Loft47 is a real estate transaction processing company that manages accounting, commission tracking, agent payouts, and deposit facilitation for brokerages across North America. The platform supports complex real estate workflows that require accurate contract review, structured data capture, and strict signature validation.
Problem: manual contract review slows transaction processing
Before adopting document automation software, large brokerages using Loft47 spent around 5 hours daily reviewing Purchase and Sale agreements manually. Teams verified buyer and seller details, property information, financial terms, commission splits, and required signatures across multiple pages and formats.
With at least 25 MLS contract templates across North America, variations in layout and structure made the process repetitive and error prone. This caused approval delays, higher operational costs, compliance risks, and limited scalability, while rule-based automation failed to handle format diversity effectively.
Solution: AI-powered document automation software for contract extraction
GoML designed and delivered an MVP document automation software platform powered by Agentic AI that automatically extracts structured data from real estate contracts and validates execution requirements.
The system uses coordinated AI agents to interpret contract structure, extract predefined transaction fields, verify signatures, and apply validation rules. It processes digital PDF contracts and generates structured JSON outputs ready for integration into Loft47’s backend systems.
Secure document ingestion and storage
The document automation software enables secure PDF uploads through web interface or API, with automated processing triggered via API or S3 monitoring.
Documents and results are stored in Amazon S3 with controlled access.
AI-driven data extraction engine
Built on Amazon Bedrock with Claude 4.5, the system processes at least 25 MLS contract formats, extracts predefined transaction and compliance fields, maintains consistent JSON mapping, and adapts to new formats through configuration.
Signature detection and validation
The platform detects signatures and initials across pages with Amazon Textract combined with OpenCV, validates placement based on contract type, and flags missing or invalid signatures.
Web-based review and approval
Users can view PDFs alongside extracted data, see highlighted fields, approve or reject documents, and edit values when required.
Dynamic contract configuration
Users can define new contract types, map custom fields, configure signature rules, and reuse templates for similar formats.
Scalable AWS architecture
Runs on AWS using Amazon S3, Python backend services, Amazon Bedrock with Claude 4.5, and REST APIs for structured JSON delivery.
Impact
- 60 to 70 percent reduction in manual contract review time for large brokerages
- Minimum 80 percent accuracy on predefined extraction fields during MVP validation
- Faster transaction approvals through automated data cap
About
Before Gen AI and after Gen AI
“With Loft47’s document automation software, we converted complex multi-format real estate contracts into structured, validated data streams that reduce manual workload and improve transaction accuracy.”
Prashanna Rao, Head of Engineering, GoML
Key takeaways for real estate transaction platforms
Common challenges
- Manual contract review consumes hours daily
- Multiple MLS formats increase operational complexity
- Signature errors create financial and compliance risk
- Scaling operations increases staffing costs
Practical guidance
- Define a standardized JSON field specification before implementation
- Use AI-driven document automation software for multi-format extraction
- Build configurable signature validation rules
- Combine automated extraction with structured review workflows
Ready to implement document automation software for real estate contracts?
Partner with GoML to accelerate scalable real estate contract processing with AI Matic powered document automation software.
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