Automate Lease Abstraction for Net Lease Properties with AI

Syntora approaches AI lease abstraction for net lease properties as a custom engineering engagement, beginning with a detailed discovery phase to understand your specific document types, critical data points, and existing workflows. The goal is to design and build a system that precisely extracts essential terms, dates, and clauses relevant to your portfolio's unique requirements, rather than adapting a generic product.

The proposed architecture for such a system would involve several key components. Lease documents would typically be ingested via secure cloud storage, such as AWS S3, triggering an automated processing pipeline. For scanned documents, an optical character recognition (OCR) service would convert images into searchable text. The core of the extraction process would leverage large language models like the Claude API, which we've successfully used for complex document processing pipelines in adjacent domains like financial contracts. This API is well-suited for understanding the nuanced language and variable structures found in triple net leases, identifying specific provisions for tenant credit, escalation clauses, renewal options, and expense allocations.

An orchestration layer, potentially built with AWS Lambda functions, would manage the flow of documents through parsing, extraction, and validation stages. The extracted data would be stored in a robust database solution like Supabase, which provides a PostgreSQL backend with real-time capabilities and integrated authentication, ensuring data integrity and secure access. A custom API, built using FastAPI, would expose the abstracted data for consumption by your existing property management systems or for integration into a custom dashboard.

The development process typically involves iterative builds, allowing for client feedback and fine-tuning of extraction models. Syntora would deliver a fully deployed and documented system, along with training for your team. A typical build timeline for a system of this complexity, including discovery, development, and deployment, would range from 12 to 20 weeks, depending on the number of document variations and integration points. Clients would need to provide a representative sample of lease documents for training and validation, along with clear definitions of the data points requiring extraction.