Templates/PropTech & Real Estate/Tenant-screening risk classifier
Tenant-screening risk classifier
Tri-state approve / conditional / decline verdict per applicant. Always-human reviewer-gate on declines for Fair Housing + ECOA adverse-action-notice evidence.
What this template is
Pattern: classifier producing tri-state rental-decision recommendation. Always-human reviewer-gate on decline ensures human review before any adverse-action notice is sent. Closed-enum reason-codes (from the ECOA adverse-action list) prevent free-text drift on the regulator-sensitive output. Hash-only redaction on applicant identifiers means no PII in the chain. Each L12 entry feeds Fair Housing disparate-impact analyses + ECOA adverse-action evidence.
The template
TypeScript · BSL-1.1 · License
import { RuntimeAISpec } from '@promethean/runtime-ai';
export const tenantScreenerSpec: RuntimeAISpec = {
specId: 'tenant-screener-v1',
displayName: 'Tenant-screening risk classifier',
description:
'Tri-state rental-decision recommendation with closed-enum adverse-action reasons.',
category: 'classifier',
schemaVersion: 'promethean-runtime-ai-spec-1.0',
canonicalForm: 'v1',
inputSchema: {
fields: [
{ name: 'applicationId', type: 'string', required: true,
redaction: 'hash-only' },
{ name: 'propertyId', type: 'string', required: true },
// Applicant identifiers are PII; never raw.
{ name: 'applicantContextHash', type: 'string', required: true,
redaction: 'hash-only' },
{ name: 'creditScoreBand', type: 'enum', required: true,
enumValues: ['below-600', '600-649', '650-699', '700-749', '750-plus'] },
{ name: 'incomeToRentRatio', type: 'number', required: true,
min: 0, max: 100 },
],
},
outputSchema: {
fields: [
{ name: 'recommendation', type: 'enum', required: true,
enumValues: ['approve', 'conditional', 'decline'] },
{ name: 'adverseActionReasons', type: 'string-list', required: false,
maxItems: 4, maxLength: 80 },
{ name: 'confidence', type: 'number', required: true,
min: 0, max: 1 },
],
},
promptTemplate: {
system:
'You score tenant-screening applications against the property profile. ' +
'Recommend approve / conditional / decline. ' +
'When decline, include adverse-action reason codes per ECOA. ' +
'Do not infer protected-class characteristics. ' +
'A human reviewer signs every decline before the adverse-action notice is sent.',
user:
'Application {{applicationId}} for property {{propertyId}}. ' +
'Credit-score band: {{creditScoreBand}}. ' +
'Income-to-rent ratio: {{incomeToRentRatio}}.',
},
modelIdentity: {
provider: 'anthropic',
model: 'claude-sonnet-4-5',
version: '20250929',
},
reviewerGate: 'always-human',
maxLatencyMs: 4000,
fallbackBehavior: 'queue-for-review',
};
Regulations addressed
This template's configuration choices map to specific regulatory obligations. The substrate doesn't certify compliance — but the spec hash + reviewer-verdict + modelIdentity per L12 entry give you the evidence layer for these citations:
- ·EU AI Act Annex III §5(b) — creditworthiness (when credit-based)
- ·US Fair Housing Act
- ·HUD Discriminatory Effects Standard (24 CFR §100.500)
- ·ECOA — adverse-action notices
Installation + usage
- Create a free Dev-tier workspace — API key + Ed25519 signing key issued instantly.
- Install the SDK:
npm install https://promethean.software/runtime-ai/latest.tgz. - Paste the template above into your codebase. Adjust
modelIdentity+ prompt for your context. - Call
runConstrainedAI(spec, input, { client, receiptLogPath, productId, signingKey })from your service code. For local testing passcreateMockRuntimeAIClient(spec); for production, an Anthropic / OpenAI / Azure adapter. - Verify the chain with the Apache-2.0 verifier.