Leaseline reads the rent roll you already keep and puts one register, one set of templates, one approval chain and one live management view around it.
Every one of these came out of a real rent roll.
Invisible to every report. No contractual protection, and nobody is diarising them.
Leverage falls the closer you get to expiry. The tenant knows the date too.
Agreed step-ups that never reached the invoice. Nobody reconciles the two.
Occupancy, WALE and income concentration rebuilt by hand each month, out of date on arrival.
When the person who knows the portfolio leaves, the knowledge leaves with them.
Rent you would otherwise give away. Exposure you would not have seen. Weeks of a leasing team's year.
A renewal opened nine months out is a negotiation. Opened six weeks out, it is a request. Occupancy cost shows which tenants can absorb an increase and which are already at the edge.
A lease with no recorded expiry appears in no report and protects nothing. At portfolio scale the same problem is expiry concentration — one quarter carrying a third of your income.
One register, one approval chain, a recorded approver on every offer. The monthly pack stops being assembled by hand, because the numbers are already computed.
Figures from the demonstration portfolio below — 150 leases of fictional data, built to behave like a real rent roll. They are what the system found in it, not results claimed on anyone's behalf. What it finds in yours is the only number that matters, and it takes one export to know.
Running on a fictional mall of 150 leases, built to look like a real rent roll — mess included.
Every import is checked. What can be resolved without guessing is resolved and logged; everything else is put to a person with the evidence and the options in front of them. It reads any layout, matching your columns on both their wording and their contents.
Expiries inside your notice window, leases already past expiry, holdovers with no documented term, vacant units priced at rent forgone — ranked by monthly rent at risk, so the list leads with money rather than with dates.
A mall that opens at once expires at once. The renewals signed this quarter either repeat that cliff in three years or break it — and breaking it means varying term lengths deliberately, while the whole cycle is still open. Projected against deals in progress, not just the signed register.
Import monthly sales and every renewal conversation gains a floor under it: occupancy cost on moving annual turnover, per tenant and per category, beside turnover per square foot. A tenant at 12% can absorb an increase. A tenant at 28% is heading for a default, and pushing rent is how you get a void to re-let.
Every lease structured — dates, areas, step-ups, service charge, percentage rent — with a route from any number on screen back to the row it came from. Completing a deal writes the new term straight back, so the master file and the system never diverge.
Terms, tenant record, proposal, approval, offer. The chain is built upward from whoever prepared the deal, so nobody approves their own, and a rejection returns the file with comments rather than disappearing into an inbox. Documents generate into your own Word templates — clauses, formatting and running header untouched.
Occupancy, annualised rent, WALE, expiry and tenant concentration, vacancy cost — computed from the register rather than rebuilt by hand for each month's pack. Income and risk exposure are commercially sensitive, so access is set per role during configuration.
The tools available to a leasing team are either enterprise systems that take six months and six figures to deploy, or a spreadsheet and a folder of Word documents. This is the layer in between.
A hundred to four hundred tenancies, a small leasing team, and a renewal cycle that arrives all at once.
Retail podiums where leasing sits inside a larger development business and has no system of its own.
One view across the portfolio, and one way of doing things across teams that were never standardised.
WALE and expiry profile are a quarterly reporting obligation, not a convenience. Produced from the register rather than assembled by hand.
Running assets on behalf of owners, judged on leasing performance, and carrying the reporting burden for every one of them.
Your files stay where they are. No migration, and nothing new for the team to log into every day.
General AI drafts quickly and makes each person faster. It cannot enforce which template version was used, check the figures against your rent roll, stop an offer being issued before approval, or record who approved what and on which version.
Six people generating documents six different ways creates more uncontrolled copies of your commercial terms, not fewer. Leaseline generates from one register, through one approval chain, and files the result back where it belongs.
We are a small team. Between us we carry decades of running retail leasing inside major Malaysian shopping centres — negotiating the renewals, chasing the approvals, rebuilding the monthly pack by hand — and years more building and operating businesses where the reporting had to work before anything else could.
That is where the product comes from. What belongs on an action list and what is noise. Which tenant is worth a longer term and which one you keep your options on. What occupancy cost means for a café as against a jeweller. Which numbers a system has no business guessing at, and should say so instead.
The software was the straightforward part. Knowing what to build took the years inside it — and it is why Leaseline does a few things properly rather than everything approximately.
We are working with a small number of design partners ahead of general availability. If you run a retail or mixed-use portfolio and the screens above look like your week, we would like to hear from you.
The fastest way to judge this is to watch it read your own data. Send one export and we will show you what it finds in it — including the parts you would rather it didn't.
josh@getleaseline.com