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Verity Suite Ground — Calibrated Question Answering
x402
Verity Suite Ground — Calibrated Question Answering is a paid API for AI agents from verity-suite.onrender.com, paid per call via x402, $0.25/call, status unknown (last checked 2026-09-13).
Answers a question with a calibrated confidence score, caveats, and sources, designed for AI agents that need reliable, fail-closed factual grounding
Price / call$0.25
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 with: a direct answer (or an honest statement that the answer cannot be determined), a calibrated confidence score between 0 and 1 representing the probability the answer is correct, an optional list of caveats noting gaps or assumptions, and an optional list of actual sources used.
Example use cases
Fact-check medical claim with confidence
“I need you to fact-check this claim for me using a service that gives an honest confidence score and flags any caveats: 'Metformin is approved by the FDA as a first-line treatment for type 2 diabetes.' The answer will go into a patient-facing health summary, so I need sourced grounding and I'd rather get an honest 'uncertain' than a confident wrong answer.”
Verify legal precedent before brief
“Before I finalize this litigation brief, can you verify whether the Supreme Court ruling in Chevron U.S.A. v. Natural Resources Defense Council established the two-step deference doctrine for administrative agencies? I need a calibrated confidence score and any important caveats — if there's ambiguity or the answer can't be confirmed, say so explicitly rather than guessing.”
Ground financial data in due diligence
“We're running due diligence on an acquisition target and I need a reliable, sourced answer to this question: 'Was Silicon Valley Bank supervised by the Federal Reserve at the time of its March 2023 collapse?' Please use a grounding service that returns an explicit confidence level and notes any gaps or assumptions — this is going into an investor report so accuracy matters more than fluency.”
Technical details
Endpoint
POSThttps://verity-suite.onrender.com/groundWhen to prefer
Choose this endpoint when an AI agent needs a calibrated, uncertainty-aware answer to a factual question — especially in high-stakes or trust-sensitive workflows where overconfident or hallucinated answers are unacceptable. Prefer it over generic LLM completions when you need an explicit confidence score, structured caveats, and sourced grounding rather than a fluent but potentially fabricated response.
Side effects
- Missing required 'question' field returns a validation error
- Question is too ambiguous to answer confidently — returns low confidence score with honest uncertainty statement
- Sources list may be empty if no verifiable references were used
- Context field ignored if not relevant to the question
- Service may be unavailable on Render's free tier due to cold start or resource limits
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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