An AI and automation solution extracting, validating and structuring commitment-related data from complex title documents at scale.
Title commitment preparation is a meticulous and compliance-heavy process that involves reviewing multi-page legal documents, extracting critical information, and ensuring accuracy per underwriter standards.
Skylark, a leader in commitment typing services, supports the real estate and title industry with tax status searches, document reviews, and title commitment generation.
As document volume and complexity increased, Skylark needed a scalable solution to automate key data extraction while maintaining accuracy and legal compliance.
Skylark provides specialized commitment typing services for title agencies and real estate institutions, with a focus on precision, speed, and regulatory compliance.
Their operations involve parsing documents that can exceed 200 pages, identifying legally binding content such as deeds, mortgages, and tax records.
To keep pace with growing volumes and diverse document formats, Skylark required intelligent automation that could seamlessly integrate with systems like ATR for downstream processing.
Every operational bottleneck reported was matched to the workstream(s) that resolved it.
Many title-related documents ranged up to 232 pages, making manual review time-intensive and error-prone.
Combined optical character recognition (OCR) with Large Language Models to accurately identify and extract deed types, party names, mortgage information, and tax data from diverse document formats.
Different counties and underwriters used distinct formats and data requirements, complicating standardization.
The system recognized and processed master/subcategories to handle varying layouts and structural nuances in legal documents.
Business rules were applied to determine grantor types, validate instrument numbers, and ensure consistency in book/page references and filing dates.
Accurate capture of critical fields like book/page numbers, instrument numbers, grantor/grantee details, and deed dates was essential for legal validity.
Business rules were applied to determine grantor types, validate instrument numbers, and ensure consistency in book/page references and filing dates.
Extracted information had to be converted into a structured format compatible with ATR's system, which was critical for further title processing.
Extracted data was formatted into JSON, enabling smooth ingestion into ATR's system for downstream workflows such as indexing, audit, and decision-making.
Manual review time was significantly reduced, accelerating overall title commitment preparation.
Business rule logic minimized inconsistencies, particularly in legally sensitive fields.
JSON-based formatting allowed real-time integration into ATR's internal systems, reducing hand-off delays.
Structured extraction and rule-based validation ensured conformance with underwriter and jurisdictional requirements.
Skylark's solution now supports multiple clients and jurisdictions with minimal template rework or rule customization.
Outputs were tailored to meet compliance and underwriter standards across multiple counties.
