AI-PEDIA

Learn the language of automation.

A simple guide to the terms we use every day. Clear explanations to help you understand how the technology works.

- 14 terms

Automations powered by models that can read, decide, and act with your data.

Meeting legal and policy requirements when you build and run AI features.

Using models to choose or recommend actions based on data and goals.

The process of serving a trained model so real users and systems can call it.

Policies, processes, and oversight that guide how AI is built and used.

Running a trained model to get an output for a real request.

The learned function that maps inputs to predictions, decisions, or generated content.

Watching model quality, cost, and safety in production so you can react fast.

Tuning prompts, models, and settings to improve quality, speed, and cost.

A set of tools and services that let you build, ship, and manage AI features in one place.

Models that suggest the next best item, action, or piece of content.

Protecting models, data, and outputs from abuse, leaks, and tampering.

Software that bakes AI into the product so users get smarter help by default.

All the pieces that make an AI feature work: models, data, tools, and guardrails together.