Tag

Consistent labels. Clean data.

Auto-tagging and taxonomy normalisation for support data quality. Ensure consistent, meaningful labels across your entire support operation.

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Capabilities

Everything you need

Built for production. Designed for simplicity.

Auto-Tagging

Automatically tag cases using LLM analysis, optionally constrained to a known tag set.

Tag Normalisation

Find and merge inconsistent tags into canonical forms.

Drift Detection

Detect how tag usage changes over time and alert on drift.

Schema Suggestions

Generate recommended tag schemas from your actual case data.

Coverage Analysis

See which tags are overused, underused, or missing.

Quality Scoring

Score tagging consistency and coverage across your operation.

Integration

Simple to use

Auto-tag support cases with consistent labels.

Full API Reference
tag_example.py
import httpx

resp = httpx.post("http://localhost:8015/api/v1/auto-tag", json={
    "cases": [
        {"subject": "Can\'t login to my account", "body": "..."},
    ],
    "max_tags": 3,
})

API

Endpoints

Clean REST APIs. No SDK required.

POST
/api/v1/auto-tag
Auto-tag cases
POST
/api/v1/normalize
Normalise tags
POST
/api/v1/drift
Detect tag drift
POST
/api/v1/suggest-schema
Suggest tag schema
GET
/health
Service health check

Learn more about Tag

Explore how this AI capability can transform your support operations.

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