🔍 Entity Normalization

Automatically resolves 50-100+ name variations per property (e.g., "John Smith" = "Smith, John" = "J. Smith" = "John A. Smith"). No more missed chain links due to spelling inconsistencies.

⛓️ Chain Gap Detection

Identifies missing deeds, unexplained ownership transfers, and breaks in the chain-of-title with exact date ranges and responsible parties. Pinpoints exactly where documentation is missing.

💰 Lien Intelligence

Detects open trusts, unreleased mortgages, and orphaned liens. Classifies by property scope (building-level vs. unit-level) and filters out historical encumbrances from prior ownership periods.

📊 Risk Scoring

Three-tier marketability assessment (CLEAR/ENCUMBERED/DEFECTIVE) with confidence scores and prioritized findings. Focuses your attention on issues that actually affect insurability.

🛠️ Actionable Roadmaps

Not just "here's what's wrong"—includes specific cure steps, required documents, estimated costs, and realistic timelines to resolve each issue.

📄 Professional Reports

Self-contained HTML reports with interactive chain visualizations, cited document references, and attorney-friendly formatting. Ready to share with clients or underwriters.

AI Architecture: ClearTitle AI™ is built as a multi-stage examination pipeline, combining advanced large language models with deterministic business rules. Each stage performs a narrowly scoped task—classification, extraction, normalization, risk evaluation—producing structured, auditable outputs that mirror how experienced examiners reason through a title record.

Infrastructure: The platform runs on a fully serverless AWS stack (Lambda, S3, API Gateway, CloudFront) with Zapier-based workflow orchestration. This architecture scales automatically from single properties to production volumes without infrastructure management. Typical end-to-end processing completes in approximately two minutes per property.

Entity Normalization: Proprietary entity-clustering logic resolves 50–100+ party name variations per property using fuzzy matching, phonetic similarity, and contextual ownership analysis. The system is designed to handle maiden names, estate transitions, trust structures, LLC naming drift, and historical spelling inconsistencies across decades of recordings.

Document Classification: AI-driven instrument classification identifies deeds, deeds of trust, assignments, releases, modifications, and corrective instruments with high accuracy. From unstructured Recorder of Deeds HTML, the system extracts structured parties, execution context, legal descriptions, recording metadata, and consideration data to support downstream analysis.

Data Security & Privacy: ClearTitle AI™ operates exclusively on public Washington, DC Recorder of Deeds records. Secure, time-limited S3 delivery is used for report access. No sensitive data is retained, no customer data is shared with third parties, and no inputs are used for model training outside the scope of the examination workflow.

Validation & Examiner Alignment: The system has been tested against manual attorney and title examiner work product. Early validation shows 85–95% concordance on chain gap identification and open lien detection, with consistent strength in uncovering issues driven by entity ambiguity, recording density, and long ownership histories.