Multimodal RAG (text + image + video)

We build multimodal retrieval-augmented generation systems that go beyond text and pull from images, diagrams, screenshots, and video alongside written content. Our team handles vision model selection, frame extraction, caption generation, and unified embedding so a single question can return a written explanation, a relevant diagram, and a video segment from a training library. We design retrieval logic that ranks across modalities and presents results in a clear, citation-backed interface. We also tune the system for your domain, whether that means product photos, engineering schematics, medical imaging, or recorded webinars. The outcome is a knowledge layer that reflects how people actually communicate inside your company, with answers that show the right picture or clip instead of only describing it in text.