Multimodal AI is AI that can understand more than one kind of input, such as text, images, audio and documents, and connect them. You can show it a photo and ask a question about it, upload a scanned form and have it read, or speak and have your words turned into structured notes. Earlier AI tools handled one type at a time. Most leading models today, including GPT, Claude and Gemini, can work with text and images together.
An everyday analogy
Think of explaining a broken boiler over the phone versus sending a photo. On the phone you describe: "There is a red light, and a sort of clicking." With a photo, the engineer sees the model number, the error code and the pipework at once.
A text-only AI is the phone call. A multimodal AI gets the photo too.
What "modes" are
A mode (or modality) is a type of information:
- Text: questions, emails, contracts.
- Images: photos, screenshots, charts, scanned pages, drawings.
- Audio: speech, recordings, dictation.
- Video: moving images, sometimes with sound.
- Documents: really a mix: a PDF can contain text, tables, charts and handwritten notes on the same page.
A multimodal model turns each of these into a form it can process together. For text, that is tokens (see what are tokens in AI). Images and audio are converted into similar internal pieces, so the model can "read" a chart and a paragraph side by side.
Concrete examples (fictional)
Clinic. A physiotherapist at "Riverside Physio" photographs a handwritten referral that arrived by fax. A multimodal AI reads the handwriting, pulls out the referring doctor, the diagnosis and the requested sessions, and drafts a reply. She checks it against the paper.
Law firm. An associate at "Grant & Cole" has 25 scanned contracts from a client's archive, some with stamps and handwritten amendments. A text-only tool sees almost nothing in a scan. A multimodal tool looks at each page as an image and can find the handwritten change to clause 9.
Office. A finance assistant uploads last quarter's slide deck and asks: "What does the chart on slide 7 show, and does it match the numbers in the spreadsheet?" The AI reads the chart and the spreadsheet and points out one figure that differs.
What it is good at, and where it slips
Good at: reading scans and screenshots, describing charts, turning speech into text, combining several sources in one answer.
Weaker at:
- Very small print, poor scans or messy handwriting.
- Precise measurements from an image (exact lengths or counts).
- Medical images: general models are not diagnostic tools and should not be used as one.
As with all generative AI, it can describe things confidently and wrongly. Check anything that matters.
What this means for confidential data
Practical tip: images carry more than you think. A photo of a document can show a name in the header, a screenshot can show an open patient list in the background, and voice recordings contain names spoken aloud. Crop and check before uploading.
And the same question applies to every file you upload: may the provider reuse it? If so, it can remove the names, and the remaining content (the scan, the diagnosis, the figures) is no longer protected by the GDPR. Legally it can then be pooled and sold. See the data trail.
Multimodal work in Wysor
In Wysor you can upload PDFs, Word, Excel and PowerPoint files, CSV data and images, and work with them using GPT, Claude, Gemini and more. The Knowledge Base agent looks at document pages visually, so scanned contracts, charts and handwritten notes become searchable with cited answers. AutoCAD drawings (.dwg and .dxf) are rendered into an image a vision model can look at, as described in our AI for construction guide. For audio, Scribe turns recorded conversations into structured notes.
We act only as your processor, never train on your files or sell them, and every connected model provider runs with zero data retention.
FAQ
What is multimodal AI in simple terms? AI that can take in different kinds of information, like text, pictures and sound, and understand them together.
Is ChatGPT multimodal? Yes. Current ChatGPT models can work with text and images, and the app supports voice. Claude and Gemini also handle text and images.
What is the difference between generative AI and multimodal AI? Generative AI describes what the AI does: it creates content. Multimodal describes what it can take in or produce: several types of media. Many tools are both. See what is generative AI.
Can multimodal AI read scanned documents? Yes, by looking at the page as an image. Quality depends on the scan, and important details should be checked against the original.
Further reading
Questions about using AI with sensitive data? Reach us at [email protected] or through the in-app contact form.