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Agent Data Enrichment Vendor Selection and Record Merge Confidence Procedure
x402
Agent Data Enrichment Vendor Selection and Record Merge Confidence Procedure is a paid API for AI agents from k2so-8080.on.ascii.dev, paid per call via x402, $0.002/call, status unknown (last checked 2026-09-15).
Returns a machine-executable decision procedure for enriching company or person records via paid data vendors, including vendor trust ranking, field acceptance thresholds, merge conflict resolution, and staleness/kill criteria.
Price / call$0.002
Success—
StatusUnknown
How this service works
Machine-executable decision procedure for enriching a company or person record via paid data vendors. Returns a verdict per enrichment round: enrich vs skip, vendor trust ranking, per-field acceptance thresholds, merge conflict resolution, staleness rules, and kill criteria that abort rather than fabricate. Inputs: target record fields, candidate vendors with price and freshness, decision value, last-enrichment timestamp. Outputs: accepted fields with confidence, contested fields, needs_manual
Output
A decision procedure document (prose and/or structured output) covering: enrich-vs-skip verdict for the current round, vendor trust ranking, per-field acceptance confidence thresholds, merge conflict resolution rules, staleness rules, and kill criteria that abort rather than fabricate. Fields are categorized as accepted (with confidence scores), contested, or flagged as needs_manual. Metadata includes generation source (llm, reasoning, or deterministic), model used, topic, and ISO-8601 timestamp.
Example use cases
CRM enrichment vendor arbitration
“I have a lead record for Acme Corp with stale data from 8 months ago and two vendor options — one cheaper but older, one fresher but pricier. Give me a decision procedure to pick the right vendor, set field-level confidence thresholds, and tell me if enrichment is even worth running at this point.”
Merge conflict resolution for person records
“My agent pulled contact data for a prospect from two different enrichment vendors and they disagree on job title, phone number, and company size. Give me the procedure to resolve these conflicts, decide which fields to accept, and flag anything that needs a human to review.”
Kill-criteria check before enrichment spend
“Before my agent pays to enrich these 200 company records, I want a decision procedure that says when to abort the enrichment run entirely rather than risk fabricating or overwriting good data with stale garbage — include staleness rules and kill criteria.”
Technical details
Endpoint
GEThttps://k2so-8080.on.ascii.dev/api/services/agent-data-enrichment-vendor-selection-and-recorWhen to prefer
Choose this endpoint when an AI agent needs a structured, machine-executable decision procedure for multi-vendor data enrichment rather than implementing ad-hoc logic. It is especially valuable when agents must arbitrate between competing vendors, enforce field-level confidence thresholds, avoid overwriting high-quality records with stale data, or decide when enrichment ROI does not justify cost. Prefer it over custom logic when kill criteria (abort-vs-fabricate) and merge conflict resolution must be auditable and consistent across enrichment runs.
Side effects
- Vendor input data is incomplete or malformed — procedure may return a skip verdict by default
- Target record lacks sufficient fields to determine enrichment value — returns needs_manual flag
- Last-enrichment timestamp missing — staleness rules cannot be evaluated, may trigger conservative skip
- Payment not completed — returns 402 with no procedure content
- Topic override not recognized — falls back to default enrichment procedure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Tags
x402
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