Abstract: A request for an inference from a customer is received at a machine learning (ML) decentralized application (DAPP) platform, where the request includes a data record associated with a user that is associated with the customer. The data record is distributed by the ML DAPP platform among a number of service providers. An inference is received at the ML DAPP platform from each service provider. The received inferences are returned to the customer by the ML DAPP platform.

Abstract: A request for an inference from a customer is received at a machine learning (ML) decentralized application (DAPP) platform, where the request includes a data record associated with a user that is associated with the customer. The data record is distributed by the ML DAPP platform among a number of service providers. An inference is received at the ML DAPP platform from each service provider. The received inferences are returned to the customer by the ML DAPP platform.

Abstract: A service request is received at an intelligence service server from a user, where the service request includes a number of required inputs associated with the user. The number of required inputs are executed by the intelligence service server to generate an inference, an outcome probability distribution and a price quote, where the price quote corresponds to the outcome probability distribution. The outcome probability distribution and the price quote are returned by the intelligence service server to the user. It is determined by the intelligence service server that whether the user accepts the price quote based on a response from the user. If so, the inference is returned by the intelligence service server to the user. Otherwise, the response from the user is logged in a database associated with the intelligence service server by the intelligence service server.

Abstract: A service request is received at an intelligence service server from a user, where the service request includes a number of required inputs associated with the user. The number of required inputs are executed by the intelligence service server to generate an inference, an outcome probability distribution and a price quote, where the price quote corresponds to the outcome probability distribution. The outcome probability distribution and the price quote are returned by the intelligence service server to the user. It is determined by the intelligence service server that whether the user accepts the price quote based on a response from the user. If so, the inference is returned by the intelligence service server to the user. Otherwise, the response from the user is logged in a database associated with the intelligence service server by the intelligence service server.

Abstract: According to some embodiments, a local thin cloud tenant computer platform is coupled to a user synchronization data store and to a remote user cloud application executing at a data center via a distributed communication network. The local thin cloud tenant computer platform may receive synchronization information from the remote user cloud application and store it into the user synchronization data store. When the local thin cloud tenant computer platform determines that the remote user cloud application is unable to respond to a request from a local user device, the synchronization information in the user synchronization data store may be accessed to provide limited functionality associated with the remote user cloud application. The local thin cloud tenant computer platform may then transmit a response to the request from the local user device.

Abstract: A request for an inference from a customer is received at a machine learning (ML) decentralized application (DAPP) platform, where the request includes a data record associated with a user that is associated with the customer. The data record is distributed by the ML DAPP platform among a number of service providers. An inference is received at the ML DAPP platform from each service provider. The received inferences are returned to the customer by the ML DAPP platform.

Abstract: According to some embodiments, a local thin cloud tenant computer platform is coupled to a user synchronization data store and to a remote user cloud application executing at a data center via a distributed communication network. The local thin cloud tenant computer platform may receive synchronization information from the remote user cloud application and store it into the user synchronization data store. When the local thin cloud tenant computer platform determines that the remote user cloud application is unable to respond to a request from a local user device, the synchronization information in the user synchronization data store may be accessed to provide limited functionality associated with the remote user cloud application. The local thin cloud tenant computer platform may then transmit a response to the request from the local user device.

Abstract: The disclosure generally describes computer-implemented methods, software, and systems, including a method for decryption of data stored in the cloud. A record is received from a cloud storage solution, wherein at least one data field in the received record is encrypted, and wherein each encrypted data field is associated with an encrypted field identifier. A client certification key associated with a user accessing the record and at least one encrypted field identifier are provided to a security server. At least one decryption key associated with at least one of the at least one encrypted field identifier is received. Using each of received decryption key, at least one encrypted data field is decrypted. The received record is presented to the user accessing the record.

