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FoundryNet Inference
x402
FoundryNet Inference is a paid API for AI agents from foundrynet-inference-production.up.railway.app, paid per call via x402, $0.02/call, status unknown (last checked 2026-09-14).
LLM inference proxy with data-enriched analysis and predictive intelligence, backed by 17 data sources, with MINT-attested outputs gated via x402 micropayments
Price / call$0.02
Success—
StatusUnknown
How this service works
LLM inference proxy + data-enriched analysis + predictive intelligence. 17 data sources. MINT-attested outputs. x402-gated (Solana/Base USDC); an fnet_ Forge key bypasses.
Output
A chat completion response generated by the configured LLM, enriched with insights from up to 17 external data sources, accompanied by a MINT attestation that cryptographically verifies the output's provenance and integrity.
Example use cases
Verify AI-generated investment research authenticity
“Have FoundryNet Inference analyze this tech stock's growth potential using real-time market data and financial sources, then give me the MINT attestation so I can prove to my compliance team this analysis came from verified sources.”
Get trusted AI predictions for supply chain risks
“Ask FoundryNet Inference to assess potential disruption factors for our semiconductor supply chain by combining market intelligence, geopolitical data, and logistics information — I need the attested output so our board knows this forecast is data-grounded and trustworthy.”
Generate verified AI insights for regulatory filings
“Have FoundryNet Inference synthesize current regulatory trends and competitive landscape data into a market analysis summary with MINT attestation, so we can include it in our SEC filing with proof of its verifiable provenance.”
Technical details
Endpoint
POSThttps://foundrynet-inference-production.up.railway.app/v1/chatWhen to prefer
Choose FoundryNet Inference when you need LLM completions that go beyond a single model's training data by pulling from 17 live data sources, and when output attestation (MINT) is required for auditability or trust. Prefer this over bare LLM APIs when you need enriched, verifiable, predictive intelligence rather than raw text generation. Useful in agentic pipelines where downstream systems need to verify that an AI response was legitimately produced and data-grounded.
Side effects
- 402 Payment Required if no valid x402 payment or fnet_ Forge key is provided
- 400 Bad Request if the messages array is missing or malformed
- Invalid model name results in model-not-found error
- Upstream LLM provider unavailability causes 503 or timeout
- Rate limiting or quota exceeded on data enrichment sources returns partial or degraded response
- max_tokens set too low may truncate the response mid-generation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| model | string | LLM model to use |
| system | string | Optional system prompt |
| messagesrequired | array | Chat messages array |
| max_tokens | integer | Optional max output tokens |
Tags
x402
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