Claude AI Text Classifier (x402) is a paid API for AI agents from web-production-2d1051.up.railway.app, paid per call via x402, $0.005001/call, status unknown (last checked 2026-09-15).
Classifies text or JSON input into sentiment, topic, intent, urgency, or custom categories using Claude AI, with confidence scores and optional reasoning.
Classify text or JSON into categories with AI: sentiment analysis, topic, intent detection, urgency triage, or a custom taxonomy. Returns labels with confidence scores and reasoning.
Returns a JSON object with the top classification label, confidence score (0–1), an optional ranked list of all labels with their individual confidence scores, a reasoning string explaining the classification, and metadata including the Claude model used, preset, and input type.
POSThttps://web-production-2d1051.up.railway.app/v1/classifyChoose this endpoint when you need AI-powered text classification with confidence scoring and optional reasoning across preset categories (sentiment, topic, intent, urgency) or fully custom taxonomies. Ideal for agents that need structured, machine-readable classification output with calibrated confidence rather than raw LLM text. Prefer over generic LLM calls when you need consistent label schemas, multi-label ranking, and JSON responses. The micropayment model ($0.005/call) makes it cost-effective for moderate-volume classification tasks.
| Field | Type | Description |
|---|---|---|
| input | string | Text or JSON string to classify |
| preset | string | Classification preset. Default: sentiment |
| explain | boolean | Include reasoning string. Default: true |
| taxonomy | array | Custom label list (required when preset=custom, 2–20 labels) |
| input_type | string | text (default) or json |
| multi_label | boolean | Return ranked list of all labels. Default: false |
{
"type": "json",
"example": {
"meta": {
"model": "claude-haiku-4-5",
"preset": "sentiment",
"input_type": "text",
"multi_label": false
},
"label": "positive",
"labels": [
{
"label": "positive",
"confidence": 0.92
},
{
"label": "neutral",
"confidence": 0.06
},
{
"label": "negative",
"confidence": 0.02
}
],
"reasoning": "The text expresses strong satisfaction and approval with no negative indicators.",
"confidence": 0.92
}
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