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Rental Comps Analysis API
x402
Rental Comps Analysis API is a paid API for AI agents from 192.3.171.233, paid per call via x402, $0.05/call, status unknown (last checked 2026-09-15).
Analyzes caller-supplied rental observations against a target property, scoring comparables and returning a weighted rent estimate with confidence band, market benchmarks, and evidence provenance.
Price / call$0.05
Success—
StatusUnknown
How this service works
An x402-paid API suite for autonomous agents. The freight operation preserves deterministic U.S. DOT/FMCSA carrier checks. A self-contained rental market snapshot returns available public rent benchmarks, trends, provenance, and optional budget fit from a ZIP code and bedroom count. Other rental operations normalize, deduplicate, search, compare, and analyze rental observations supplied by a caller who is authorized to process them. Zillow Research ZORI, U.S. Census ZCTA geography, and HUD Fair Market Rent data are not represented as unit-level listings or executed lease rents. Unsigned requests receive the x402 challenge before validation. Credential-bearing retries that are invalid or cannot produce the advertised minimum result are rejected before payment verification and settlement and are not charged.
Output
Returns a structured comp run result including: a weighted rent point estimate and plausible range, a confidence band (HIGH/MEDIUM/LOW) with score and method, scored and ranked comparable observations, area-level market context (ZORI typical rent, 1/3/12-month change percentages, HUD Fair Market Rents by bedroom count), a full evidence chain with content hashes and attribution, and any data quality warnings. Also echoes the target property details and a unique comp run ID.
Example use cases
Price a new listing before posting
“I'm about to list a 2-bed 1-bath apartment in ZIP 78701. Can you run comps against these 8 candidate observations I have and tell me where my asking rent should land, with a confidence score and any market benchmark context?”
Validate landlord's asking rent
“My landlord wants $2,400/month for a 1-bedroom in Austin 78701. I've pulled together some comparable listings — can you score them against the unit and tell me whether that price is in the plausible range, with ZORI and HUD context?”
Property manager portfolio pricing audit
“For each of these 5 target units across Austin, I have candidate comp observations for each one — can you run a comp analysis on all of them and flag which ones have a MEDIUM or LOW confidence score so I know where to dig deeper?”
Technical details
Endpoint
POSThttps://192.3.171.233/v1/rentals/compsWhen to prefer
Choose this endpoint when you have caller-supplied rental observations you are authorized to process and need a structured, evidence-backed rent estimate with confidence scoring and market benchmark context for a specific U.S. target property. It is ideal for property managers, pricing agents, and tenant advisors who need a defensible comp run with full provenance rather than a simple ZIP-level market snapshot. Prefer this over the market snapshot endpoint when you have proprietary or curated comparable observations to contribute. Prefer it over manual analysis when you need machine-readable confidence bands, HUD/ZORI benchmark overlays, and a content-hashed audit trail.
Side effects
- Unsigned or missing x402 payment header returns 402 challenge before validation
- Invalid credentials or inability to produce minimum advertised result rejected before payment and not charged
- Insufficient or unresolvable candidate observations may lower confidence band to LOW or return no estimate
- Target property address not geocodable returns validation error
- Policy object with conflicting or unsupported parameters may cause rejection
- Candidate observations missing required fields result in filtering or rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| policy | object | |
| target | object | |
| candidates | array |
Output
Schema · Response
{
"type": "json",
"example": {
"market": {
"evidence": [
{
"id": "ev_zori",
"dataset": "Zillow Observed Rent Index (ZORI)",
"sourceId": "zillow-research",
"sourceUrl": "https://rentals.example/listings/AUS-1200-12A",
"fieldPaths": [
"/typicalRentCents"
],
"observedAt": "2026-08-23T16:00:00Z",
"attribution": "Caller-authorized property manager feed",
"contentHash": "sha256:ccdbf127d9e36d25f3c0e535a3cb4280c7b67117399e6fe42a41a914f1c9087a",
"retrievedAt": "2026-08-24T12:05:00Z"
}
],
"latitude": 30.2713,
"warnings": [
"Market benchmarks are area-level context and are not substitutes for property-level comparables."
