{"uid":"cap_aT7KC-IeGzx-TjkJI2j7S","slug":"synthora-decision-engine-b12f42f5","name":"SYNTHORA Decision Engine","description":"General decision synthesis for an agent that has a question plus optional evidence or context. Separates observed facts from inferences and gives a traceable recommended action. Qwen3.8-27B; 0.005 USDC on Base.","url":"https://decision-engine.hergertsynthora.com/service?utm_source=zero.xyz","method":"POST","headers":{},"bodySchema":{"type":"object","properties":{"question":{"type":"string","description":"Decision question with optional evidence/context"}}},"responseSchema":{"type":"json","example":{"ok":true,"niche":"decision_engine","result":{"facts":[],"sources":[],"decision":"...","freshness":"...","confidence":0,"inferences":[],"limitations":[],"contradictions":[],"recommended_action":"..."}}},"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.005","displayCostAsset":"USDC","priceDynamic":false,"priceHint":null,"priceStatus":"priced","priceSource":"probe","requiresHandshake":false,"reviewCount":0,"rating":{"score":"0.00","successRate":"0.00","reviews":0,"stars":null,"state":"unrated"},"availabilityStatus":"down","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.005/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.005","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.005","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_rXE1-yX0N2m9ocUiiiFne","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.005","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Synthesizes a traceable decision recommendation from a question plus optional evidence, separating observed facts from inferences using Qwen3 reasoning.","exampleAgentPrompt":"I need to decide whether to accept this job offer — the salary is 20% higher but requires relocation and the company is a Series A startup. Can you synthesize a decision for me, separating what's fact from what's inference, and give me a recommended action with a confidence score?","exampleUseCases":[{"title":"Medical triage decision support","prompt":"My patient has fever, elevated CRP, and a recent travel history to a malaria-endemic region but negative rapid tests. Help me decide whether to start empirical antimalarial treatment anyway — separate the facts from inferences and give me a recommended action with your confidence and limitations noted."},{"title":"Investment risk assessment","prompt":"I'm deciding whether to put $50k into a real estate deal in Phoenix — rental yields are 6%, the neighborhood is gentrifying, but interest rates just rose 50bps. Synthesize a decision for me, tell me what's observed fact vs inference, flag any contradictions, and give me a clear recommended action."},{"title":"Product launch go/no-go decision","prompt":"We have a product launch scheduled for next Friday — beta feedback scores are 4.2/5, but our payment integration has one unresolved bug and two enterprise clients haven't signed NDAs yet. Should we launch on time? Give me a traceable decision with facts, inferences, confidence level, and a recommended action."}],"resultDescription":"Returns a structured JSON object containing: a list of observed facts extracted from the question/context, a list of inferences drawn by the model, a decision summary, a recommended_action string, a numeric confidence score (0-1), data freshness assessment, known limitations of the analysis, and any contradictions detected in the provided evidence.","failureModes":["Missing or empty question field returns an error response","Ambiguous or very short questions may yield low confidence scores and broad limitations","Model may fail to distinguish user-supplied facts from inferences if context is poorly structured","Contradictions in the input may cause the model to hedge heavily without a clear recommended action","Network or payment authorization failures return non-ok responses"],"whenToPreferThis":"Choose this endpoint when you need a structured, traceable decision output that explicitly separates facts from inferences — not just a free-text opinion. It's especially useful when the agent needs to audit its own reasoning, show confidence levels, or flag contradictions in the supplied evidence. Prefer it over a generic LLM chat call when the output must be machine-parseable (facts[], inferences[], recommended_action) and when decisions need to be logged or explained downstream.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-31T06:25:09.638Z","isFirstParty":false,"canonicalSlug":"synthora-decision-engine-b12f42f5"}