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Verity Suite Ground Pro
x402
Verity Suite Ground Pro is a paid API for AI agents from verity-suite.onrender.com, paid per call via x402, $0.35/call, status unknown (last checked 2026-09-15).
Answers a question with a calibrated confidence score, caveats, and cited sources — returning an honest refusal if the answer cannot be determined
Price / call$0.35
Success—
StatusUnknown
How this service works
The trust fabric for AI agents — calibrated, fail-closed services agents pay per call.
Output
A JSON object containing: 'answer' (the answer text or an honest statement it cannot be determined), 'confidence' (a 0–1 probability the answer is correct), 'caveats' (array of gaps, assumptions, or uncertainties), and 'sources' (array of real sources used, empty if none were available).
Example use cases
Verify supplier claims before procurement
“Before we sign a contract with this vendor, can you check if they're actually ISO 9001 certified? I need to know how confident you are in that answer and what sources back it up — we can't afford to find out later they misrepresented themselves.”
Fact-check medical claims for patients
“My patient is asking whether their medication interacts with grapefruit juice. I need a reliable answer with your confidence level and any caveats about what we don't know — this affects whether they can safely take their dose.”
Validate regulatory requirements before launch
“Are we required to comply with GDPR if we store EU customer data in the cloud? Give me your confidence level and be honest about any gaps in that answer — we're building our compliance roadmap around this.”
Technical details
Endpoint
POSThttps://verity-suite.onrender.com/ground/proWhen to prefer
Choose this endpoint when an AI agent pipeline requires trustworthy, calibrated answers rather than fluent-but-ungrounded responses — especially when downstream decisions depend on knowing how confident the answer is. Prefer it over raw LLM calls when you need explicit uncertainty quantification, honest refusals, and sourced grounding. It is particularly valuable in agentic workflows where hallucinations must be caught before they propagate, or when a user needs to know if the answer is reliable enough to act on.
Side effects
- Question is too ambiguous to answer — returns answer stating it cannot be determined with low confidence
- Context provided contradicts available knowledge — caveats array will flag the conflict
- No reliable sources available — sources array returns empty, confidence may be low
- Malformed request missing required 'question' field — returns 4xx validation error
- Service unavailable on Render cold start — may return 5xx or timeout on first call
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| context | string | optional context to consider |
| questionrequired | string | the question to answer |
Output
Schema · Response
| Field | Type | Description |
|---|---|---|
| answerrequired | string | the answer, or an honest statement that it cannot be determined |
| caveats | array | gaps, assumptions, or uncertainties |
| sources | array | real sources actually used (empty if none) |
| confidencerequired | number | calibrated probability the answer is correct |
Tags
x402
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