What is Multimodal AI?
Multimodal AI models are capable of simultaneously processing and understanding multiple data types: text, images, audio, video, and even code. Instead of separate models for text and images, one model understands cross-modal context.
Application examples
"Describe what you see in this photo and answer questions about this text" — a multimodal model processes both together. Practical uses: document analysis with images and tables, video meeting transcription, invoice processing (OCR + context understanding), visual product inspection + report generation.
Future of enterprise AI
Multimodality changes automation approaches: instead of building separate pipelines, a multimodal agent processes entire documents at once. This simplifies architecture and improves results — the model sees context that would be lost when separating into stages.