Multimodal AI
AI that can process and relate more than one type of input, such as text together with images, documents, or audio, within a single model.
In more detail
Multimodal AI handles more than one input type in the same model. A multimodal model can read an image alongside text, interpret a scanned invoice, describe a screenshot, or answer a question about a chart. This removes a brittle preprocessing step that older pipelines needed to convert everything to text first.
For automation, multimodal capability matters wherever the source data is not clean text: a photographed receipt, a PDF with tables, a product image, or a screen the workflow needs to understand. The model can work with the artifact as it actually exists rather than requiring a perfect text extraction first.
Where this shows up at Ceven
Ceven's workflows can include steps that read documents and images directly, so a process that starts with a scanned form or a screenshot does not need a separate extraction tool bolted on ahead of it. The interpreted result flows into the rest of the workflow like any other step, with the same approval gates and audit trail.