Extracts and validates real estate transaction documents automatically.
A brokerage closing 50+ transactions monthly processes 40-60 documents per transaction: purchase agreements, disclosures, inspections, appraisals, title commitments, loan docs, and closing statements. Coordinators manually extract dates and terms, verify compliance, and track contingency deadlines.
Missing a contingency deadline means losing earnest money. Title defects not caught create closing delays. Inspection flags need immediate comparison against repair provisions. Document volume creates genuine error risk.
Docsumo and Prophia parse 200+ variables in minutes for commercial real estate, reducing processing time 85-95%. The same capability eliminates error-prone manual review in residential transactions.
The agent ingests documents as received — MLS, email, DocuSign, or upload — and performs type-specific extraction. Purchase agreements get parties, price, earnest money, closing date, contingencies. Inspection reports get flagged deficiencies with severity. Title commitments get exceptions and requirements.
Extracted data populates a transaction timeline showing every deadline. The agent alerts when deadlines approach: inspection contingency in 3 days, appraisal due in 5, earnest money tomorrow.
Cross-document validation catches inconsistencies: closing date in amendment matches lender commitment? Legal description consistent across agreement, title, and deed? Mismatches flagged before closing delays occur.
We configure a Python/FastAPI pipeline using LayoutLM for document-layout-aware extraction — it understands form structure, not just raw text, which matters for state-specific purchase agreements and HUD forms. Celery handles async ingestion from MLS feeds, DocuSign webhooks, and email; extracted records land in PostgreSQL with Redis caching for fast transaction lookups. We write deadline and contingency rules per transaction type (residential, commercial, refinance) as configuration, not hardcoded logic. Setup runs 2-3 weeks from integration access to production.
Processes purchase agreements, title commitments, inspection reports, appraisals, and loan packages using type-specific extraction templates. LayoutLM handles the positional structure of state-specific forms rather than treating every doc as free-form text. Each extracted field is tagged with confidence score and source location.
Builds a complete deadline timeline from dates extracted across all transaction documents — offer acceptance, inspection window, financing contingency, title clearance, closing date. Proactive alerts fire when a contingency deadline is approaching or a document hasn't arrived on schedule.
Checks consistency across the full document set: legal descriptions match between purchase agreement and title commitment, loan amounts reconcile across the HUD and lender disclosures, dates don't conflict between contingency addenda and closing instructions. Flags discrepancies before they become closing delays.
Ingests documents via DocuSign webhooks, MLS data feeds, and monitored email inboxes — no manual upload step. Each incoming document is automatically classified, extracted, and attached to the correct transaction record. New addenda or counter-offers trigger re-validation against the existing document set.
Anonymized work with hard metrics — NDA-bound, no client names.
2.1x
Time on Page
38%
More Qualified Leads
52%
Fewer No-Shows
“The no-show reduction was the metric our agents cared about most. The buyers who book visits after exploring the virtual tour have already self-selected — they know the property and they are serious.”
— Head of Digital, Real Estate Platform
We custom-build each agent to fit your data, your rules, and your existing systems.
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Fordel Studios