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AgentUtility Research Brief
x402
AgentUtility Research Brief is a paid API for AI agents from x402.agentutility.ai, paid per call via x402, $0.1/call, status unknown (last checked 2026-09-14).
Generates a structured JSON research brief (overview, key facts, recent news with citations) on any company, person, product, or topic using live web search and LLM synthesis.
Price / call$0.1
Success—
StatusUnknown
How this service works
Builds a structured research brief on a company, person, product, or topic as fixed-shape JSON: overview, key_facts, recent_news (with date hints), all with source-index citations. Combines Decodo Google SERP + parallel cheerio scrape (up to 8 sources) + Morpheus llama-3.3-70b with json_schema response_format. Use it for company briefs, entity profiles, topic briefs, sales-prep dossiers, due-diligence summaries, competitive intel, or agent-readable research.
Output
A fixed-shape JSON object containing: an 'overview' narrative paragraph, a 'key_facts' array of factual bullet points, and a 'recent_news' array of news items each with a date hint and source-index citation. All claims are attributed to one of up to 8 scraped web sources included in the response.
Example use cases
Sales call prep on a prospect
“I have a call with a potential client, Databricks, tomorrow — can you build me a research brief with their overview, key facts, and recent news so I'm fully prepped?”
Due diligence summary on a startup
“We're considering investing in Mistral AI — put together a due-diligence research brief with an overview, key facts, and recent news items with source citations.”
Competitive intel on a rival product
“I need a competitive intelligence brief on Notion — summarize what they are, key facts about their product and business, and any recent news, with sources cited.”
Technical details
Endpoint
POSThttps://x402.agentutility.ai/research-briefWhen to prefer
Choose this endpoint when you need a structured, citation-backed research brief in a predictable JSON schema — ideal for agent pipelines that must parse and act on research output. Prefer it over raw search APIs when you want synthesis, not just links, and over general LLMs when you need live web data and source citations. Best for company profiles, sales prep, due diligence, or topic overviews where a fixed JSON shape (overview + key_facts + recent_news) is required.
Side effects
- Topic too obscure for SERP to return useful results — sparse or generic output
- Scraping blocked on some sources — fewer than 8 sources scraped, reduced citation coverage
- LLM hallucination risk on very recent or niche facts despite citations
- Rate limiting or x402 payment failure — 402 or 429 HTTP error
- Ambiguous entity name (e.g. 'Apple') may produce a mixed or unfocused brief
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"model": "llama-3.3-70b",
"sources": [
{
"url": "https://anthropic.com/",
"title": "...",
"domain": "anthropic.com",
"snippet": "..."
}
],
"overview": "Anthropic is an AI-safety research company that builds Claude...",
"key_facts": [
{
"fact": "Founded in 2021 by ex-OpenAI researchers",
"source_index": 0
}
],
"recent_news": [
{
"summary": "...",
"headline": "Claude 4.7 launches",
"date_hint": "2026-04",
"source_index": 1
}
],
"scraped_count": 5,
"entity_or_topic": "Anthropic"
}
}Tags
x402
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