The AI & Automation
Glossary

A software program that uses an LLM to perceive inputs, reason about them, and take autonomous actions to achieve a goal — without human direction at each step.

The use of software to execute a sequence of business tasks automatically, based on predefined rules or triggers — replacing manual, repetitive work.

An open-source, self-hostable workflow automation platform that lets you build complex automations and AI agent workflows using a visual node-based interface — with no code required.

The practice of building automated workflows and AI systems using visual, drag-and-drop tools — without writing any programming code.

Retrieval-Augmented Generation — an AI technique where a language model retrieves relevant information from an external knowledge base before generating a response.

The process of connecting a large language model to a business application, workflow, or data source — allowing the LLM to process inputs and take actions within that system.

An AI architecture where multiple specialized AI agents collaborate — each handling a different subtask — to complete complex goals that a single agent couldn't handle efficiently alone.

The practice of designing and refining text inputs (prompts) to guide large language models toward producing more accurate, useful, or structured outputs.

The combination of artificial intelligence and workflow automation — using AI models to make decisions, handle exceptions, and process unstructured data within automated business processes.

AI systems that operate autonomously over extended tasks — planning multi-step actions, using tools, and adapting their behavior based on results without requiring human input at each step.