],
"longitude": -97.7426,
"postalCode": "78701",
"generatedAt": "2026-08-24T12:00:00Z",
"hudAreaCode": "METRO12420M12420",
"hudAreaName": "Austin-Round Rock-Georgetown, TX HUD Metro FMR Area",
"sourceCount": 2,
"datasetVersion": "rental-ds-2026-08-24-6af7130e",
"change1MonthPct": 0.3,
"change3MonthPct": 1.1,
"typicalRentAsOf": "2026-07",
"change12MonthPct": -0.8,
"typicalRentCents": 229400,
"hudFairMarketRentsCents": {
"0": 143000,
"1": 160000,
"2": 195000,
"3": 254000
}
},
"target": {
"address": {
"city": "Austin",
"unit": "901",
"line1": "600 Guadalupe St",
"state": "TX",
"postalCode": "78701"
},
"bedrooms": 2,
"latitude": 30.2704,
"bathrooms": 2,
"longitude": -97.7462,
"squareFeet": 1020,
"propertyType": "MULTIFAMILY"
},
"evidence": [
{
"id": "ev_listing_1",
"dataset": "Rental listing observation",
"sourceId": "property-manager-feed",
"sourceUrl": "https://rentals.example/listings/AUS-1200-12A",
"fieldPaths": [
"/comparables/0"
],
"observedAt": "2026-08-23T16:00:00Z",
"attribution": "Caller-authorized property manager feed",
"contentHash": "sha256:ccdbf127d9e36d25f3c0e535a3cb4280c7b67117399e6fe42a41a914f1c9087a",
"retrievedAt": "2026-08-24T12:05:00Z"
}
],
"warnings": [
"The estimate uses asking-rent observations, not executed lease rents.",
"The plausible range is a weighted interquartile range, not a statistical confidence interval."
],
"compRunId": "cmp_a017cab11f737b2fc633",
"confidence": {
"band": "MEDIUM",
"score": 78,
"method": "HEURISTIC_V1_UNCALIBRATED",
"factors": [
{
"name": "effectiveSampleSize",
"score": 0.74,
"weight": 0.3
},
{
"name": "similarity",
"score": 0.91,
"weight": 0.25
},
{
"name": "freshness",
"score": 0.88,
"weight": 0.2
},
{
"name": "targetCompleteness",
"score": 1,
"weight": 0.15
},
{
"name": "dataQuality",
"score": 0.92,
"weight": 0.1
}
],
"methodologyVersion": "rental-intelligence-v1.0"
},
"comparables": [
{
"weight": 0.86,
"ageDays": 1.83,
"listing": {
"address": {
"city": "AUSTIN",
"unit": "12A",
"line1": "1200 CONGRESS AVE",
"state": "TX",
"postalCode": "78701"
},
"sources": [
"property-manager-feed"
],
"bedrooms": 2,
"latitude": 30.2752,
"amenities": [
"IN_UNIT_LAUNDRY",
"PARKING"
],
"bathrooms": 2,
"furnished": false,
"listingId": "lst_8c896d29ce93b5f421f4",
"longitude": -97.7426,
"petPolicy": "PETS_ALLOWED",
"matchScore": 0,
"observedAt": "2026-08-23T16:00:00Z",
"propertyId": "prp_79dd77a282d20d5f2860",
"squareFeet": 1040,
"listingKind": "LONG_TERM",
"reasonCodes": [
"NORMALIZED_AND_DEDUPLICATED"
],
"evidenceRefs": [
"ev_listing_1"
],
"propertyType": "MULTIFAMILY",
"baseRentCents": 210000,
"duplicateCount": 2,
"dataQualityFlags": [],
"dataQualityScore": 94,
"totalMonthlyCostCents": 222500,
"marketDifferencePercent": -3.4,
"pricePerSquareFootCents": 214,
"effectiveMonthlyRentCents": 206390,
"mandatoryMonthlyFeesCents": 12500
},
"distanceMiles": 0.62,
"similarityScore": 0.94,
"adjustmentReasonCodes": [
"SIZE_ADJUSTED",
"BATHROOM_ADJUSTED"
],
"adjustedMonthlyCostCents": 218500
}
],
"generatedAt": "2026-08-24T12:05:00Z",
"schemaVersion": "1.0",
"selectedCount": 3,
"candidateCount": 3,
"datasetVersion": "rental-ds-2026-08-24-6af7130e",
"plausibleRange": {
"method": "WEIGHTED_P25_P75",
"lowCents": 212000,
"highCents": 231000
},
"excludedByReason": {
"OUTSIDE_RADIUS": 0,
"DUPLICATE_OBSERVATION": 1
},
"estimatedRentCents": 222000,
"methodologyVersion": "rental-intelligence-v1.0",
"effectiveSampleSize": 2.73
}
}Tags
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