Multimodal

AI models that can process and combine multiple types of input, such as text, images, and audio.

What is Multimodal AI?

Multimodal systems can understand and process different types of information simultaneously. For AI automation, this capability enables more comprehensive analysis and processing of complex content.

Multimodal capabilities allow for the creation of sophisticated workflows that can handle various types of inputs and outputs, from documents with images to audio-visual content.

Why are Multimodal Systems important?

Multimodal AI enables more comprehensive and natural automation solutions. For businesses using Lleverage, this means being able to process complex, real-world inputs that combine different types of information. This capability is particularly valuable for applications that need to handle diverse content types or provide more natural and comprehensive interactions.

How you can use
Multimodal
with Lleverage

A real estate company uses Lleverage to automate property listing creation. Their workflow processes property photos, floor plans, and textual descriptions simultaneously, automatically generating comprehensive listings that combine visual and textual information in a coherent way.

Multimodal
FAQs

Everything you want to know about

Multimodal

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What types of input can multimodal AI handle?

Common input types include text, images, audio, video, and structured data, often processed simultaneously.

How does multimodal AI improve automation workflows?

It enables more comprehensive processing of complex content and can handle real-world scenarios that involve multiple types of information.

More references for
Multimodal

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