Abstract: An agent-based website search interface utilizes a multimodal model to enhance enterprise operations. Data agents collect and process diverse inputs, while an orchestrator manages these agents. The system leverages machine learning models to generate insights and automate decision-making processes. It includes tools for data visualization and validation, ensuring accuracy and reliability. By integrating generative AI, the interface provides advanced search functionalities, improving user experience and operational efficiency. This facilitates seamless interaction to answer context specific questions from complex data, offering a robust solution for enterprise-level search and analysis.

Abstract: An agent-based website search interface utilizes a multimodal model to enhance enterprise operations. Data agents collect and process diverse inputs, while an orchestrator manages these agents. The system leverages machine learning models to generate insights and automate decision-making processes. It includes tools for data visualization and validation, ensuring accuracy and reliability. By integrating generative AI, the interface provides advanced search functionalities, improving user experience and operational efficiency. This facilitates seamless interaction to answer context specific questions from complex data, offering a robust solution for enterprise-level search and analysis.

Abstract: Systems and methods are configured to generate a set of potential responses to a prompt using one or more data models with data from at least a plurality of data domains of an enterprise information environment that includes access controls. A deterministic response is selected from the set of potential responses based on scoring of the validation data and restricting based on access controls in view of profile information associated with the prompt. These enterprise generative AI systems and methods support granular enterprise access controls, privacy, and security requirements, and provide traceable references and links to source information underlying the generative AI insights. These systems and methods enable dramatically increased utility for enterprise users to access information, analyses, and predictive analytics associated with and derived from a combination of enterprise and external information systems.

Abstract: An agent-based website search interface utilizes a multimodal model to enhance enterprise operations. Data agents collect and process diverse inputs, while an orchestrator manages these agents. The system leverages machine learning models to generate insights and automate decision-making processes. It includes tools for data visualization and validation, ensuring accuracy and reliability. By integrating generative AI, the interface provides advanced search functionalities, improving user experience and operational efficiency. This facilitates seamless interaction to answer context specific questions from complex data, offering a robust solution for enterprise-level search and analysis.

Abstract: Systems and methods managing, by an orchestrator, a plurality of agents to generate a response to an input. The orchestrator employs one or more multimodal models such as a large language models to process or deconstruct the prompt into a series of instructions for different agents. Each agent employs one or more machine-learning models to process disparate inputs or different portions of an input associated with the prompt. The system generates, by the orchestrator, a natural language summary of the structured and unstructured data records. The system formulates output and transmits the natural language summary of the data records.

Abstract: An anti-hallucination and attribution architecture for enterprise generative AI systems is disclosed herein which increases the accuracy and reliability of generative artificial intelligence content (e.g., responses or answers) by detecting, preventing, and mitigating hallucination. The anti-hallucination and attribution architecture can be added to deployed generative artificial intelligence systems as a separate tool or module, which allows it to work with the deployed systems without having to retool or redesign those systems. The anti-hallucination and attribution architecture can also be deployed with minimal impact on live production systems.

Abstract: Systems and methods managing, by an orchestrator, a plurality of agents to generate a response to an input. The orchestrator employs one or more multimodal models such as a large language models to process or deconstruct the prompt into a series of instructions for different agents. Each agent employs one or more machine-learning models to process disparate inputs or different portions of an input associated with the prompt. The system generates, by the orchestrator, a natural language summary of the structured and unstructured data records. The system formulates output and transmits the natural language summary of the data records.

Abstract: Systems and methods for a model inference service system that provides a technical solution for deploying and updating trained machine-learning models with support for specific use case deployments and implementations at scale with efficient processing. The model inference service system includes a hierarchical model registry for versioning models and model dependencies for each versioned model, a model inference service for rapidly deploying model instances in run-time environments, and a model processing system for managing multiple instances of deployed models. Changes to deployed models are captured as new versions in the hierarchical model registry.

Abstract: Systems and methods managing, by an orchestrator, a plurality of agents to generate a response to an input. The orchestrator employs one or more multimodal models such as a large language models to process or deconstruct the prompt into a series of instructions for different agents. Each agent employs one or more machine-learning models to process disparate inputs or different portions of an input associated with the prompt. The system generates, by the orchestrator, a natural language summary of the structured and unstructured data records. The system formulates output and transmits the natural language summary of the data records.

Abstract: A plurality of different data domains of an enterprise information environment are scanned. A plurality of data records of multiple enterprise data sources of the different data domains are chunked. The chunking generates one or respective data record segments for each of the plurality of data records. Respective contextual metadata is generated for each of the one or more respective data record segments. Each respective contextual metadata indicates semantic or contextual descriptions of the respective data records segment, and at least one of the respective contextual metadata is capable of facilitating a determination of a relationship between one of the respective data record segments of a particular respective data record and another one the respective data segments of another respective data record. A respective segment embedding is generated for each data record segment based on the respective contextual metadata, and the segment embeddings are stored in an embeddings datastore.

