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LeaseIQ – AI Lease Abstraction, USA (Concept)
Concept project. This is a demonstration project designed by Softsols to show how we would approach a typical US commercial real estate AI brief. It is not a delivered client engagement, and all names and data shown are fictional. Talk to us about building something similar.
ProjectLeaseIQ (Concept)
MarketUSA
IndustryReal Estate · AI
PlatformsWeb, AI/LLM
Overview
LeaseIQ is a concept AI application that reads commercial leases and produces structured lease abstracts: rent schedules, renewal options, critical dates, CAM provisions and unusual clauses. Property and asset managers can also ask plain-English questions across their whole lease portfolio and get answers with citations to the source page.
The challenge
Abstracting a commercial lease by hand can take hours, and portfolios contain hundreds of leases with amendments, scanned exhibits and inconsistent formats. Missed renewal deadlines or misread escalation clauses cost real money, yet the knowledge often sits only in PDFs and in the heads of a few people.
Our solution
We designed a retrieval-augmented generation (RAG) pipeline that OCRs and indexes every lease and amendment, then uses a large language model to extract a configurable set of fields with page citations. Low-confidence fields go to a human reviewer, so abstracts are verified before they reach the rent roll. A chat assistant answers portfolio-wide questions grounded in the indexed documents.
Key features
- Bulk upload of PDFs and scans with OCR and amendment linking
- AI extraction of configurable abstract fields with page-level citations
- Confidence scoring and a human-in-the-loop review queue
- Critical-date calendar with email and Slack alerts
- Portfolio Q&A assistant grounded in your leases (RAG)
- Exports to Excel and property management systems via API
- Role-based access, audit trails and no training on client data
Responsible AI by design
Every extracted value links back to its source page so reviewers can verify it in seconds. The architecture is model-agnostic (OpenAI, Claude or Gemini) and can run through Azure OpenAI or AWS Bedrock with zero data retention for sensitive portfolios.
Technology stack
Python (FastAPI), LlamaIndex, PostgreSQL with pgvector, OCR (AWS Textract), React front end, deployed on AWS or Azure.
Design goals
- Turn hours of manual abstraction into a short verification step
- Never miss a critical lease date
- Make lease knowledge searchable for the whole team
Planning a similar product? Get a free consultation or estimate your project cost in 60 seconds. Related services: AI integration and LLM apps, AI agent development.
