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Claim Grounding Deep Research
x402
Claim Grounding Deep Research is a paid API for AI agents from claim-grounding.prospectintel.workers.dev, paid per call via x402, $8/call, status unknown (last checked 2026-10-17).
Checks factual claims in text against Wikipedia, Wikidata, Google News, Europe PMC, FRED, and SEC EDGAR and returns a verdict on each claim's accuracy
Price / call$8
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 Every checked claim returns verdict: supported | contradicted | outdated | mixed | insufficient_evidence, plus status_detail and legacy_verdict (pre-1.2.0 value: supported | contradicted | not_found | conflict).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
Returns a job receipt with a job_id and poll URL for async retrieval. Each claim in the input gets a claim_id, a verdict from the set (supported, contradicted, outdated, mixed, insufficient_evidence), a status_detail explanation, and a legacy_verdict for backward compatibility. The receipt also includes creation timestamp and the price charged in USD.
Example use cases
AI hallucination audit before publishing
“I just got a response from my AI assistant summarizing our competitor's recent SEC filings. Can you run a deep fact-check on it and flag any claims that are contradicted or not backed by evidence before I send it to my team?”
Medical research claim verification
“My draft blog post says 'ivermectin has been shown in clinical trials to significantly reduce COVID-19 mortality.' Can you check that claim against PubMed and tell me if it's supported, contradicted, or if the evidence is mixed?”
Financial data claim grounding
“Our analyst wrote that 'US inflation peaked at 9.1% in June 2022 and has been declining steadily since.' Can you verify that against FRED data and let me know if it checks out or if there's anything outdated or incorrect?”
Technical details
Endpoint
POSThttps://claim-grounding.prospectintel.workers.dev/v1/deep_research?utm_source=zero.xyzWhen to prefer
Choose this endpoint when an AI agent needs to verify factual accuracy of specific claims against authoritative sources including Wikipedia, academic literature (PubMed), financial data (FRED), and SEC filings — especially when fine-grained verdicts (supported/contradicted/outdated/mixed/insufficient_evidence) are needed. Prefer this over generic web search when you need a structured, per-claim verdict rather than raw search results. Ideal for auditing LLM outputs, validating research summaries, or grounding agent-generated answers before they are shown to end users. The $8/call pricing makes it best suited for high-stakes fact checks rather than high-volume trivial lookups.
Side effects
- 400 error if confirmed:true is not included in the request body — nothing is charged
- Insufficient evidence verdict when sources don't cover the claim's subject
- Outdated verdict for time-sensitive claims where sources have newer information
- Mixed verdict when sources disagree on the claim
- Long polling delay if the job queue is busy — client must poll the job URL returned in response
- Claims about very niche topics may return insufficient_evidence due to limited source coverage
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": 8
},
"next_actions": []
}
}Tags
x402
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