Abstract: Systems and methods are described for a messaging agent for managed multidimensional search based on an electronic message and management policies. A messaging application at a client device can send a new electronic message, such as an email, to a connector service. An attachment can be ingested and stored in a vector database. Then one or more artificial intelligence (“AI”) agents can be selected for responding to the body of the email, such as a query in the body. The responses can be formatted and sent to multiple users, such as a sending user of the electronic message and a recipient user that was copied or also sent the new electronic message. The AI agents can use different AI models, prompts, and vector databases depending on user permissions. This allows for building up vector databases with relevant content items and answering user questions based on those vector databases.

Abstract: Systems and methods are described for a connected AI agent for managed multidimensional search based on an electronic message and management policies. A messaging application at a client device can send a new electronic message, such as an email, to a connector service. An attachment can be ingested and stored in a vector database. Then one or more artificial intelligence (“AI”) agents can be selected for responding to the body of the email, such as a query in the body. The responses can be formatted and sent to multiple parties, such as a sending user of the electronic message and a recipient that was copied or also sent the new electronic message. The AI agents can use different AI models, prompts, and vector databases depending on user permissions. This allows for building up vector databases with relevant content items and answering user questions based on those vector databases.

Abstract: Systems and methods are described for executing customer artificial intelligence pipelines by dynamically selecting service providers based on resource consumption. A server can poll a group of service providers and receive resource information that indicates compute, network, storage, and token requirements to perform an action. When the customer AI pipeline executes, a pipeline engine can select a service provider to execute the action based on stored resource information. The service providers available in the group can also dynamically change based on terms of service.

Abstract: Systems and methods are described for executing tenant artificial intelligence pipelines by dynamically selecting service providers based on resource consumption. A server can poll a group of service providers and receive resource information that indicates compute, network, storage, and token requirements to perform an action. When the tenant AI pipeline executes, a pipeline engine can select a service provider to execute the action based on stored resource information. The service providers available in the group can also dynamically change based on terms of service.

Abstract: Systems and methods are described for a messaging agent for managed multidimensional search based on an electronic message and management policies. A messaging application at a client device can send a new electronic message, such as an email, to a connector service. An attachment can be ingested and stored in a vector database. Then one or more artificial intelligence (“AI”) agents can be selected for responding to the body of the email, such as a query in the body. The responses can be formatted and sent to multiple users, such as a sending user of the electronic message and a recipient user that was copied or also sent the new electronic message. The AI agents can use different AI models, prompts, and vector databases depending on user permissions. This allows for building up vector databases with relevant content items and answering user questions based on those vector databases.

Abstract: Systems and methods are described for a connected AI agent for managed multidimensional search based on an electronic message and management policies. A messaging application at a client device can send a new electronic message, such as an email, to a connector service. An attachment can be ingested and stored in a vector database. Then one or more artificial intelligence (“AI”) agents can be selected for responding to the body of the email, such as a query in the body. The responses can be formatted and sent to multiple parties, such as a sending user of the electronic message and a recipient that was copied or also sent the new electronic message. The AI agents can use different AI models, prompts, and vector databases depending on user permissions. This allows for building up vector databases with relevant content items and answering user questions based on those vector databases.

Abstract: Systems and methods are described for a maintaining consistent and reliable outputs from artificial intelligence (“AI”) based search systems that use pipelines with a dataset, AI model, and prompt. An application can send a query through a pipeline and set the result as a baseline for future results. The application can periodically resend the query through the pipeline and compare the new results to the baseline. If the new results vary from the baseline above a predetermined threshold, then corrective measures can be taken. This can include notifying an administrator or querying the pipeline for how to change the prompt so that results are more similar to the baseline.

Abstract: Systems and methods are described for a messaging agent for managed multidimensional search based on an electronic message and management policies. A messaging application at a client device can send a new electronic message, such as an email, to a connector service. An attachment can be ingested and stored in a vector database. Then one or more artificial intelligence (“AI”) agents can be selected for responding to the body of the email, such as a query in the body. The responses can be formatted and sent to multiple users, such as a sending user of the electronic message and a recipient user that was copied or also sent the new electronic message. The AI agents can use different AI models, prompts, and vector databases depending on user permissions. This allows for building up vector databases with relevant content items and answering user questions based on those vector databases.

Abstract: Systems and methods are described for a maintaining consistent and reliable outputs from artificial intelligence (“AI”) based search systems that use pipelines with a dataset, AI model, and prompt. An application can send a query through a pipeline and set the result as a baseline for future results. The application can periodically resend the query through the pipeline and compare the new results to the baseline. If the new results vary from the baseline above a predetermined threshold, then corrective measures can be taken. This can include notifying an administrator or querying the pipeline for how to change the prompt so that results are more similar to the baseline.

