{"uid":"cap_jPHcidZGX-7Q0CspzKhDW","slug":"foundrynet-inference-predictive-analytics-6aa983bc","name":"FoundryNet Inference Predictive Analytics","description":"LLM inference proxy + data-enriched analysis + predictive intelligence. 17 data sources. MINT-attested outputs. x402-gated (Solana/Base USDC); an fnet_ Forge key bypasses.","url":"https://foundrynet-inference-production.up.railway.app/v1/predict","method":"POST","headers":{},"bodySchema":{"type":"object","required":["values","threshold"],"properties":{"oem":{"type":"string","description":"Optional equipment manufacturer (enables field normalization)"},"values":{"type":"array","description":"Time series values (16+ recommended for a reliable forecast)"},"direction":{"type":"string"},"threshold":{"type":"number","description":"Breach threshold"},"canonical_field":{"type":"string","description":"Optional field name (e.g. spindle_load_pct); with `oem` it enables canonical normalization"}}},"responseSchema":null,"example":null,"exampleRequest":null,"tags":["x402"],"displayCostAmount":"0.1","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":"unknown","priceObserved":null,"sessionDeposit":null,"pricing":{"kind":"static","summary":"$0.1/call","primary":{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.1","per":"call","confidence":"exact"},"accepted":[{"kind":"static","protocol":"x402","network":"base","amountUsd":"0.1","per":"call","confidence":"exact"}]},"paymentMethods":[{"uid":"pm_23jUou69E8swiI8b7ZJv5","protocol":"x402","methodType":"crypto","chain":"base","mode":"charge","costAmount":"0.1","costPer":"request","priority":0,"asset":"0x833589fCD6eDb6E08f4c7C32D4f71b54bdA02913","unit":"request","depositMicros":null,"planRef":null}],"brandName":null,"brandSlug":null,"brandBaseUrl":null,"brandDocsUrl":null,"whatItDoes":"Accepts a time-series array and breach threshold to produce LLM-enriched predictive intelligence with MINT-attested outputs, optionally normalizing by OEM and canonical field name.","exampleAgentPrompt":"Using FoundryNet's MINT-attested predictive inference, analyze this 20-point spindle load time series — [72,74,75,78,80,83,85,84,87,90,91,93,95,96,98,99,100,102,104,107] — for OEM 'HaasMill', canonical field 'spindle_load_pct', with a breach threshold of 105 in the 'up' direction, and tell me if and when it's likely to breach.","exampleUseCases":null,"resultDescription":"Returns a predictive intelligence result enriched by LLM inference and up to 17 data sources, including whether the time series is forecasted to breach the given threshold, in what direction, and with a MINT-attested output for verifiability.","failureModes":["Payment not provided or invalid x402/fnet_ key — returns 402 Payment Required","Fewer than 16 values in array — reduced forecast reliability or rejection","Invalid OEM or canonical_field — normalization skipped or error returned","Threshold or direction mismatch with series — ambiguous or low-confidence prediction","Service unavailable on Railway — 503 or timeout"],"whenToPreferThis":"Choose this endpoint when you need LLM-enriched, MINT-attested predictive forecasting on time-series data — especially for industrial/OEM equipment metrics where canonical field normalization matters. Prefer it over generic inference APIs when attestation, multi-source enrichment, and breach-threshold prediction are required together.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-09-14T12:36:55.045Z","isFirstParty":false}