Classification Application
Auto-tag every incoming item against your classification scheme.
Runs each arriving item — document, ticket, transaction, product — through a classification scheme and assigns category labels. Rules, ML classifiers, or hybrid. The output is a continuously labelled stream that makes downstream search, routing, and reporting possible. Nothing else in the stack changes what kind of thing an item is — this does.
Shape
Operational dimensions
Runs without a person in the path.
Fires when an upstream condition occurs.
Holds working state that compounds over runs.
Reads from and writes to external systems.
Inputs
- item stream (documents, tickets, transactions, products, content)
- classification scheme (taxonomy or label set)
- rules, model weights, or hybrid config
- confidence threshold settings
Outputs
- per-item label assignments with confidence scores
- ambiguous / low-confidence cases flagged for review
- classification distribution metrics (optional)
Mechanism
Applies a defined classification scheme to incoming items by assigning one or more category labels per item — the tagged items are the deliverable.
Why this is a primitive
Cannot be decomposed: the inspect-item → predict-or-rule-match-categories → assign-labels operation is a single act of categorisation. It assumes the scheme already exists (vocabulary-authoring), assumes the item is in canonical form, and does not link the item into a graph (graph-instantiation). It just answers 'what category/categories does this item belong to?'
Where it shows up
Related primitives
Tags
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Primitives are configured into named solution shapes for each client’s domain. The fastest next step is a conversation about which shape fits your problem.
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