Abstract: A declarative agent service generates a set of scripts that simulate a user input in a conversation between an agent and the user and runs agent code on the set of scripts to generate a set of responses corresponding to the set of scripts. The service identifies a set of resulting tags based on at least the set of responses and inserts the set of resulting tags in the set of scripts. The service may compare the set of resulting tags with a set of pre-determined tags. In response to determining that at least one of the one or more required tags is not identified in the set of resulting tags or at least one of the one or more prohibited tags is identified in the set of resulting tags, the service may determine that the agent code includes an error and modify the agent code to correct the error.

Abstract: A system receives a portion of a user input from a real-time conversation between an agent and a user. After receiving the portion but before receiving a remainder of the user input, the system dynamically identifies indicators corresponding to an intent of the user based on the portion. The system provides the indicators to a machine learning model to predict user intents. Each predicted user intent is associated with a confidence score indicating a likelihood that the predicted user intent is an actual user intent. The system selects a set of predicted user intents based on the confidence scores and pre-generates a response to the user input for each of the set. The system detects an end of the user input responsive to receiving the remainder and selects a predicted user intent. The system presents the pre-generated response corresponding to the selected predicted user intent.

Abstract: A system uses a machine-learning model to solve micro-escalation events. The system receives, from an artificial intelligence (AI) agent, a stream of input data from a user during a real-time conversation between the AI agent and the user. The system applies the machine-learning model to the stream of input data to identify micro-escalation events. The system creates a communication channel between the agent and one or more human operators. The system assigns each micro-escalation event to a human operator via the communication channel. The system receives a result generated by a respective human operator for each micro-escalation event via the communication channel. The system dynamically integrates the results to form an overall response to the stream of input data from the agent into the real-time conversation.

Abstract: A declarative agent service deploys a hierarchical set of skills with a large language model (LLM) to generate a response to a user input. An agent of the declarative agent service receives a prompt from a user. The agent inputs the prompt into an LLM, which is trained using a taxonomy having a plurality of root classifications, and a set of child classifications under each root classification. The agent receives, from the LLM, a classification corresponding to one of the child classifications based on the prompt. The agent may deploy a hierarchical set of skills to iteratively identify one or more LLM calls based on the classification. Responsive to detecting an exception during deployment of the hierarchical set of skills, the agent overrides the deployment by performing an exception activity.

Abstract: In variants, a method for plan generation can include: determining a set of plans, selecting a plan, optionally determining a set of tasks for the selected plan, optionally performing the set of tasks, and optionally determining a set of explanations for a primary model. However, the method can additionally and/or alternatively include any other suitable elements.

Abstract: A computer-implemented system and method for managing and visualizing financial transaction data is disclosed. Rows of financial data are managed as data objects with a reorganizable node tree hierarchy. A user interface visualization system supports an interactive user interface with a client device. In some implementations, a user may reorganize the node hierarchy, define dimension, communicate on a node-based basis, and assign directly responsible individuals to nodes.

Abstract: A computer-implemented system and method for managing and visualizing financial transaction data is disclosed. Rows of financial data are managed as data objects with a reorganizable node tree hierarchy. A user interface visualization system supports an interactive user interface with a client device. In some implementations, a user may reorganize the node hierarchy, define dimension, communicate on a node-based basis, and assign directly responsible individuals to nodes.

Abstract: A method, system, and non-transitory computer readable medium for displaying relevant messages of a conversation graph. A reverse chronological stream of messages broadcasted to a recipient account of a messaging platform is received. The set of authoring accounts having a predefined graph relationship with the recipient account. Among the stream of messages, a message determined to be a part of a relevant conversation is identified. Additional content associated with the conversation is then inserted into the stream. A client displaying the stream displays the conversation related content with one or more display elements depicting relationships among messages of the conversation.