# AR Analyzer – Days Sales Outstanding

> 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

## Facts

- Endpoint: POST https://ar-analyzer.rileycraig14.workers.dev/ar/dso
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/ar-analyzer-days-sales-outstanding-f407c869
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_QxGQOS1GHY9Kq7oFlq5dr

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability ar-analyzer-days-sales-outstanding-f407c869 -d '<json body>'
```

Example prompt: Calculate my DSO and AR aging buckets — I have $480,000 in credit sales and a $192,000 receivables balance over a 90-day period, and I need to know how I benchmark plus which accounts to prioritize for collections.

## When to prefer this

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.

## Known failure modes

- 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

## 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.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "required": [
  "credit_sales",
  "receivables_balance"
 ],
 "properties": {
  "monthly": {
   "type": "array"
  },
  "period_days": {
   "type": "integer"
  },
  "credit_sales": {
   "type": "number"
  },
  "receivables_balance": {
   "type": "number"
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "dso": 36,
 "read": "Collection is inside the 30-45 day band most B2B terms imply.",
 "benchmark": "typical",
 "period_days": 90
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/ar-analyzer-days-sales-outstanding-f407c869/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from ar-analyzer.rileycraig14.workers.dev](https://www.zero.xyz/host/ar-analyzer.rileycraig14.workers.dev/llms.txt)