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AR Analyzer – Days Sales Outstanding
x402
AR Analyzer – Days Sales Outstanding is a paid API for AI agents from ar-analyzer.rileycraig14.workers.dev, paid per call via x402, $0.01/call, status unknown (last checked 2026-09-15).
Computes Days Sales Outstanding (DSO) with benchmark bands, aging bucket breakdowns, overdue totals, and a ranked collections call list from accounts-receivable data
Price / call$0.01
Success—
StatusUnknown
How this service works
Deterministic accounts-receivable analysis for AI agents running back-offices: aging buckets (0-30/31-60/61-90/90+), seriously-overdue totals under the strictly-greater-than-60-days rule, Days Sales Outstanding with benchmark bands and trend, and collections triage with a ranked call list and an explicit recovery-decay curve. Exact arithmetic, every rule stated in the response, nothing stochastic.
Output
Returns a DSO figure in days, a plain-English benchmark read (e.g. 'inside the 30–45 day band'), the benchmark band label (typical/fast/slow), aging bucket totals, seriously-overdue amounts using the strictly-greater-than-60-days rule, a ranked collections call list, and a recovery-decay curve — all computed with exact arithmetic and every rule stated explicitly in the response.
Example use cases
Monthly AR health check for CFO
“Run an AR analysis for last month: we had $1,200,000 in credit sales, $320,000 in receivables balance, and the period was 30 days — give me DSO, how it benchmarks, and flag anything seriously overdue.”
Collections triage before quarter close
“I need to know which accounts to call first for collections — plug in $750,000 credit sales, $280,000 AR balance over 90 days and give me the ranked call list and recovery-decay curve.”
AR aging breakdown for investor report
“Generate a full AR aging breakdown with 0-30, 31-60, 61-90, and 90-plus day buckets — credit sales are $2,000,000, receivables are $600,000, period is 90 days.”
Technical details
Endpoint
POSThttps://ar-analyzer.rileycraig14.workers.dev/ar/dsoWhen to prefer
Choose this endpoint when you need deterministic, rule-explicit AR analysis — especially DSO benchmarking, aging bucket breakdowns, and prioritized collections triage — without any stochastic or AI-generated guesswork. Ideal for back-office AI agents that must show auditable arithmetic and comply with strict greater-than-60-days overdue definitions. Prefer over general-purpose finance LLMs when reproducibility and exact rule citation in the response are required.
Side effects
- Missing required fields (credit_sales or receivables_balance) returns a validation error
- Zero or negative credit_sales causes a division error or invalid DSO
- Malformed monthly array entries may be ignored or cause a parsing error
- Period_days defaulting to an unexpected value if omitted may skew DSO calculation
- Network or worker timeout if the Cloudflare Worker is unavailable
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| monthly | array | |
| period_days | integer | |
| credit_salesrequired | number | |
| receivables_balancerequired | number |
Output
Schema · Response
{
"dso": 36,
"read": "Collection is inside the 30-45 day band most B2B terms imply.",
"benchmark": "typical",
"period_days": 90
}Tags
x402
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