A canvas in the context of AI agents refers to a visual workspace where users and intelligent systems collaborate on shared content in real time.

Durable execution refers to a programming model where workflow state persists automatically, allowing processes to resume exactly where they left off after failures, restarts, or infrastructure outages.

A graph-based workflow is a computational model that represents tasks, decisions, and processes as interconnected nodes within a directed graph structure.

An MCP Server is a service that exposes tools, resources, and prompts to AI agents through the Model Context Protocol, a standardized interface for agent to tool communication.

MCP Tools are standardized interfaces that allow AI agents to interact with external systems, databases, and services through the Model Context Protocol.

Parallel task execution refers to an AI agent architecture pattern where multiple independent operations run simultaneously rather than sequentially.

how an orchestration layer matches incoming tasks to the most suitable AI agent based on predefined roles and verified capabilities.

This architectural choice defines how agents manage workloads, prioritize requests, and maintain consistency during complex financial operations.

Standardized tool integration refers to the practice of connecting AI agents to external services, databases, and APIs through consistent, well defined interfaces.

State management in graph systems refers to the techniques and architectures that track, persist, and synchronize data as it flows through interconnected nodes in a graph based workflow.

Agent constraints are the boundaries, rules, and limitations that govern what an AI agent can and cannot do during autonomous operation.

Agent response filtering is the process of inspecting, modifying, or blocking outputs generated by AI agents before those outputs reach end users or downstream systems.

Agentic orchestration refers to the coordination and management of multiple autonomous AI agents working together to accomplish complex tasks.

Linear task handling refers to a sequential execution model where an AI agent processes tasks one at a time, completing each step before moving to the next.

Memory storage refers to the systems and mechanisms that allow AI agents to retain, organize, and retrieve information across sessions and interactions.

Multi-agent orchestration refers to the coordination and management of multiple AI agents working together to accomplish complex tasks that exceed the capabilities of any single agent.

A multimodal agent is an AI system that can perceive, reason about, and generate content across multiple data types including text, images, audio, and video.

Process automation refers to the use of technology to perform repetitive tasks or workflows with minimal human intervention.

Prompt engineering is the practice of designing and refining the text inputs given to large language models to elicit accurate, useful, and consistent outputs.