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NetIntel Event Classify
x402
NetIntel Event Classify is a paid API for AI agents from netintel.dev, paid per call via x402, $0.02/call, status unknown (last checked 2026-09-13).
Classifies whether a given text or topic refers to a specific real-world event (e.g. a dated occurrence) versus a general concept, returning a confidence score and reason.
Price / call$0.02
Success—
StatusUnknown
How this service works
Cheap, fast "is this a dateable event?" filter for social and web text — one tiny Haiku call returns is_event, confidence, and a one-line reason, so agents can screen every post for free-ish and only pay for full extraction on the ones that pass. Front-end filter to /event-extract; intentionally minimal output for cost/latency discipline.
Output
Returns a JSON object with: is_event (boolean indicating if the text describes a specific event), confidence (float 0-1), reason (human-readable explanation), plus a grade (letter A-F), numeric score (0-100), and any findings. Model metadata is included.
Example use cases
Example prompt
“Can you classify whether this text is describing a specific real-world event or just a general concept: 'The Federal Reserve emergency rate cut on March 15, 2020'? I want to know if it's an event, why, and how confident you are.”
Technical details
Endpoint
POSThttps://netintel.dev/event-classifyWhen to prefer
Use this endpoint when you need to determine programmatically whether a piece of text or a search query refers to a specific, dated real-world event (news, incident, occurrence) versus a generic topic or concept. Ideal for routing logic in search engines, news classifiers, query understanding systems, or agent pipelines that behave differently for event-driven vs. evergreen content. Prefer it over general-purpose LLM calls for its pay-per-call micropayment model (no subscription), automatic no-charge on failures, and purpose-built confidence scoring.
Side effects
- Input text is missing or empty — returns validation error, not billed
- Upstream AI model failure — returns server error, not billed
- Ambiguous text yields low confidence score (e.g. 0.4) with is_event uncertain
- Rate limits or network timeouts from the underlying model provider
- Text in unsupported language may yield lower accuracy or undefined behavior
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"data": {
"reason": "specific dated event",
"is_event": true,
"confidence": 0.93
},
"meta": {
"model": "haiku-4.5"
},
"grade": "A",
"score": 100,
"findings": []
}
}Tags
x402
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