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Verity Suite – Ground Quick (Calibrated Q&A)
x402
Verity Suite – Ground Quick (Calibrated Q&A) is a paid API for AI agents from suite.veritylayer.dev, paid per call via x402, $0.03/call, status unknown (last checked 2026-09-14).
Answers a question with a calibrated confidence score, cited sources, caveats, and an optional Ed25519-signed receipt for auditability
Price / call$0.03
Success—
StatusUnknown
How this service works
The trust fabric for AI agents — calibrated, fail-closed services agents pay per call.
Output
Returns a structured object containing: a plain-language answer (or honest statement that the answer cannot be determined), a calibrated confidence score between 0 and 1, an array of actual sources used, an array of caveats (gaps, assumptions, uncertainties), and an optional Ed25519-signed VerityLayer receipt for independent verification.
Example use cases
Fact-check claim before publishing
“Before we publish this article, ground-check this claim for me: 'The Eiffel Tower is taller than the Statue of Liberty including its pedestal.' Give me a confidence score and any caveats or sources.”
Agent self-verification in pipeline
“My agent just stated that 'lithium-ion batteries were first commercialized by Sony in 1991' — can you run that through the grounding service and tell me how confident it is and whether there are any gaps or uncertainties I should know about?”
Research assistant due diligence
“I'm writing a report and need to verify this: 'The global EV market surpassed 10 million annual sales for the first time in 2022.' Give me a calibrated probability it's correct, the sources used, and flag any assumptions.”
Technical details
Endpoint
POSThttps://suite.veritylayer.dev/ground/quickWhen to prefer
Choose this endpoint when your agent needs a calibrated, auditable answer rather than a raw LLM response — especially when accuracy confidence matters, when you need cited sources, when downstream decisions depend on knowing uncertainty, or when you require a cryptographically signed receipt for auditability. Prefer it over generic LLM calls when fail-closed behavior (honest 'I don't know') is more valuable than confident-sounding but potentially hallucinated output.
Side effects
- Missing required 'question' field returns a validation error
- Question exceeds 2000 character limit causes rejection
- Context exceeds 2000 character limit causes rejection
- Insufficient confidence in answer yields a low score with explicit 'cannot be determined' answer rather than a hallucinated response
- Receipt is null if signing is not configured on the server side
- Payment failure (HTTP 402) if USDC micropayment is not correctly attached
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| context | — | optional context to consider |
| question | string | the question to answer |
Tags
x402
Reviews
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