A method of dynamically ordering tasks in a production system comprises providing a control unit configured to: receive a plurality of job orders; determine tasks associated with each of the plurality of job orders; dynamically adjust the priority of each job order in a pending job orders list; and send one of the job orders and associated tasks to a queue when a threshold associated with the system is met.

A system, method, apparatus, and computer program product that provides a strategically integrated interdisciplinary staffing and budgetary management system for staffing of corrections facilities. The Constitutional Public Safety Staff Management System (CPSSMS) incorporates effective methodologies for regulating the staffing management of public and private sector organizations as it pertains to the administrative governance of domestic public safety organizations within the American criminal justice system. The CPSSMS include a Schedule Mapping Tool; a Tour, Group, Squad Balance Calibration Tool; an Enhanced Overtime Code Mapping Tool; an Overtime Tracking System; a Governed System Compliance Engine; and a Sequential Staff Sort System. The CPSSMS provides for operational staffing of the corrections facility and can be utilized for documenting requirement shortfalls for obtaining legislative and other budgetary requirements to maintain humane conditions and constitutional standards of confinement that promote the general welfare of individuals held within an institutional jail or prison setting.

Embodiments of the present disclosure provide a computer-implemented method. The computer-implemented method performed by a controller includes generating a plurality of virtual agents with Artificial Intelligence (AI) capabilities based at least on organizational data. Furthermore, the computer-implemented method includes delegating at least a portion of operational workflows to one or more of the plurality of virtual agents. The computer-implemented method further includes generating a plurality of employee digital twins associated with a plurality of respective employees, based at least on employee-specific data. Furthermore, the computer-implemented method includes generating at least one workplace digital twin representing at least one respective workplace environment. The computer-implemented method also includes enabling communication amongst a plurality of disparate groupings generated by selecting a plurality of entities from one or more of a plurality of employee devices, the plurality of virtual agents, the plurality of employee digital twins, or the at least one workplace digital twin.

The invention provides an artificial intelligence system for autonomously generating and optimizing complex task workflows using self-improving specialist archetypes. Modular processor circuitry and distributed compute-enabled devices execute agent flows defined within an application layer comprising Archetypes, Archetype Optimization Pipelines, and Project Optimization Pipelines. Archetypes supply foundational configurations, while project-level pipelines refine them into Specialistsagents such as Business Analyst, Product, Solutions, Architect, Team Lead, Implementer, Chief Architect, and Blocker Resolution roles. Each Specialist executes Meta Reasoning Flows to perform tasks including stakeholder identification, requirement gathering, feature decomposition, task generation, cost estimation, artifact creation, testing, review, and blocker resolution. Declarative self-improvement frameworks provide hierarchical optimization through atomic, composite, and meta-reasoning flows, enabling continuous refinement of workflows. Integrated test systems ensure correctness through behavior-driven and test-driven methodologies. The system enables scalable, autonomous artifact production with minimal human intervention across dynamic, data-driven environments.

A method, computer system, and computer program product are provided for identifying missing reserves in a reservoir. Well site data for well sites in a reservoir are ingested. A first machine learning model generates behind casing opportunities and reservoir quality indicators from the plurality of logs. A second machine learning model determines missing reserves based on the reservoir quality indicators for the well sites and in between the wells. A third machine learning model determines candidate wells based on the missing reserves. A fourth machine learning model predicts economic outcomes for intervention options for the candidate wells. An oilfield decision is supported based on the predicted economic outcomes.

The disclosed invention presents an AI-driven, dynamic, task-based information retrieval and processing system tailored for the financial sector. Utilizing advanced machine learning, natural language processing, and data analytics, this system automates the decomposition of complex tasks into manageable sub-tasks, executes these through a sophisticated data processing pipeline, and generates customized reports. The system enhances efficiency by integrating knowledge graphs for query augmentation, employing noise filtering algorithms, and adaptively re-ranking documents to align with user-specific contexts and objectives. This approach addresses the challenges of manual data synthesis and the inflexibility of existing semi-automated systems, significantly reducing the time and labor involved in generating precise and relevant financial reports. By streamlining the retrieval and processing of vast and varied financial data, the system supports informed decision-making and reduces operational costs, making it a valuable tool for financial analysts and investment professionals.

A clinical workflow optimization system includes a data processing and analysis platform electrically connected or communicatively coupled to a user device and an HIS server, and a generative AI model set communicatively coupled to the data processing and analysis platform. The data processing and analysis platform provides one or more assistant tools. When the user device selects an assistant tool to execute a task instruction, the data processing and analysis platform uses one model of the generative AI model set to interpret and execute the task instruction. The analysis platform presents the execution result of the task instruction to the user device, wherein data required to execute the task instructions is recorded in the content of the task instructions or provided by the HIS server, the user device, or an external database. On the platform, users can independently develop and build clinical data processing tools using natural language.

Techniques for guiding a user in performing a process based on historical digital interaction data of one or more users performing the process, the historical digital interaction data comprising multiple streams of event data, the method comprising: obtaining a stream of event data corresponding to a series of interactions between at least one application program executing on the user's computing device and the user performing the process using the at least one application program; identifying, within the historical digital interaction data and using the stream of event data, at least one instance of the process previously performed by at least one user; generating guidance for the user performing the process using the at least one instance of the process, the guidance indicating one or more suggested acts for the user in furtherance of performing the process; and providing the generated guidance to the user.