Real Estate · Document AILease Abstraction Software & Document AI
AI lease abstraction for landlords, occupiers and investors — key terms, dates and obligations extracted from leases and property documents, each linked to its source clause and checked by a person.
Message on WhatsApp
TRUSTED BY TEAMS
A lease abstract is a short summary of a lease’s key terms: parties, term, rent, escalations, options, obligations and critical dates. Lease abstraction is the work of producing one, and it is usually done by someone reading every lease by hand.
Sodio builds AI lease abstraction software that reads leases and other property documents, extracts their terms into structured data, links every value to the clause it came from, and sends anything uncertain to a person — so the result can be trusted, not just produced quickly.
/// IS CUSTOM RIGHT FOR YOU?
A Service, a Tool, or Your Own System or Your Own System
Lease abstraction services — teams that abstract leases for you — and packaged AI abstraction tools both exist, and for many portfolios one of them is the right answer.
Use a service or a packaged tool when
- You have a fixed backlog to abstract once
- A standard abstract template suits you
- The output only needs to live in a spreadsheet
- Leases are the only documents involved
Build your own when
- New leases, acquisitions and amendments arrive all year
- Your abstract has fields and definitions specific to your business
- Extracted data has to flow into your lease, portfolio or accounting systems
- Rent rolls, offering memoranda, estoppels and invoices need reading too
/// WHAT THE SYSTEM COVERS
What Lease Abstraction Software Covers
Document intake
Your abstract template
Clause extraction
Critical date calculation
Amendment reconciliation
Source linking
Confidence and review
Portfolio questions
Export and integration
Beyond leases
/// DOCUMENTS
Documents It Reads
/// HOW A LEASE BECOMES DATA
How a Lease Becomes Data
Documents arrive, in any format
Pages read, including scans, and sorted by document type
The text is structured
Sections, clauses and defined terms identified
Fields are filled in
Each value extracted with its source clause and a confidence score
Amendments are applied
Original lease, amendments and side letters combined into current terms
A person checks
Uncertain and high-value fields reviewed; corrections recorded
The abstract goes live
Data passed to your systems and critical date alerts set
/// WHERE EXTRACTION GOES WRONG
Where Extraction Goes Wrong — and How It Is Caught
Most lease abstraction errors come from a handful of predictable places. These are designed for, not discovered later.
/// ACCURACY
How Accurate Is AI Lease Abstraction?
Accuracy is not one number. It depends on the field, the document and the quality of the scan, which is why it is measured on your own leases before anything goes live — compared field by field with abstracts your team already trusts.
/// COMPARE
Manual Abstraction, Automated Tool or Custom Document AI
/// COST AND TIMELINE
What Drives the Cost and Timeline
A pilot on a sample of your own leases, measured against your existing abstracts, typically runs within 30 days. If it meets the accuracy you need, a production system follows within 90.
The cost moves with six things: how many documents and how long they are; the quality of the scans; how detailed your abstract template is; which document types beyond leases are included; the review workflow; and the systems the abstracts must flow into.
/// FAQ
Frequently Asked Questions
A lease abstract is a short summary of a lease's key terms — usually one to three pages — covering the parties, the premises, the term, rent and escalations, options such as breaks and renewals, obligations, and the critical dates. It exists so that nobody has to reread a sixty-page lease to answer a simple question. Lease abstraction is the work of producing one, and lease abstraction software is what automates it.
It depends on the field and the document. Parties, dates and rent are extracted reliably from a clean lease; complex obligations and heavily amended leases are harder. That is why accuracy is measured on a sample of your own leases against abstracts your team trusts, field by field, before anything goes live — and why uncertain values go to a person rather than being saved.
Yes, and it is where most abstraction errors come from. The system reads the original lease together with every amendment and side letter in date order, so the abstract shows the terms that apply now, with a history of how each one changed. If a lease refers to a document that is missing from the file, that gap is flagged.
They are read with text recognition, and each value is scored for confidence. Faint scans, handwritten changes and faxed pages usually score lower, and those values are sent for review rather than trusted. Very poor copies are flagged so the original can be found.
Yes, as part of a project. For a one-off backlog — a system migration, an acquisition, a portfolio review — we can run the AI-assisted abstraction with your team reviewing the results, rather than you building a process for work you do only once. For ongoing volume, the software stays with you.
Yes. Models are hosted so your documents are not used to train anyone else's, access follows the same permissions as your other systems, and documents and abstracts are stored under the data protection rules that apply to you.
/// RELATED SERVICES
Related Industries and Services
Routes where scope overlaps with real estate software.
/// GET STARTED
Start With Your Hardest Leases
Tell us how many leases and documents you hold, and share a sample — including the heavily amended and badly scanned ones. We will assess, free, what can be extracted reliably, where a person still needs to look, and what a system would take.