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Claim Grounding Pro Deep Research
x402
Claim Grounding Pro Deep Research is a paid API for AI agents from claim-grounding.prospectintel.workers.dev, paid per call via x402, $15/call, status unknown (last checked 2026-10-17).
Verifies factual claims in text against authoritative sources (Wikipedia, Wikidata, Google News, Europe PMC, FRED, SEC EDGAR) and returns a structured verdict per claim
Price / call$15
Success—
StatusUnknown
How this service works
Pay-per-call claim checks for AI agents. Sources: Wikipedia, Wikidata, Google News, Europe PMC (PubMed), FRED and SEC EDGAR. USDC on Base via x402 (Coinbase CDP facilitator). No API key. Every checked claim returns verdict: supported | contradicted | outdated | mixed | insufficient_evidence, plus status_detail and legacy_verdict (pre-1.2.0 value: supported | contradicted | not_found | conflict).
Output
An async job object with a job_id and a polling URL for the full result. The receipt includes each parsed claim with its claim_id and grounding_required flag, priced_usd ($15), and created_at timestamp. When polled, each claim resolves to a verdict (supported, contradicted, outdated, mixed, or insufficient_evidence), a status_detail explanation, and a legacy_verdict for backward compatibility.
Example use cases
Grounding AI-generated medical summaries
“Before I send this patient FAQ to the clinic, verify the claim 'Metformin reduces cardiovascular risk in type 2 diabetics' against PubMed and Wikipedia — is it supported, contradicted, or is the evidence mixed?”
Validating financial assertions in reports
“I'm reviewing an investment memo that says 'US CPI peaked at 9.1% in June 2022.' Can you fact-check that claim against FRED and tell me the verdict with supporting detail?”
Checking news-based claims before publishing
“Our AI wrote that 'the EU passed the AI Act in March 2024.' Before we publish, can you ground that claim against Google News and Wikipedia and tell me if it's accurate or outdated?”
Technical details
Endpoint
POSThttps://claim-grounding.prospectintel.workers.dev/v1/deep_research/pro?utm_source=zero.xyzWhen to prefer
Choose this endpoint when an AI agent needs authoritative, multi-source fact verification covering biomedical (PubMed), financial (FRED, SEC EDGAR), encyclopedic (Wikipedia, Wikidata), and news (Google News) domains in a single call. It is especially valuable for grounding LLM-generated text before publication, auditing research summaries, or flagging hallucinations. Prefer it over generic web search when you need a structured, machine-readable verdict with source provenance rather than raw search results.
Side effects
- Returns 400 if confirmed: true is missing from the request body — nothing is charged
- Insufficient evidence verdict when no authoritative source addresses the claim
- Outdated verdict if claim was once true but sources reflect changed facts
- Mixed verdict when sources conflict with each other
- Polling may be needed if status is 'queued' — results are not always synchronous
- Malformed or ambiguous claim text may produce low-confidence or insufficient_evidence results
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| text | string | |
| claim | object | |
| answer | string | Text whose claims should be researched. |
| claim_ids | array | |
| confirmed | — | Required. Without confirmed: true the call returns 400 and nothing is charged. |
Output
Schema · Response
{
"type": "json",
"example": {
"mode": "fast",
"poll": "GET /v1/jobs/job_8c1d2e3f4a5b6c7d (free)",
"claims": [],
"job_id": "job_8c1d2e3f4a5b6c7d",
"status": "queued",
"receipt": {
"claims": [
{
"text": "Paris is the capital of France",
"claim_id": "clm_3f9a1c2b4d5e6f70",
"grounding_required": true
}
],
"job_id": "job_8c1d2e3f4a5b6c7d",
"created_at": "2026-10-10T12:00:00.000Z",
"priced_usd": 15
},
"next_actions": []
}
}Tags
x402
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