At Visual Lease, we’ve spent years dedicated to creating a true system of record for enterprise lease workflows – our software provides powerful tools to help real estate and finance teams make strategic decisions, but the data that powers those decisions has always been our primary focus, and something we were unwilling to compromise on.
So when AI lease abstraction tools started to hit the market that promised unmatched speed, we were skeptical.
Lease abstraction errors don’t stay isolated. A wrong date, a misread rent schedule,or an ambiguous responsibility split that the AI guessed on flow directly into your financial reporting, your audit trail, and every portfolio decision downstream.
Speed only matters if the data coming out the other end is right.
We put many tools to the test, and found they just weren’t meeting our standard for accuracy, reliability, and security. So we built a better way.
AI lease abstraction that’s actually accurate
- Separate logic for every document type Lease language varies across regions, asset classes, and industries. We’ve created dedicated logic for each — so a retail lease in California and a warehouse lease in Germany don’t get processed the same way.
- Engineered by actual lease experts Our prompts were built and continuously refined in partnership with our in-house, onshore team of 50+ attorneys and lease abstractors. Not a generic LLM pointed at documents — purpose-built for lease complexity.
- Validated against CoStar’s proprietary data. Better data means access to more scenarios to build for – and validate against. With the acquisition of Visual Lease, CoStar now represents the largest lease management software provider for commercial real estate leases by an order of magnitude. Every abstraction is cross-checked against CoStar’s real estate data — including 1M+ verified leases and 8M+ tenant comparables — to catch rent anomalies and square footage mismatches before they reach your portfolio.
- When it’s not certain, it doesn’t make it up If the AI isn’t confident on a field, it never guesses. You’ll know exactly where to focus your review.
- You stay in control Every AI-generated field enters your system in draft, tied back to the original lease language. Your team reviews and approves — AI handles the heavy lifting, you stay in control.
Introducing AI lease abstraction in Visual Lease
Upload lease files, or a folder of them, and within minutes you get a draft record with auto-populated fields, source language tied back to every suggested data point, and an AI Summary with critical dates, rent schedules, key clauses, and more — all in draft status, ready for your team to review before anything goes live in your portfolio.
How AI lease abstraction works
Most AI abstraction tools apply a general-purpose model to any document you upload. That works reasonably well for simple, clean leases. But the leases we see are anything but. Lease language isn’t uniform. Responsibility splits are often genuinely ambiguous. Details to built out rent schedules are often hidden in tables, handwritten annotations, strikeouts, or deal-specific structures that a generic model will misread or skip entirely.
The Visual Lease AI Abstraction engine was purpose-built for this complexity. Here’s what actually happens when you upload a lease:
- Document classification first. Before anything is extracted, the engine classifies the document — identifying what type of lease it is, what region it covers, and what regulatory context applies. Different document types go through different prompts. That classification step alone sets this apart from tools that treat every document the same.
- Two OCR passes. The first scan classifies. The second captures everything — tables, images, struck-through text, formatting — the details that standard extraction misses and that matter for building out an accurate rent schedule.
- Expert-built prompts. Our in-house team of 50+ onshore attorneys and lease abstraction experts built the prompts the engine runs on — and they continuously refine them. These aren’t generated by software engineers pointing an AI at a document. They’re built by people who have spent careers doing this work manually and know exactly where lease complexity hides.
- CoStar data validation. Every output is validated against CoStar’s real estate data — over a million verified leases and millions of tenant comparables — before it reaches you. If a rent figure is significantly outside the norm for that market, the engine catches it. This is a capability no other lease abstraction solution can offer, and it’s what makes the accuracy story fundamentally different.
Enterprise-grade security you can take to your IT Team
Our customer base is incredibly diverse, including brands in highly regulated industries that consider on their real estate data as proprietary, confidential competitive differentiator for retail foot traffic, supply chain efficiency, and so much more. Those customers expect the highest security standards – so we built for it.
- Customer data is never stored or exposed to the public cloud. We invested in Amazon Bedrock to isolate customer data from public models and provide end-to-end data encryption in transit and at rest.
- All customer data usage is governed by our existing privacy policies and SOC requirements as well as our contractual obligations.
