AI engineering for enterprise · Building since 20164 products · run on our own ops · 30+ enterprise clients

Real Estate & Construction · Lease document automation

Your renewal window passed. It was in clause 14.3(b).

Banao builds AI pipelines that read every lease PDF in your portfolio — pulling renewal dates, break options, rent escalations, and tenant obligations into a structured register your asset team can query in plain language.

A missed renewal deadline or a rent review that went uncalendared costs more than a year of the platform. The pipeline reads the clause, logs the date, and fires the alert before the window closes.

a Gulf commercial property portfolio— lease obligations extracted from 300+ PDF contracts into a live queryable register.

The first call is free · 45 minutes · no obligation

What we build

What a lease automation deployment covers

The value is not in reading one lease — it is in maintaining a live, accurate register across every property, every renewal cycle, and every portfolio change.

Clause and obligation extraction

AI reads each lease PDF and pulls the clauses that carry financial or legal weight — rent amounts, escalation formulas, service-charge caps, break rights, and reinstatement obligations — into structured fields a human can audit.

Renewal and break-option calendar

Critical dates — option exercise windows, break notice periods, rent review triggers — are logged with lead-time alerts so a portfolio manager is notified weeks before the window, not days after it closes.

Rent escalation register

CPI-linked, fixed-step, and open-market review clauses are extracted and tagged with their next trigger date. The register tells you what the rent becomes, when, and under which formula — without re-reading the document.

Plain-language portfolio query

Asset teams query the entire register in plain English — 'which leases expire in Q3 with no renewal option?' or 'show all tenants carrying reinstatement liability'. The answer comes from structured data, not a PDF search.

Lease comparison and variance flagging

When a new lease or variation document arrives, the system compares it against the existing record and flags what changed — rent, term, break rights, obligations — so a reviewing solicitor works from a diff, not a blind read.

Integration with asset management and ERP

Extracted data feeds into the property management or ERP system your team already uses — Yardi, MRI, SAP, or custom — so the register is a live upstream source, not a parallel spreadsheet to maintain.

Receipts

Where this is already running

Metrics shown dotted (··) are being finalised in our case-study metrics pack — published only once verified.

a regional Gulf commercial property developer

Lease obligations extracted from a 300-contract portfolio

··%
lease terms captured accurately
··hrs
abstraction time saved per lease
··%
renewal windows now tracked

Hundreds of commercial and residential leases had been managed in spreadsheets maintained by hand. Banao built an extraction pipeline that reads each PDF, pulls the financial and legal obligations, and feeds a register the asset team queries in plain language — without re-opening a document.

Dogfooding

We run our contracts through the same pipeline

Banao operates a ~300-person engineering company with vendor agreements, client MSAs, and sub-contractor terms spread across 50+ active documents. We use our own document processing tools to track the obligations that carry money — the same pipeline we build for you.

A lease register is only as good as the team that trusts it. We will not hand over something we would not stake our own contracts on — and we do.

InterviewGod

Screens Banao's own engineering hires every week.

Vikaas

Runs Banao's own demand-gen pipeline end to end.

The honest version

When lease automation is the wrong starting point

Automated extraction is fast and accurate on well-formed PDFs. A few situations change the calculus — we will say so before you commit:

  • Handwritten or scanned legacy leases: extraction accuracy falls sharply on photocopied documents without OCR remediation. If the portfolio runs on scanned agreements, week one is document digitisation, not extraction.
  • Fewer than thirty leases: below that threshold, a trained paralegal reads faster than an AI pipeline pays back. The crossover depends on renewal frequency and clause complexity — we calculate it honestly in the Sprint.
  • One-off acquisition due diligence: if you need a single portfolio read for a transaction, a law-firm extraction team is often faster. We build living registers for ongoing operations, not one-shot reads.

How we start

How we start — fixed-price, no PDF roulette

Lease automation fails when a vendor trains on generic contract data and your leases use custom wording. We start by reading yours.

  1. 01

    AI Discovery Sprint

    2 weeks · fixed price

    We read a sample of your actual leases, test extraction accuracy on your hardest clause types, and hand back a field-by-field accuracy estimate and the ROI maths — yours to keep. If you proceed, the Sprint cost is credited against the build.

  2. 02

    Build

    Pipeline built on your documents, your clause taxonomy, and your integration targets. The model is fine-tuned to your lease style — not a generic contract model — and the register schema matches the fields your team actually uses.

  3. 03

    Production & continuous improvement

    Live extraction for new leases, variation documents, and renewals as they arrive. Accuracy reports and a human-review queue for low-confidence extractions. The model improves with each reviewed correction.

FAQ

Frequently asked questions

What types of lease documents can the pipeline read?

Commercial leases, residential tenancy agreements, ground leases, and variation deeds in PDF or Word format. The pipeline handles well-formed digitally-created documents reliably from day one; scanned or handwritten documents need an OCR remediation step, which we scope in the Discovery Sprint.

How accurate is the extraction on complex clause wording?

Accuracy on a fine-tuned model for your specific lease style runs high on standard financial and date fields. Negotiated bespoke clauses — non-standard rent formulas, unusual break conditions — are where a human-review queue adds value. We publish a field-by-field accuracy estimate from the Sprint before you commit to the build.

Can it handle leases in multiple languages or jurisdictions?

Yes, with jurisdiction-specific fine-tuning. GCC portfolios often carry Arabic and English versions of the same instrument; we have processed both in the same pipeline and reconciled them against each other. Multi-jurisdictional scope is agreed during the Sprint.

Does the register connect to our property management software?

Yes. The extracted data feeds into Yardi, MRI, SAP, or a bespoke system via API or direct database write. Integration with the property management or ERP system is a deliverable of the build phase, not an afterthought.

What happens when a lease is amended or a new document arrives?

The pipeline processes new documents automatically — variations, surrender deeds, licence letters — and flags what changed against the existing record. The asset manager sees a diff, confirms the change, and the register updates without re-reading the whole document.

Get started

Find out how many critical dates your portfolio is missing

Bring a sample of your lease PDFs. In 45 minutes we will show you what an AI extraction picks up, where the gaps are, and what a live register would cost to build.

Book a Discovery Sprint