1 Lease Administration AI Agent, Live in Production.

1 live agent automates lease administration within real estate. It runs on demand. It publishes the inputs it needs, the steps it works through and what it hands back.

  • Live

    Lease Abstraction

    Pull the commercial terms, critical dates, and recurring obligations out of a lease, quote the clause each came from, and flag what a lease of this type should contain but does not.

Flagging what a lease of this type should contain but does not

Lease abstraction is done once, at speed, and everything afterwards depends on it. A reader extracts the rent, the term, the break clause and whatever else they notice into a spreadsheet, and the lease returns to storage. Two failure modes follow. The first is transcription: a notice period recorded as three months when the clause says three months prior to the fifth anniversary, and the difference surfaces when the break is missed. Nothing catches it, because the spreadsheet is now the record and nobody compares it back. The second is subtler and structural — a reader can only extract what is present. A lease of a given type that is missing a service charge cap, or a reinstatement provision, or an assignment right, produces no entry in the spreadsheet and therefore no signal. The absence is invisible.

Lease Abstraction pulls the commercial terms, critical dates and recurring obligations out of a lease, quotes the clause each came from, and flags what a lease of this type should contain but does not. The quoted clause solves the transcription problem by making the abstraction auditable against the source. The absence check solves the second problem, and it is the output that a careful human reader structurally cannot generate — noticing what is not there requires comparing against an expected set rather than reading what is written. One agent covers this process, and its output is an abstraction for review, not a record.

What this moves

Critical dates captured in a system
Commercial terms, dates and recurring obligations are extracted with the clause each came from, so the abstraction can be verified against the lease.
Absent provisions identified
What a lease of this type should contain but does not is flagged, which is the finding a person reading the document cannot produce.

Real Estate

How AI agents handle lease administration

Drawn from the 1 agent above — what they require, how they run, and what comes back.

What they need

  • Lease document
  • Abstraction settings

What comes back

  • Gaps and inconsistencies Validation result
  • Headline terms Metadata grid
  • Critical dates Table of results
  • Recurring obligations Table of results
  • Clause review Clause table
  • Property-system record Json payload

How they run

Run on demand
1
Steps per run
5
Credits per run
7

Where lease administration fits in real estate

Terms, dates and obligations are extracted from documents nobody reads end to end, so a question about a clause takes seconds instead of an afternoon.

All 2 real estate agents

Next Step

Deploying lease administration agents

These run as-is against the inputs listed above. Most deployments adapt one — a different source system, a different tolerance, a different approval path. The first call establishes which.

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