AI & Automation Glossary

New to AI or looking to speak the same language as your tech team? This glossary breaks down key terms in plain English—so you can better understand the technologies shaping your business.

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Your Go-To Glossary for AI, Agents & Automation

Browse alphabetically or search for a specific term. We’re constantly updating this page with relevant, real-world definitions to keep you informed.

A

Agentic AI

A model of artificial intelligence where AI agents operate autonomously with the ability to make decisions, adapt to environments, and pursue goals over time.

API (Application Programming Interface)

A set of rules that allows two or more software systems to communicate and share data or functions seamlessly.

Autonomous Agent

An AI-powered system that can perceive its environment, make decisions, and take actions independently to achieve a specific objective.

C

Conversational AI

Technology that enables machines to understand, process, and respond to human language—used in chatbots, virtual assistants, and voice applications.

Cloud Computing

The delivery of computing services (like servers, databases, and software) over the internet, enabling flexible and scalable infrastructure.

D

Data Pipeline

A series of automated processes that move data from one system to another for storage, transformation, or analysis.

Decision Engine

A system or component that uses rules or AI models to evaluate data and determine actions within a workflow or process.

F

Fine-Tuning (AI)

The process of taking a pre-trained AI model and adjusting it with a smaller, specific dataset to improve its performance for a targeted task.

G

GraphQL

A query language for APIs that allows clients to request exactly the data they need, improving performance and flexibility over traditional REST APIs.

L

LLM (Large Language Model)

A type of AI model trained on vast amounts of text data, capable of generating human-like text, answering questions, and performing complex language tasks.

LlamaIndex (GPT Index)

An AI framework that connects large language models to external data sources, enabling smart retrieval and contextual responses from custom datasets.

M

Machine Learning (ML)

A subset of AI where systems learn from data and improve performance without being explicitly programmed for every scenario.

O

OAuth2

An authorization framework that enables secure delegated access—allowing apps to access user data without exposing login credentials.

P

Pinecone

A vector database built for fast, scalable similarity search—commonly used in AI systems for search, retrieval, and recommendations.

Prompt Engineering

The practice of crafting precise inputs to guide large language models like GPT for more accurate and relevant responses.

R

RAG (Retrieval-Augmented Generation)

A method of combining language models with external data sources to produce more grounded and accurate responses by retrieving relevant information before generating answers.

W

Webhook

An automated message sent from one system to another when an event occurs, enabling real-time communication between tools and apps.

Workflow Automation

The use of software and AI to execute business processes and tasks without human intervention—reducing manual work and errors.