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SYNTHORA decision_pulse
x402
SYNTHORA decision_pulse is a paid API for AI agents from decision-pulse.hergertsynthora.com, paid per call via x402, $0.005/call, status unknown (last checked 2026-10-27).
Performs fast AI-driven decision triage on a single question or signal, returning a structured breakdown of facts, inferences, contradictions, confidence, limitations, and a recommended action.
Price / call$0.005
Success—
StatusUnknown
How this service works
Fast decision triage from one signal or question. Returns a structured decision, facts, inferences, contradictions, confidence, limitations and a recommended action. Qwen3.8-27B; 0.005 USDC on Base.
Output
A JSON object containing: a top-level decision statement, an array of supporting facts, inferences drawn from the signal, contradictions identified, a confidence score (0-1), a freshness indicator, a list of limitations, and a concrete recommended_action string.
Example use cases
Go/no-go launch decision
“Should we go live with this pricing change next Monday given that our A/B test showed a 3% revenue lift but customer satisfaction dropped slightly? Give me the facts, contradictions, confidence level, and what you recommend we do.”
Investment opportunity triage
“I'm looking at a Series A startup in the logistics space — they have strong unit economics but a crowded market. Triage this decision for me: what are the key facts, inferences, contradictions, and what action should I take?”
Operational risk assessment
“Our main supplier just notified us of a 6-week delay. Triage this situation for me — what are the facts, what can we infer, are there any contradictions I should know about, and what's the recommended action?”
Technical details
Endpoint
POSThttps://decision-pulse.hergertsynthora.com/service?utm_source=zero.xyzWhen to prefer
Choose decision_pulse when you need a fast, structured triage of a single decision or signal with explicit confidence scoring and contradiction detection — ideal for lightweight decision support in agent pipelines where a full reasoning chain or multi-source research tool would be overkill. Prefer this over generic LLM calls when you need a consistent schema with facts, inferences, contradictions, and a recommended action in one shot.
Side effects
- Vague or ambiguous question may produce low-confidence output with many listed limitations
- Network or payment failure returns a non-2xx HTTP response with no result body
- Question outside the model's knowledge cutoff may yield low freshness and hedged inferences
- Extremely complex multi-part questions may result in oversimplified facts or missed contradictions
- Payment of 0.005 USDC not fulfilled results in a 402 Payment Required response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| question | string | Signal or decision question |
Output
Schema · Response
{
"type": "json",
"example": {
"ok": true,
"niche": "decision_pulse",
"result": {
"facts": [],
"sources": [],
"decision": "...",
"freshness": "...",
"confidence": 0,
"inferences": [],
"limitations": [],
"contradictions": [],
"recommended_action": "..."
}
}
}Tags
x402
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