.com.

## Abstract

A computer-controlled decision lifecycle management system and method are provided for orchestrating a decision lifecycle. The system is to classify a decision type as one of a decision made by a manual intervention, autonomously by an artificial intelligence (AI) system, or collaboratively by both the AI system and the manual intervention. The system is to trigger an initiation of the decision based on a triggering event and generate a decision token representing the decision. The system collects evidence in the form of computer-executable data from a plurality of data sources and associates the evidence with a decision token to enable traceability. An AI-based analysis module of the system processes the evidence by executing one or more AI algorithms and generate a computer executable decision recommendation based on processed evidence.

## Independent claims

1. A computer-controlled decision lifecycle management system for orchestrating a decision lifecycle, the system comprising: a decision categorization module that classifies a decision type as one of a decision made by a manual intervention, a decision made autonomously by an artificial intelligence (AI) system, or a decision made collaboratively by both an AI system and the manual intervention, based on a set of predefined criteria; a decision initiation module that triggers an initiation of the decision based on a triggering event, wherein the triggering event comprises one or more of a hardware input, a user request, a predefined schedule, wherein the decision initiation module is to generate a decision token representing the decision; an evidence aggregation module communicatively coupled to a plurality of data sources distributed across discrete and remote locations, wherein the evidence aggregation module is to collect evidence in the form of computer-executable data from the plurality of data sources and associate the evidence with a decision token to enable traceability; and an AI-based analysis module that processes the evidence by executing one or more AI algorithms and generate a computer executable decision recommendation based on processed evidence.

14. A computer-implemented method for managing a decision lifecycle, the method comprising: classifying, by a decision categorization module, a decision type as one of a decision made by a manual intervention, a decision made autonomously by an artificial intelligence (AI) system, or a decision made collaboratively by both the AI system and the manual intervention, based on predefined classification criteria; triggering, by a decision initiation module, an initiation of the decision in response to a triggering event, wherein the triggering event includes one or more of a hardware input, a user request, or a predefined schedule, and generating a decision token representing the decision; collecting, by an evidence aggregation module communicatively coupled to a plurality of data sources distributed across discrete and remote locations, evidence in the form of computer-executable data from the plurality of data sources and associating the evidence with the decision token for traceability; processing, by an AI-based analysis module, the evidence by executing one or more AI algorithms to generate a computer-executable decision recommendation; and updating the decision token to reflect the status of the decision lifecycle stages.

Source: https://www.intellectualfrontiers.com/patents/autonomous-orchestration-system-for-decision-lifecycle-management-with-integrated-traceabi/us20250217680a1