Abstract: A non-transitory computer-readable medium having program instructions for a method implemented in a Software as a Service (SaaS) management platform (SMP) is provided, including: receiving a plurality of expense records for a customer organization, wherein each one of the plurality of expense records identifies a user, a vendor, and an amount spent; using a first machine learning model to analyze the plurality of expense records and determine which ones of the expense records represent software purchases; using a second machine learning model to analyze the expense records that are determined to represent software purchases, and identify software titles that the software purchases are for; surfacing the expense records that represent software purchases, in association with their respective identified software titles, through a user interface of the SMP for the customer organization.

Abstract: Systems and methods for enhancing customer service are disclosed. The system can perform operations including detecting individuals and performing facial recognition on the individuals using visitor profiles stored by a local database. The operations can further include determining known visitors and unknown visitors among the individuals. The operations can further include generating new visitor profiles for the unknown visitors, obtaining identity information for the unknown visitors, and associating the identity information of the unknown visitors with the new visitor profiles. The operations can further include accessing identify information of the known visitors, obtaining personalized information for the known visitors from a central database, and providing the personalized information to the known visitors.

Abstract: An online concierge system allows users to order items from a warehouse, which may have multiple warehouse locations. The online concierge system provides a user interface to users for ordering the items, with the user interface providing an indication of whether an item is predicted to be available at the warehouse at different times. To predict availability of an item model at different times, the online concierge system selects data from historical information about availability of items at one or more warehouses based on temporal, geospatial, and socioeconomic information about observations of historical availability of items at warehouses. The online concierge system accounts for distances between observations and a time and geographic location in a feature space to select observations for predicting item availability at the time and the geographic location.

Abstract: A method includes acquiring historical well construction data associated with a set of historical wells. The method also includes developing a well construction model using the corpus of historical well construction data. Additionally, the method includes acquiring real-time well construction data during a well construction operation and applying the well construction model to the real-time well construction data to identify changes to a well construction parameter. Further, the method includes outputting a command to update the well construction operation using the changes to the well construction parameter.

Abstract: Systems and methods for generating an agenda for a group meeting are disclosed. Exemplary implementations may: manage environment state information maintaining a collaboration environment, the collaboration environment being configured to facilitate interaction by users with the collaboration environment; obtain user input information conveying user input to initiate individual group meetings with individual groups of users; responsive to obtaining the user input information: identify the individual groups of users corresponding to the individual group meetings, and/or identify the work unit records corresponding to the individual group meetings; generate agenda information defining individual agendas for the individual group meetings, the individual agendas including individual sets of agenda items, an individual agenda item corresponding to an individual work unit record; and/or perform other operations.

Abstract: A system and method for assisting entities or users to make decisions is disclosed. The user access the decision-making engine (MG Case composite) for end-to-end decision-making process. The system comprises a computing device (physical or on the cloud) having a processor and a memory, and a database. The engine comprises multiple modules such as case open, structure, MG Case matrix, brainstorming, problem solving, data analysis, speed math, and case end along with drive and alignment, integration and transition, and insights and impacts. The system is an integrated system and the modules are executed by the processor to perform an operation that draws on modules as needed. The decision-making engine interacts with internal and external facets of an organization, including users, various communication systems, ERPs, databases, etc. to execute various tasks related to decision making such as gathering data and driving the decision-making process through the organization or with the user.

Abstract: A non-transitory computer-readable medium having program instructions for a method implemented in a Software as a Service (SaaS) management platform (SMP) is provided, including: receiving a plurality of expense records for a customer organization, wherein each one of the plurality of expense records identifies a user, a vendor, and an amount spent; using a first machine learning model to analyze the plurality of expense records and determine which ones of the expense records represent software purchases; using a second machine learning model to analyze the expense records that are determined to represent software purchases, and identify software titles that the software purchases are for; surfacing the expense records that represent software purchases, in association with their respective identified software titles, through a user interface of the SMP for the customer organization.

Abstract: A system and method is proposed for estimating the contribution of components of a distributed computing environment to the generation of economically relevant values, like e.g., revenue numbers. Agents are deployed to the computing environment that trace executed transactions and that monitor components used to execute those transactions. The transaction trace data also contains data about the origin/user of transactions, which may be used to group transactions corresponding to particular interactions of individual users with the monitored application into visit data. Data describing economically relevant activities of transactions, like the purchase of goods, are also observed by agents and reported in trace data. Functional dependencies described in transaction trace data and resource related dependencies derived from component monitoring data are used to identify functionality and components that contributed to the generation of business value.

Abstract: Methods and systems for simulating fulfillment of digital orders within a retail supply chain are disclosed. One method includes receiving a selection of a first operational parameter of a supply chain model. The supply chain simulation model is a transaction-level model representative of a digital order fulfillment process within a retail supply chain network. The selection of the first operational parameter includes a default value for the first operational parameter and an experimental value for the first operational parameter that is different from the default value. Simulations of a set of predicted digital orders within the retail supply chain network, using the supply chain simulation model as modified in accordance with the first operational parameter, are performed. Scenario evaluations including predicted metrics associated with each of a cost, a capacity, and a guest experience for the digital order fulfillment process may be output and displayed on a user interface.

Abstract: Methods and apparatuses for intelligently determining and implementing distinct routines for entities are provided. An apparatus includes at least a processor and a memory communicatively coupled to the at least a processor, the memory containing instructions configuring the at least a processor to receive entity data associated with an entity, generate at least one distinct routine for the entity as a function of the entity data, generate a functional model as a function of the at least one distinct routine, and generate a user interface data structure configured to display and including the at least one distinct routine and the functional model. A graphical user interface (GUI) is communicatively connected to the processor and is configured to receive the user interface data structure and display the at least one distinct routine on a first portion of the GUI.

