What is AgentRow?

AgentRow is a visual AI agent builder. You design an agent as a graph of nodes in the dashboard (input, memory, knowledge retrieval, language model, tools, validation, output), test it in a chat panel, and publish it. The same graph you draw is the graph the runtime executes, in the same order, with every step recorded.

AgentRow is built for teams that want to ship AI assistants without stitching together frameworks by hand:

• Agents are executable workflows. Each node has explicit settings, and a run shows exactly which node ran, what the model was sent, which tools were called and what came back.
• Apps package one or more agents behind a public surface. Today that surface is an embeddable chat widget for websites; a router decides which agent handles a message.
• Tools connect agents to HTTP APIs, databases, browsers, code execution and other systems, with schemas, authentication, safety levels and rate limits.
• Knowledge bases hold your documents, chunked and embedded, so agents answer from your content with citations.
• Memory lets agents remember durable facts and preferences per user, per conversation, per agent or per app, with approval before anything is saved.
• Observability is native: runs, steps, generations, tool calls, retrievals, memory reads and writes, token usage and cost are all stored and browsable.

Typical uses: customer support assistants embedded on a website, internal operations assistants over company data, sales proposal assistants, e-commerce product assistants, developer debugging assistants, and workflow automation agents.