Commercial real estate

How to Build a Lease Abstraction API Integration (With Code Examples)

A developer guide to integrating a lease abstraction API into PropTech applications, lease management systems, and accounting platforms.

Lease abstraction APIs let PropTech platforms, lease management systems, and accounting software ingest lease documents and receive structured data without building their own AI extraction pipeline. This guide covers the integration patterns, data handling considerations, and common implementation challenges — using LeaseIQ's API as the reference implementation.

Integration Patterns

Three common integration patterns, depending on your use case:

Pattern 1: Synchronous extraction (small volume)

Upload a document, wait for the response. Works for individual lease uploads in a web application where a user is waiting for results. Typical response time: 10–60 seconds depending on document size and complexity. Appropriate for <50 leases/day.

Pattern 2: Asynchronous extraction with webhook (production)

Upload document, receive a job ID, get notified via webhook when extraction completes. Appropriate for production applications where you can't block on extraction time, or for bulk uploads. The recommended pattern for any serious integration.

Pattern 3: Batch processing (portfolio ingestion)

Submit a batch of documents in one API call, receive a batch job ID, poll or receive webhook notifications as each document completes. Appropriate for initial portfolio onboarding (100+ leases) where you want to process an entire portfolio overnight.

Basic Integration: Upload and Extract

1. Upload the lease document

// Node.js example
const FormData = require('form-data');
const fs = require('fs');

async function uploadLease(filePath) {
  const form = new FormData();
  form.append('document', fs.createReadStream(filePath));
  form.append('document_type', 'commercial_lease');
  form.append('output_schema', 'asc842'); // or 'ifrs16', 'full'

  const response = await fetch('https://api.leaseiq.io/v1/extract', {
    method: 'POST',
    headers: {
      'Authorization': `Bearer ${process.env.LEASEIQ_API_KEY}`,
      ...form.getHeaders(),
    },
    body: form,
  });

  return response.json();
  // Returns: { job_id: "job_abc123", status: "processing" }
}

2. Poll for results (synchronous pattern)

async function getExtractionResult(jobId) {
  const response = await fetch(
    `https://api.leaseiq.io/v1/jobs/${jobId}`,
    { headers: { 'Authorization': `Bearer ${process.env.LEASEIQ_API_KEY}` } }
  );
  const result = await response.json();

  if (result.status === 'complete') {
    return result.data; // Structured lease abstract
  } else if (result.status === 'processing') {
    await new Promise(r => setTimeout(r, 2000));
    return getExtractionResult(jobId); // Poll again
  } else {
    throw new Error(`Extraction failed: ${result.error}`);
  }
}

3. Handle the structured output

// Example response structure (ASC 842 schema)
{
  "lease_id": "lease_xyz789",
  "document_name": "123_main_st_office_lease.pdf",
  "extraction_confidence": 0.96,
  "parties": {
    "landlord": "Main Street Properties LLC",
    "tenant": "Acme Corp",
    "guarantor": null
  },
  "premises": {
    "address": "123 Main St, Suite 400, Phoenix, AZ 85001",
    "rsf": 12500,
    "usf": 10800,
    "floor": "4"
  },
  "term": {
    "commencement": "2022-03-01",
    "expiration": "2027-02-28",
    "rent_commencement": "2022-06-01",
    "lease_term_months": 60
  },
  "payments": {
    "schedule": [
      { "start": "2022-06-01", "end": "2023-05-31",
        "monthly": 31250, "annual": 375000 },
      { "start": "2023-06-01", "end": "2024-05-31",
        "monthly": 32188, "annual": 386250 }
      // ... continues through lease term
    ],
    "free_rent_months": 3,
    "ti_allowance": 125000
  },
  "options": [
    {
      "type": "renewal",
      "term_months": 60,
      "notice_months": 9,
      "rent_determination": "fair_market_value",
      "exercise_deadline": "2026-05-31"
    }
  ],
  "asc842_classification": {
    "classification": "operating",
    "criteria_met": [],
    "rou_asset_initial": 1284500,
    "lease_liability_initial": 1284500
  },
  "flags": [
    {
      "type": "amendment_detected",
      "message": "First Amendment dated 2023-01-15 modifies rent schedule",
      "severity": "review_required"
    }
  ]
}

Webhook Integration (Recommended)

// Register your webhook endpoint when submitting
const response = await fetch('https://api.leaseiq.io/v1/extract', {
  method: 'POST',
  headers: {
    'Authorization': `Bearer ${process.env.LEASEIQ_API_KEY}`,
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({
    document_url: 'https://your-storage.com/leases/lease123.pdf',
    document_type: 'commercial_lease',
    output_schema: 'full',
    webhook_url: 'https://your-app.com/webhooks/leaseiq',
    metadata: { internal_id: 'LEASE-2024-001' }
  }),
});

// Your webhook handler (Express example)
app.post('/webhooks/leaseiq', (req, res) => {
  const { job_id, status, data, metadata } = req.body;

  if (status === 'complete') {
    // Store structured abstract in your database
    await db.leases.update({
      where: { internal_id: metadata.internal_id },
      data: { abstract: data, abstracted_at: new Date() }
    });
  } else if (status === 'failed') {
    await notifyTeam(`Lease extraction failed: ${job_id}`);
  }

  res.sendStatus(200); // Always acknowledge
});

Handling Confidence Scores and Flags

Every field in the extracted output includes a confidence score. Fields with confidence below your threshold should be routed for human review, not automatically stored:

const CONFIDENCE_THRESHOLD = 0.90;

function processExtraction(data) {
  const flags = [];

  // Check field-level confidence
  for (const [field, value] of Object.entries(data.fields)) {
    if (value.confidence < CONFIDENCE_THRESHOLD) {
      flags.push({
        field,
        extracted_value: value.value,
        confidence: value.confidence,
        requires_review: true,
      });
    }
  }

  // Always review documents with extraction-level flags
  const needsReview = data.flags.some(f => f.severity === 'review_required')
    || flags.length > 0;

  return { abstract: data, needs_review: needsReview, review_fields: flags };
}

Common Implementation Considerations

Amendment ordering. Always submit amendments in chronological order with the base lease. The API needs to reconcile amendments against the original to produce the correct current abstract.
Document quality. Scanned PDFs with poor resolution produce lower confidence scores. Where possible, use digital originals. If you must process scans, pre-process with a deskew and enhancement step before submission.
Storage and versioning. Store both the raw extracted JSON and a versioned history of changes. Lease terms change at amendment; the historical versions are required for audit trails.
Rate limits. Bulk portfolio ingestion should use the batch endpoint and space submissions to avoid rate limiting. Contact API support for higher limits on large portfolio onboarding projects.

Get API access to LeaseIQ

LeaseIQ provides REST API access with full OpenAPI documentation, sandbox environment, and support for ASC 842, IFRS 16, and custom output schemas. Available for PropTech platforms, lease management systems, and accounting software.

See LeaseIQ API →