Multimodal AI: definition

Multimodal AI is a model that can take in or produce more than one kind of data, such as text plus images, audio, or video, rather than text alone.

A text-only model reads and writes words. A multimodal model can also look at a photo of a damaged part, read a scanned invoice, or listen to a call, and reason across all of it in one request.

For a business this unlocks the work that was stuck in images and audio: reading documents, checking photos, understanding recordings, without a separate tool for each format.

Related terms

Large language model (LLM): A large language model is a neural network trained on huge amounts of text to predict the next token, which lets it write, summarise, classify, and answer questions across almost any topic.
Inference: Inference is the act of running a trained model to get an output, and inference cost is what you pay each time the model answers, measured in tokens.
Voice agent: A voice agent is an AI system that answers or makes phone calls, understands speech, holds a natural conversation, and takes actions like booking or rescheduling, usually handing off to a human when needed.