Intent Detection

x402

Intent Detection is a paid API for AI agents from x402.agentindex.world, paid per call via x402, $0.002/call, status unknown (last checked 2026-10-29).

Classifies text as a question, request, complaint, compliment, or other, returning a confidence score and alternate label within 4.5 seconds

Price / call$0.002

Seller volume →—

Success—

StatusUnknown

How this service works

Intent detection: classify text as a question, request, complaint, compliment, or other, with a confidence score and an alternate label. Powered by Jev, with an automatic Groq-hosted LLM fallback if Jev is slow or unavailable - under 4.5s guaranteed. Try GET /intent/sample.

Output

Returns a primary intent label (question, request, complaint, compliment, or other), a confidence score between 0 and 1, and an alternate label suggesting the next most likely intent category.

Example use cases

Triage customer support tickets

“Classify this support message by intent so I can route it correctly: 'Your app keeps crashing every time I try to upload a photo — I've lost hours of work.'”

Filter positive feedback from complaints

“Tell me whether this user review is a complaint, compliment, or something else, and how confident you are: 'Honestly the onboarding was seamless and the team responded within minutes!'”

Detect questions in chatbot logs

“Go through this user message and tell me if it's a question, a request, or something else — I need to know the intent and an alternate label too: 'Can someone explain how refunds work for annual subscriptions?'”

Technical details

Endpoint

GEThttps://x402.agentindex.world/intent?utm_source=zero.xyz

When to prefer

Choose this endpoint when you need fast, structured intent classification with a confidence score and alternate label, particularly for customer-facing text like support tickets, chat messages, or user reviews. It is ideal when you need guaranteed sub-4.5s latency thanks to its dual-provider architecture (Jev + Groq fallback), and when you want a pay-per-call model with no subscription overhead. Prefer it over general-purpose LLM prompting when you want a consistent, schema-bound output for downstream routing logic.

Side effects

Text exceeding 4000 characters may be rejected or truncated
Both Jev and Groq fallback unavailable — call may fail after timeout
Ambiguous or very short text may produce low-confidence or inaccurate classifications
Non-English text may yield unreliable results depending on model support
Network timeout beyond the 4.5s guaranteed SLA if both providers are degraded

Input

Schema · Request body

Field	Type	Description
text	string	Text to classify, up to 4000 characters.

Output

Schema · Response

{
  "type": "json",
  "example": {
    "input": "Could someone take a look at why my last two orders were both delayed?",
    "label": "request",
    "engine": "jev",
    "probability": 0.55,
    "alternate_label": "question",
    "alternate_probability": 0.29
  }
}

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Run ID: run_7f3a9c2e
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