UNGRIA Patentes y Marcas, S.A.

Artificial intelligence (Al)-based techniques for determining best action recommendations for issues that arise during the operation of conductor applications and/or robotic process automation (RPA) robots, and for implementing such recommendations, are disclosed. A generative Al model or other type of AI model (e.g., a classifier) is trained to detect issues that occur during operation of such conductor applications and/or RPA robots and to provide recommendations to users with respect to the best action to address the problem. The AI model may list the recommendations that exceed a recommendation threshold, along with their respective confidence scores. In some cases, the Al model may analyze characteristics of executing jobs and provide recommendations for improving the automations, or implement the improvements automatically.

The present invention relates to a food baking pan (1) comprising: at least one hollow element (3) which shape is equivalent to a shape of a food to be baked; a frame (5) configured to hold several hollow elements (3) and to be displaced by a conveyor device (6); a lid (2) covering the at least one hollow element (3). The lid (2) is made of ferromagnetic materials and the frame (5) comprises attracting magnets (4) configured to keep the lid (2) against the hollow elements (3) at temperatures above 100° Celsius. The invention further relates to a removal system for removing the lid with removing magnets (7), which are made of samarium-cobalt.

The present invention comprises several positioning devices (3) for stabilising the roof (2) of the body (1), and means for moving the roof vertically and thus placing it at the required height with final resting on the positioning devices. Each positioning device comprises a movable vertical structure (8) with height-adjustable displacement, formed by an elongated profile (8a) and a tilting skid (8b), which is coupled to the elongated profile (8a) below it by means of a horizontal articulated connection (9). The tilting skid (8b) includes a horizontal transverse shaft (10) which is configured to fit into one of several recesses (15a) delimited between teeth of a toothed rack (15) according to the required height of the roof (2). The positioning devices are arranged at least in the four vertical corner areas of the truck body (1), so that the roof (2) rests on ends of the various movable vertical structures (8).

A system for making ditches on roadways which comprises a moulding implement (1) configured to be coupled to a vehicle, such as a tractor or a grader, where said moulding implement (1) is configured to shape a mass by adapting it to the ground surface, such as a surface of a ditch of a road, by means of a movement of said moulding implement (1) with respect to said surface. The moulding implement (1) comprises a frame structure comprising a hopper (11), the shaping surface (13) configured to adapt the mass received by the hopper (11) to the ground surface, by means of the movement of the moulding implement (1), and a skid (12) comprising reference means for the placement of the shaping surface (13), as well as of the opening of the hopper (11) with respect to the ground surface to be shaped.

A method and system for testing triboelectric materials comprising: a first platform (2); a counter-electrode (5) arranged on the first platform to receive a piece of a first triboelectric material; a force measurement means to measure force at the first platform; a piston (11); a second platform (12) at one end of the piston; an electrode (13) arranged at the second platform to receive a piece of a second triboelectric material; a drive system (15) to vertically move the piston to a position with contact between the two triboelectric materials at a certain level of force and frequency; and measuring means to measure an output signal as result of the contact between the triboelectric materials.

A method is provided. The method is executed by an robotic process automation using a document processing engine. The method includes generate an extracted data prediction of a document by the robotic process automation using multiple distinct document processing operations of the document processing engine. The method includes automatically validating the extracted data prediction by the robotic process automation cross-checking the extracted data prediction with a validator panel of the document processing engine. The method includes determining a confidence for the multiple distinct document processing operations based on the validating of the extracted data prediction.

Orchestration solutions for agentic automation for artificial intelligence (AI) agents, robotic process automation (RPA) robots, agentic orchestration processes (AOPs), and humans-in-the-loop with self-healing and capabilities to increase autonomy. Agentic orchestration, via a conductor application, enables the automation, modeling, and monitoring of complex business processes from start to finish. A user or an initiating software process requests that a given AOP be run. The AOP defines a business process (e.g., in Business Process Model and Notation (BPMN)), and may utilize one or more RPA robots, one or more Al agents, and/or one or more humans to assist with accomplishing this process, such as resolving invoice discrepancies, onboarding an employee, performing compliance checks, synchronizing order data among multiple backend systems, etc.

Unified solutions for agentic automation and robotic process automation (RPA) with self-healing and capabilities to increase autonomy are disclosed. Al agents "coexist" in tandem with RPA robots that execute RPA automations. The Al agents can dynamically leverage the tools available via these RPA robots to perform document processing, user interface (UI) automation, semantic copy-and-paste between a source and a target, etc. Al agents can dynamically select these tools and execute them in the form of a pipeline.

Unified artificial intelligence (AI) agent, robotic process automation (RPA) robot, and agentic orchestration process (AOP) development applications are disclosed. In such embodiments, Al agents "coexist" in tandem with RPA robots that execute RPA automations. Automation developers can provide a natural language description of a process intended to be implemented by an Al agent, as well as prompts for a user. Developers can also select grounding context, service integration tools, RPA robots, and escalation attributes for the Al agent. When executed, the Al agent will implement a dynamic flow and attempt to perform its logic autonomously. If this is not successful, the Al agent can escalate to a human-in-the-loop, and the human resolution may be saved in memory for self-healing purposes. Developers can also develop AOPs that can utilize Al agents and RPA robots via a conductor application as well.

A method is provided. The method is executed by a document processing and natural language engine implemented as a computer program within a computing environment. The method includes generating parsed non-standardized data from a document or a natural language text and converting the parsed non-standardized data using a generative pretrained transformer into a hypertext markup language output. The method includes extracting pages, controls, or entity fields from the hypertext markup language output using a hypertext markup language application interpreter. The method includes integrating application specific constructs based on the pages, the controls, or the entity fields into an application template to provide an operational form application. The method includes inserting into the operational form application a submit form button configured to push form data to a corresponding entity.