Abstract: A number of parking segments is defined as a plurality of areas for street parking. A request for parking within the plurality of parking segments is received that defines parking constraints. The request is for optimize navigation to search for a free parking spot. Parking segments that comply with the parking constraints are determined. Current values for probabilities to park for the parking segments are determined based on evaluation of collected data for parking events. The data may include both traffic data and data related to defined features that are associated with determining of probability values. A route for traversing the parking segments is determined. The route defines an optimized order for traversing according to the determined current value for the probabilities to park. Navigation instructions are provided for the determined optimized route in response to the received request.

Abstract: A number of parking segments is defined as a plurality of areas for street parking. A request for parking within the plurality of parking segments is received that defines parking constraints. The request is for optimize navigation to search for a free parking spot. Parking segments that comply with the parking constraints are determined. Current values for probabilities to park for the parking segments are determined based on evaluation of collected data for parking events. The data may include both traffic data and data related to defined features that are associated with determining of probability values. A route for traversing the parking segments is determined. The route defines an optimized order for traversing according to the determined current value for the probabilities to park. Navigation instructions are provided for the determined optimized route in response to the received request.

Abstract: Systems and methods to determine vehicle safety conditions are provided. Techniques include receiving one or more vehicle conditions from vehicle sensors and sending the data to a centralized server. The data is aggregated based on vehicle identifier and location to determine the type and location of the safety condition. The determined safety condition is sent to one or more vehicles in the vicinity of the determined safety condition to alert the drivers of the hazard. The safety condition can be displayed as an overlay on a map to aid the driver in locating it.

Abstract: The disclosure generally describes computer-implemented methods, software, and systems, including a method for decryption of data stored in the cloud. A record is received from a cloud storage solution, wherein at least one data field in the received record is encrypted, and wherein each encrypted data field is associated with an encrypted field identifier. A client certification key associated with a user accessing the record and at least one encrypted field identifier are provided to a security server. At least one decryption key associated with at least one of the at least one encrypted field identifier is received. Using each of received decryption key, at least one encrypted data field is decrypted. The received record is presented to the user accessing the record.

Abstract: A system and method for integrating a client application across multiple client devices is disclosed. A device management server receives a session request from a first client device, the session request indicating a second client device for a communication session. Upon receipt of the session request, the device management server transmits a security key to the first client device, and subsequently, receives the security key from the second client device. Upon receipt of the security key, the device management server establishes the communication session, and integrates the client application across the first and second client devices.

Abstract: A computer-implemented method for assigning a consultant to an enterprise system includes: receiving an input that indicates a need regarding an enterprise system; selecting, based on the input and using one or more processors, at least one of multiple task-object pairs as corresponding to the need, each of the task-object pairs including a task identifier and an object identifier, wherein the object identifier specifies an aspect of the enterprise system and the task identifier specifies a task performed on the aspect; selecting, in a consultant repository and using one or more processors, one or more consultant identifiers as being associated with the selected at least one task-object pair; and presenting the selected one or more consultant identifiers in response to the input.

Abstract: This disclosure provides various embodiments of systems, methods, and software for the management of relationship networks. In one implementation, the software identifies an electronic communication, parses the electronic communication into a first communication attribute and a second communication attribute, and stores the first and second communication attributes in an attribute repository. Based on this persisted information, the software calculates one or more relationship indicators based on at least one of the first and second communication attributes and, perhaps in response to a request, communicates at least a subset of the relationship indicators to an interface for presentation as a graphical relationship network.

Abstract: This disclosure provides various embodiments of systems, methods, and software for the management of relationship networks. In one implementation, the software identifies an electronic communication, parses the electronic communication into a first communication attribute and a second communication attribute, and stores the first and second communication attributes in an attribute repository. Based on this persisted information, the software calculates one or more relationship indicators based on at least one of the first and second communication attributes and, perhaps in response to a request, communicates at least a subset of the relationship indicators to an interface for presentation as a graphical relationship network.

Abstract: Disclosed is a method and system for receiving data from an enterprise application of an enterprise, converting the data into enterprise data based on an enterprise blueprint. The enterprise data is analyzed based on the enterprise blueprint to determine a state of the enterprise and an activity to be performed is determined based on the state of the enterprise.