You will get AI Lease Abstraction — Structured Data from Your Commercial Leases
Project details
Send me your commercial lease PDFs and I'll extract every key field into a clean, structured spreadsheet — tenant, landlord, term, rent schedule, escalations, critical dates, renewal options, and CAM provisions. Every extracted field is traced back to its source page so your team can verify without re-reading the document. I hold an LLB from the University of London, so I understand what I'm extracting — not just the format but the legal substance. A CPI escalation with a floor and cap gets labeled correctly. A personal guarantee buried in an amendment gets flagged. The output is ready to use, not a rough AI dump that needs a lawyer to decode. I handle any lease format — NNN, gross, modified gross, ground leases, subleases — and any volume from 1 to 500+.
AI Development Type
Knowledge RepresentationAI Development Language
PythonWhat's included
| Service Tiers |
Starter
$150
|
Standard
$350
|
Advanced
$900
|
|---|---|---|---|
| Delivery Time | 3 days | 7 days | 14 days |
Number of Revisions | 1 | 1 | 2 |
AI Model Integration | |||
Detailed Code Comments | - | - | - |
Knowledge Graph | - | - | - |
Model Documentation | - | ||
Ontology | - | - | - |
Source Code | - | - | - |
Taxonomy | - | - | - |
Optional add-ons
You can add these on the next page.
Additional Revision
+$10Frequently asked questions
About Syed Uzair
AI Document Processing for Legal & Real Estate | Lease Abstraction
Karachi, Pakistan - 1:35 pm local time
I build AI document processing pipelines specifically for commercial real estate firms and law practices handling lease portfolios. What that means in practice:
• You send me your lease PDFs (any format, any length, any state's template)
• I run them through an AI extraction system I built and maintain
• You get back a clean spreadsheet: tenant, landlord, premises, term, rent schedule, escalations, options, CAM provisions, insurance requirements, and every critical date
• Every extracted field links back to the exact page and paragraph it came from — so your team can verify without re-reading the whole document
I also build document Q&A systems: upload a set of contracts, ask plain-English questions ("What's the notice period for early termination across all our Chicago leases?"), and get cited answers.
Background: LLB (Hons), University of London. I understand lease structures, not just AI tooling. That means I catch errors that a pure technologist would miss — a rent escalation tied to CPI vs. a fixed percentage, an option that requires 180-day notice vs. 90, a personal guarantee clause buried in an amendment.
I'm building my Upwork profile — so early clients get senior-level attention at introductory rates. Happy to process a sample lease as a paid trial so you can evaluate the output before committing to a batch.
Steps for completing your project
After purchasing the project, send requirements so Syed Uzair can start the project.
Delivery time starts when Syed Uzair receives requirements from you.
Syed Uzair works on your project following the steps below.
Revisions may occur after the delivery date.
Document intake and format review
I review your lease PDFs for quality and format, flag any issues (poor scans, missing pages), and confirm the extraction field list with you.
AI extraction with legal review
Each lease is processed through my AI pipeline, then I manually verify every extracted field against the source document using my legal background.