Abstract: Systems and methods for assessing, tracking and improving security maturity of an organization are provided. Described is a system for assessing security maturity of an organization. The system receives a list of data sources located across multiple jurisdictions for the organization, collects data sources/data using custom rules from a plurality of data sources of the list of data sources, determine criticality score for each of the plurality of data sources, calculates data source coverage and asset collection coverage, determines use case coverage, and determines security maturity score using a maturity score model. The maturity score model is a logistic equation which is a function of the data source coverage, the asset collection coverage, the criticality score associated with each of the plurality of data sources, the use case coverage, asset coverage by each the plurality of data sources.

Abstract: Methods and systems for improved collection and evaluation of audit responses for healthcare sites are provided. In one embodiment, a method is provided that includes receiving responses associated with an audit of a healthcare site. A deficiency score and a total score may be calculated based on the responses. The deficiency scores may be calculated based on a quantity of responses indicating a deficient status and/or an improvement required status. The total score may be calculated based on a total quantity of the responses and a quantity of the responses that indicate an inapplicable status. The risk score may then be calculated based on the deficiency score.

Abstract: A system for managing performance of a service establishment, the service establishment having multiple servers and multiple customers. Each server has a server queue with zero or more customers. Servers take orders from customers when they reach the head of the server's queue. The system includes: an order input interface for obtaining orders from the servers as the servers take orders from the customers; one or more digital video cameras positioned and configured to capture video of the server queues; a public view monitor viewable by the customers; a management monitor viewable by one or more managers of the service establishment; and a customer tracking processor. The customer tracking processor is configured to: receive video of server queues; identify customers in the video data; track customer progress in the server queues; and calculate and display expected wait times of the server queues on the public view monitor.

Abstract: A system and method of combining table management software and customer experience skills by generating profiles of patrons, servers, and restaurants and using machine learning algorithms on those profiles to build more intimate relationships between patrons, food service establishments, and food service professionals. Trait matching provides optimized matchmaking between patrons and servers who share certain commonalities while also balancing the table management operations. Machine learning algorithms may be used to identify patterns of commonality that would not otherwise be recognized. This system allows patrons to choose servers at an establishment over a plurality of electronic devices by using the cluster analysis results. It provides servers more lateral work experience between participating restaurants, and restaurants more power to operate smoothly and build highly cohesive teams.

Abstract: A system and method for real-time operational predictive scoring of components and services of an information technology system (ITS) for forecasting and assessing performance of the components of the ITS are provided. A data pipeline is configured to collect and store, in real-time, multiple time series signals corresponding to health, performance, and functionality of each of the components of the ITS. An operational predictive score (OPS) engine of a scoring module calculates an OPS for each of the time series signals. An OPS roll-up module of the scoring module calculates an OPS for each of the components and services in the ITS by aggregating the OPS for the individual time series signals. An alerting engine to notify operational issues and provide root cause analysis using OPS score decomposition. A visualization layer for OPS based analytics.

Abstract: Provided are an index value calculator to calculate an index value obtained by quantifying a degree of status for evaluation items, a teamwork evaluator to evaluate a teamwork based on the index value, a support content determiner to select target persons to be supported including the members of the team based on the evaluation result of the teamwork and determine support contents in accordance with the target persons to be supported, and a presentation information generator to generate presentation information for presenting the determined support contents for each of the output devices corresponding to the selected target persons to be supported, and the teamwork evaluator evaluates the teamwork using an evaluation logic configured by combining logical formulas for comparing a threshold value set for evaluation items with the calculated index value.

Abstract: An embodiment of the present invention is directed to a market data hub. The innovative system comprises a processing engine that manages contributed content and allows for custom analytics, alerting, reporting, machine learning interfaces, etc., while preserving entitlements controls specific to participants. Moreover, the system disseminates market data to downstream consumers and syndicated entities that are entitled to view the market data.

Abstract: A messaging system may receive a plurality of messages in a conversation maintained by a messaging service. It may be determined that a first message sent from a first messaging application associated with a first user comprises information identifying a second user. The messaging system may receive information indicative of a date associated with the first message. At least one database may store an association among at least the first message, the second user, and the date. The messaging system may send information indicative of the date still being active in the at least one database to a second messaging application associated with the second user.

Abstract: Systems and methods of improving AI governance are disclosed. One or more sub-contexts associated with a plurality of users are generated from one or more data sources. The one or more sub-contexts represent one or more changes in data that are relevant to assessing one or more risks associated with the plurality of users. One or more sub-contexts are provided as training data to a plurality of models. Each of the models is associated with a confidence score. A probabilistic assessment of the one or more risks associated with the plurality of users is generated based on an application of the plurality of models to additional data pertaining to the plurality of users received in real time. The probabilistic assessment is presented in a dashboard user interface, the dashboard user interface having user interface elements configured to provide insight into how the probabilistic assessment was generated.

Abstract: Computer implemented sales prediction system collects data relating to events of visitors showing an interest in a client company from plural data sources, an organization module which organizes collected data into different event types and separates collected event counts in each event type between non-recent and recent events occurring within a predetermined time period, a first processing module which periodically calculates weighting for each event type based on recent and non-recent events for the event type compared to totals for other selected event types, a second processing module which periodically calculates sales prediction scores for each visitor and companies with which visitors are associated based on accumulated event data and weighting, and a reporting and data extract module which is configured to detect variation in sales prediction scores over time to identify spikes which can predict upcoming sales and to provide predicted sales information and leads to the client company.