Abstract: Systems and methods managing a plurality of agents to generate a response to a query using a multimodal model. An example method uses the plurality of agents to iteratively determine subsequent outputs of the multimodal model satisfies the query. It can generate a respective context associated with a respective output of the multimodal model. And determine, by the multimodal model based on the respective context, whether the respective subsequent output satisfies the query.

Abstract: Systems and methods are configured to generate a set of potential responses to a prompt using one or more data models with data from at least a plurality of data domains of an enterprise information environment that includes access controls. A deterministic response is selected from the set of potential responses based on scoring of the validation data and restricting based on access controls in view profile information associated with the prompt. These enterprise generative AI systems and methods support granular enterprise access controls, privacy, and security requirements. enterprise generative AI providing traceable references and links to source information underlying the generative AI insights. These systems and methods enable dramatically increased utility for enterprise users to information, analyses, and predictive analytics associated with and derived from a combination of enterprise and external information systems.

Abstract: A tire uniformity machine includes an apparatus for receiving and rotating a tire. The apparatus includes opposed spindles for receiving, inflating and rotating a tire, and a load wheel applied to the rotating tire to obtain tire test results. A spindle alignment assembly is associated with the opposed spindles to align the spindles with one another each time a tire is received. At least one characterizing device is associated with components of the apparatus to characterize forces of the opposed spindles and the characterized forces are used in adjusting tire test results.

Abstract: A tire uniformity machine includes an apparatus for receiving and rotating a tire. The apparatus includes opposed spindles for receiving, inflating and rotating a tire, and a load wheel applied to the rotating tire to obtain tire test results. A spindle alignment assembly is associated with the opposed spindles to align the spindles with one another each time a tire is received. At least one characterizing device is associated with components of the apparatus to characterize forces of the opposed spindles and the characterized forces are used in adjusting tire test results.

Abstract: A system and method is provided for characterizing color separation misregistration associated with marking a substrate. The method includes providing an input image having a plurality of patches, each patch having a pattern using a first and second color; marking a substrate with a copy of the input image using a first and second color separation to correspond to the first and second colors, respectively; and measuring a color characteristic of markings of respective copied patches of the copied plurality of patches and generating corresponding colorimetric values. Misregistration of the first color separation markings relative to the second color separation markings is characterized based on the measured calorimetric values.

Abstract: A system and method is provided for characterizing color separation misregistration associated with marking a substrate. The method includes providing an input image having a plurality of patches, each patch having a pattern using a first and second color; marking a substrate with a copy of the input image using a first and second color separation to correspond to the first and second colors, respectively; and measuring a color characteristic of markings of respective copied patches of the copied plurality of patches and generating corresponding colorimetric values. Misregistration of the first color separation markings relative to the second color separation markings is characterized based on the measured calorimetric values.

Abstract: A computer-implemented method of email processing within a multitenant unified communications environment includes receiving, at a first email system component that is a sub-component of a unified communications system, an email that is addressed to a recipient by way of a delivery address that includes a first domain identifier. Based at least in part on the delivery address, a second delivery address associated with the user is identified. The second delivery address does not include the first domain identifier but does include a second domain identifier that is different than the first domain identifier. The email is automatically sent to the second delivery address.

Abstract: A preferred embodiment reproduces an image by receiving an input contone array of M contone data values. The contone data values may lie within a range from 1 to N. The embodiment includes comparing each contone data value to an array of M sets of pattern look-up tables to generate an array of M pattern values. M may be a number of one or more. Each pattern value in the array of M pattern values may be decoded to a corresponding K by L multi-pixel pattern of binary data. The binary data is rendered by a reprographic device.

Abstract: A method is provided for characterizing color separation misregistration of a printer device, the method including receiving from the printer device an output image having marked calibration patches having a variety of color separation configurations, each using a first and second color separation, and a marked measurement patch having a predetermined color separation configuration. Measured colorimetric values are received corresponding to the calibration patches and the marked measurement patch, and a characteristic of a curve associated with the measured colorimetric values corresponding to the calibration patches is determined. A calibration function is generated based on the determined characteristic of the curve, providing expected colorimetric values for the predetermined color separation configuration as related to a misregistration characteristic value.

Abstract: A method and system for estimating color separation misregistration of a printing system. The method may include marking a substrate to form a misregistration estimation patch. The misregistration estimation patch being formed by first and second color separations. The first color separation marking the substrate with a first halftone pattern. The first halftone pattern has a first halftone-frequency vector in a first direction and a second halftone-frequency vector in a second direction. The second color separation marking the substrate with a second halftone pattern. The second halftone pattern has a first halftone-frequency vector in a first direction and a second halftone-frequency vector in a second direction. The first and second halftone patterns form a moiré pattern. A deviation in at least one the halftone frequency vectors and/or the moiré pattern can be indicative of a color separation misregistration.