A Classification skill processes one file per transaction. To classify several files containing documents of different types, use the Classify Activity Process skill.
How it works
To train a Classification skill, specify the classes you want and provide a few example documents for each. Vantage analyzes the text and visual elements of each document — including seals and signatures — so the classifier can handle low-quality images and distinguish between similar document types.When to use a Classification skill
A Classification skill can run as part of a Process skill or on its own:- As part of a Process skill. The classifier sorts each incoming document by type, and the Process skill automatically routes it through the rest of the pipeline.
- On its own. Classify documents directly through the Vantage API, or through a front-end built on it such as the Try Any Skill portal.
Typical use cases
- Sorting mailroom intake into invoices, contracts, and correspondence
- Triaging archived documents before extraction
- Routing inbound requests to the correct department
Relationship to other skills
A Classification skill sits at the front of a document pipeline and decides what type each file is. Other Vantage skills handle what happens next:- Document skill — extracts field data from a document once its type is known.
- OCR skill — produces searchable text from an image or PDF.
- Process skill — orchestrates multiple skills (classification, extraction, validation) into a single workflow.
Common misconceptions
A Classification skill labels documents by type. It does not extract field values, run validation rules, or produce searchable text. For field extraction, pair it with a Document skill. For text recognition only, use an OCR skill.Next steps
Set up a Classification skill
Configure languages, Online learning, and publishing for a new Classification skill.
Train a classifier
Build a training set, assign documents to classes, and run classifier training.
Analyze classifier results
Review per-class accuracy in the Result tab and fix common training-set errors.
