AgentsFlow abstracts each AI agent as a node in a directed graph, enabling developers to visually and programmatically design complex pipelines. Each node can represent an LLM call, data preprocessing task, or decision logic, and can be connected to trigger subsequent actions based on outputs or conditions. The framework supports branching, loops, and parallel execution, with built-in error handling, retries, and timeout controls. AgentsFlow integrates with major LLM providers, custom models, and external APIs. Its monitoring dashboard offers real-time logs, metrics, and flow visualization, simplifying debugging and optimization. With a plugin system and REST API, AgentsFlow can be extended and integrated into CI/CD pipelines, cloud services, or custom applications, making it ideal for scalable, production-grade AI workflows.

Deerflow provides a visual interface where users can assemble AI workflows from modular components—input processors, LLM or model executors, conditional logic, and output handlers. Out of the box connectors allow you to pull data from databases, APIs, or document stores, then pass results through one or more AI models in sequence. Built-in tools handle logging, error recovery, and metric tracking. Once configured, workflows can be tested interactively and deployed as REST endpoints or event-driven triggers. A dashboard gives real-time insights, version history, alerts, and team collaboration features, making it simple to iterate, scale, and maintain AI agents in production.

Agent Visualiser is a developer-focused visualization tool that maps the internal operations of AI agents into intuitive graphical flows. It hooks into an agent’s runtime, capturing every prompt, LLM call, decision node, action execution, and memory lookup. Users can view these steps in an interactive graph, expand nodes to inspect parameters and responses, and trace back the logic path that led to each outcome. The tool supports LangChain agents out of the box, but can be adapted for other frameworks via simple adapters. By providing real-time insights and detailed step breakdowns, Agent Visualiser accelerates debugging, performance tuning, and knowledge sharing across development teams.