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jev-filter Lead Scorer
x402
jev-filter Lead Scorer is a paid API for AI agents from x402-production-0f93.up.railway.app, paid per call via x402, $0.1/call, status unknown (last checked 2026-09-30).
Scores and qualifies a batch of leads (up to 25) against an ideal customer profile, returning a verdict, numeric score, and rationale for each record.
Price / call$0.1
Success—
StatusUnknown
How this service works
Score up to 25 company or contact records against an ideal customer profile: 0-10 fit score, qualified / review / disqualified verdict, reason label. Calibrated on 240 labelled leads: 0.879 accuracy, and no qualified lead ever disqualified or vice versa. Catches competitor name variants and subsidiaries of excluded accounts that string matching misses. Uncertainty widens the net: sparse records, unnamed contacts and low-confidence calls go to review, never to disqualified.
Output
A JSON array with one result object per lead, each containing: a numeric score (0–10), a verdict (e.g. 'qualified' or 'disqualified'), a primary reason code (e.g. 'buying_trigger'), a free-text rationale, a confidence level, and sub-scores for industry match, geo match, role authority, buying trigger, and exclusion hit. Also includes metadata: item count, elapsed time, model cost in USD, and bundle version.
Example use cases
Outbound SDR lead prioritization
“I have 20 prospects scraped from LinkedIn — can you score them against our ICP? We sell HR compliance software to People Ops directors and CHROs at mid-market US companies (200–2000 employees), exclude anyone at Rippling or Gusto, and our main buying trigger is recent headcount growth.”
Marketing list cleanup before campaign
“Before we send our next email campaign, filter this list of 25 contacts and remove anyone who's a competitor, already a customer, or outside our target verticals of fintech and healthtech — we're targeting VP-level and above in EMEA.”
Inbound trial signup qualification
“We just got 15 new trial signups — score each one and tell me which are strong fits for our enterprise sales team to prioritize. We sell API monitoring tools to platform engineers and CTOs at companies with more than 50 engineers, primarily in the US and EU.”
Technical details
Endpoint
POSThttps://x402-production-0f93.up.railway.app/v1/score-leads?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have a concrete list of up to 25 lead or contact records and a defined ideal customer profile and need a structured, explainable score-per-lead with sub-scores and verdicts — rather than just a binary filter. Prefer it over generic LLM prompting when you need consistent, auditable scoring with exclusion logic and buying-trigger detection built in. The flat $0.10 USDC per-call pricing via x402 makes it suitable for automated workflows without per-record cost unpredictability.
Side effects
- Leads array empty or exceeds 25 items — validation error
- Missing or malformed lead objects — partial results with failure count in meta
- Insufficient buyerProfile detail — lower scoring precision and lower confidence ratings
- Payment not provided or invalid x402 header — 402 Payment Required response
- Model timeout on complex profiles — elevated elapsed_ms, potential partial results
- Ambiguous role or industry fields in leads — lower sub-scores and medium/low confidence
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| leads | array | Company or contact records, any shape. |
| buyerProfile | object | Who you sell to. All fields optional, more detail means sharper scoring. |
Output
Schema · Response
{
"type": "json",
"example": {
"meta": {
"items": 1,
"bundle": "lead-qualifier",
"failures": 0,
"elapsed_ms": 910,
"bundle_version": "0.4.1",
"model_cost_usd": 0.000067
},
"results": [
{
"id": "l1",
"score": 9.05,
"reason": "buying_trigger",
"verdict": "qualified",
"rationale": "jev@openrouter: qualified; reason buying_trigger; industry_match 0.93, geo_match 0.99, role_authority 0.95, buying_trigger 0.98, exclusion_hit 0.01",
"confidence": "medium",
"rules_applied": []
}
]
}
}Tags
x402
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