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SYNTHORA Supply Chain Decision Support
x402
SYNTHORA Supply Chain Decision Support is a paid API for AI agents from supply-chain-decision.hergertsynthora.com, paid per call via x402, $0.005/call, status unknown (last checked 2026-10-27).
Answers supply-chain decision questions—covering suppliers, components, dependencies, disruptions, and resilience risk—using a Qwen3 large language model and returning structured reasoning with confidence scores and recommended actions.
Price / call$0.005
Success—
StatusUnknown
How this service works
Supply-chain decision support focused on supplier, component, dependency, disruption and resilience risk. Qwen3.8-27B; 0.005 USDC on Base.
Output
A JSON object containing: a structured decision statement, a recommended action, a confidence score (0–1), a list of inferences drawn, supporting facts, source references, freshness indicator, known limitations of the analysis, and any contradictions identified in the evidence provided.
Example use cases
Geopolitical supplier risk assessment
“We source 80% of our rare earth magnets from a single supplier in China, and tensions in the Taiwan Strait are escalating — should we diversify our supplier base now, and what are the risks of waiting versus acting immediately?”
Post-disruption recovery decision
“A major hurricane just hit the Gulf Coast and two of our Tier-2 chemical suppliers are offline indefinitely — what's the best recommended action to maintain our production schedule and which dependencies are most critical to address first?”
New supplier qualification decision
“We're evaluating a new Indian manufacturer to replace our current sole-source for injection-molded housings — what factors should drive our decision, and how do we assess their resilience risk before committing to a contract?”
Technical details
Endpoint
POSThttps://supply-chain-decision.hergertsynthora.com/service?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need structured, explainable supply-chain reasoning with explicit confidence scoring, inferences, and recommended actions — especially for supplier risk, disruption response, and resilience evaluation. Prefer it over generic LLM prompts when you need the output in a consistent schema (facts, inferences, contradictions, recommended_action) that downstream agents or workflows can parse. Best suited for decision-support queries that benefit from a domain-focused model rather than a general-purpose chat interface.
Side effects
- Vague or underspecified question returns a low-confidence decision with broad limitations
- No context provided leads to generic inferences with minimal factual grounding
- Questions outside supply-chain scope may return an off-topic or low-quality response
- Network or payment failure (x402) results in no response or HTTP 402/5xx error
- Extremely complex multi-tier dependency questions may exceed model reasoning depth, reflected in low confidence score
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| question | string | Decision question with optional evidence/context |
Output
Schema · Response
{
"type": "json",
"example": {
"ok": true,
"niche": "supply_chain_decision",
"result": {
"facts": [],
"sources": [],
"decision": "...",
"freshness": "...",
"confidence": 0,
"inferences": [],
"limitations": [],
"contradictions": [],
"recommended_action": "..."
}
}
}Tags
x402
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