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KARP by SoulDriver – Multi-Model Research Cards
x402
KARP by SoulDriver – Multi-Model Research Cards is a paid API for AI agents from agents.souldriver.com.au, paid per call via x402, $0.03/call, status unknown (last checked 2026-10-31).
Returns AI research cards synthesized by four models (GPT, Gemini, Grok, Claude) debating a topic, each card containing a conclusion, key insight, warnings, dated figures, consensus status, and open questions.
Price / call$0.03
Success—
StatusUnknown
How this service works
Research cards from KARP, SoulDriver's multi-model research engine: GPT, Gemini, Grok and Claude debate a question and publish a conclusion. Each card: conclusion, key insight, warnings, dated figures, consensus, open questions, research date. Check your question first with the free POST /v1/coverage. Deepest on Alzheimer's, ageing biology, ancient scripts, AI governance, quantum computing. No wallet? Free research grant: POST /v1/grant. Usually 5-15 s.
Output
A JSON object containing an array of research cards, each with: a ranked conclusion synthesized from multi-model debate, a key insight, warnings about limitations or outdated data, dated anchor figures with as-of dates, an age-in-days and staleness flag, open questions, a relevance score, a session ID, and the topic string. Also includes top-level relevance score and a list of related research topics with their session IDs.
Example use cases
Regulatory briefing before a board meeting
“I need a quick research brief on EU AI Act enforcement in 2025 — pull 5 KARP cards so I can see what multiple AI models have concluded, including any warnings about stale figures.”
Investment thesis background research
“I'm evaluating a position in solid-state battery companies — can you get me up to 8 KARP research cards on the latest commercial developments, key insights, and open questions in that space?”
Journalist fact-gathering on a policy topic
“I'm writing a piece on Australia's national housing affordability crisis — fetch me 4 KARP cards summarizing what the major AI models have concluded, including any dated figures and unresolved questions.”
Technical details
Endpoint
POSThttps://agents.souldriver.com.au/v1/ask?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a synthesized, multi-model research consensus on a topic rather than a single-model answer. It is especially valuable for policy, science, finance, or geopolitical topics where cross-model debate adds credibility. Prefer it over a simple web search when you want structured conclusions with explicit uncertainty flags, dated figures, staleness indicators, and open questions surfaced automatically. Use POST /v1/coverage first if unsure whether the topic is indexed.
Side effects
- Query too vague or outside covered topics — low relevance scores or empty cards array
- max_cards out of range (must be 1–8) — validation error
- Topic not yet researched by KARP — coverage miss, recommend checking POST /v1/coverage first
- Stale cards returned for rapidly evolving topics — staleness flag will be true
- Network timeout given ~15s processing time — retry recommended
- Payment failure via x402 protocol — 402 response with payment details
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| query | string | The question you are researching, in plain words. A specific question finds closer matches than a single keyword. |
| intent | string | Optional: what you or your user are trying to find out, and what it is for (max 300 characters). Kept private; it helps decide what KARP researches next. |
| max_cards | integer | Research cards to return |
Output
Schema · Response
{
"type": "json",
"example": {
"cards": [
{
"date": "2026-04-06",
"rank": 1,
"stale": true,
"topic": "AI governance 2026: latest regulatory developments, EU AI Act enforcement updates, and Australia's AI safety framework progress",
"anchors": [
{
"as_of": "2026-04-07",
"label": "ISO 42001 Certification Cost",
"value": "$85,000 - $650,000"
}
],
"age_days": 193,
"warnings": [
"Agentic AI may operate outside existing legal frameworks."
],
"relevance": 0.994,
"conclusion": "A bifurcated global landscape: the EU has paused high-risk enforcement pending harmonised standards, while Australia enforces AI obligations through existing privacy law.",
"session_id": "karp_1775506768",
"key_insight": "The 40% grey zone in high-risk AI categorisation reflects a failure of categorical logic, not just technical standards.",
"open_questions": [
"How will legal frameworks adapt to agentic AI systems?"
]
}
],
"query": "AI governance in 2026",
"top_relevance": 0.994,
"related_research": [
{
"date": "2026-04-10",
"topic": "Timeline of the US federal-state AI regulatory collision",
"session_id": "karp_1775819207"
}
]
}
}Tags
x402
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