Abstract: Systems and methods are described for a connected AI agent for managed multidimensional search based on an electronic message and management policies. A messaging application at a client device can send a new electronic message, such as an email, to a connector service. An attachment can be ingested and stored in a vector database. Then one or more artificial intelligence (“AI”) agents can be selected for responding to the body of the email, such as a query in the body. The responses can be formatted and sent to multiple parties, such as a sending user of the electronic message and a recipient that was copied or also sent the new electronic message. The AI agents can use different AI models, prompts, and vector databases depending on user permissions. This allows for building up vector databases with relevant content items and answering user questions based on those vector databases.

Abstract: Systems and methods are described for a maintaining consistent and reliable outputs from artificial intelligence (“AI”) based search systems that use pipelines with a dataset, AI model, and prompt. An application can send a query through a pipeline and set the result as a baseline for future results. The application can periodically resend the query through the pipeline and compare the new results to the baseline. If the new results vary from the baseline above a predetermined threshold, then corrective measures can be taken. This can include notifying an administrator or querying the pipeline for how to change the prompt so that results are more similar to the baseline.

Abstract: An application privacy analysis system is described, where the system obtains an application and analyzes it for privacy related data use. The system may determine privacy related activities of the application from established sources of such data and/or may decompile the application and analyze the resulting code to determine the privacy related activities of the application. The system may execute the application and monitor the communications traffic exchanged by the application to determine privacy related activities of the application. The system may store the results of such analyses for future reference.

Abstract: Disclosed are various examples for remotely restricting client devices. A client device can be placed into a restricted mode in which application switching capabilities of the client device are disabled. Additionally, the client device can transmit screen capture data to a management service, which can provide the ability for an administrator user to monitor data shown on a display associated with the client device. The client device can also be removed from the restricted mode in response to a command sent from the management service to the client device.

Abstract: Resource watermarking and management actions on electronic resources are described. In one example, a process for resource watermarking and management actions includes receiving, from a client device, a request to perform an action on an electronic resource and a device profile for the client device. The device profile can include at least one attribute of the client device. The process also includes identifying a watermark template for the electronic resource, determining descriptive data of the watermark template based on the request to perform the action and whether the device profile complies with a compliance rule, overlaying the watermark template and the descriptive data onto the electronic resource, and determining that the client device is authorized to perform the action on the electronic resource in response to the electronic resource being united with the watermark template.

Abstract: An application privacy analysis system is described, where the system obtains an application and analyzes it for privacy related data use. The system may determine privacy related activities of the application from established sources of such data and/or may decompile the application and analyze the resulting code to determine the privacy related activities of the application. The system may execute the application and monitor the communications traffic exchanged by the application to determine privacy related activities of the application. The system may store the results of such analyses for future reference.

Abstract: An application privacy analysis system is described, where the system obtains an application and analyzes it for privacy related data use. The system may determine privacy related activities of the application from established sources of such data and/or may decompile the application and analyze the resulting code to determine the privacy related activities of the application. The system may execute the application and monitor the communications traffic exchanged by the application to determine privacy related activities of the application. The system may store the results of such analyses for future reference.

Abstract: Disclosed are various examples for remotely restricting client devices. A client device can be placed into a restricted mode in which application switching capabilities of the client device are disabled. Additionally, the client device can transmit screen capture data to a management service, which can provide the ability for an administrator user to monitor data shown on a display associated with the client device. The client device can also be removed from the restricted mode in response to a command sent from the management service to the client device.

Abstract: Resource watermarking and management actions on electronic resources are described. In one example, a process for resource watermarking and management actions includes receiving, from a client device, a request to perform an action on an electronic resource and a device profile for the client device. The device profile can include at least one attribute of the client device. The process also includes identifying a watermark template for the electronic resource, determining descriptive data of the watermark template based on the request to perform the action and whether the device profile complies with a compliance rule, overlaying the watermark template and the descriptive data onto the electronic resource, and determining that the client device is authorized to perform the action on the electronic resource in response to the electronic resource being united with the watermark template.

Abstract: An application privacy analysis system is described, where the system obtains an application and analyzes it for privacy related data use. The system may determine privacy related activities of the application from established sources of such data and/or may decompile the application and analyze the resulting code to determine the privacy related activities of the application. The system may execute the application and monitor the communications traffic exchanged by the application to determine privacy related activities of the application. The system may store the results of such analyses for future reference.

Abstract: An application privacy analysis system is described, where the system obtains an application and analyzes it for privacy related data use. The system may determine privacy related activities of the application from established sources of such data and/or may decompile the application and analyze the resulting code to determine the privacy related activities of the application. The system may execute the application and monitor the communications traffic exchanged by the application to determine privacy related activities of the application. The system may store the results of such analyses for future reference.