Commercial mortgage brokers

Know which loan is coming due, and what to do about it, two years early.

A maturity that is six months out is a race. Everyone in the market can read the same date, the borrower is already taking calls, and the only lever left is price. Twelve to twenty-four months out, the structure is still open and the conversation is uncontested. We build the system that watches every loan in your book, reads the documents behind it, scopes it against the lenders and structures that could actually take it, and puts the proposal in front of you while there is still time to be creative.

See how we do it

Why the refinance gets away.

Timing

The maturity gets worked at six months, when the whole market can see it

By the time a loan is half a year from maturity, every broker in the market has the same date and the borrower has already been called. What is left to compete on is rate, which is the one thing you do not control.

Parsing

The book is locked inside documents

Term sheets, letters of intent, rent rolls, and the inbox and message threads around every deal. All of it is unstructured, none of it is queryable, and the loan you closed four years ago cannot be found by maturity date, sponsor, or structure.

Lender coverage

Who lends on what lives in a few people's heads

Which lender will take which structure, at what leverage, on which asset class, and how that has moved this quarter. The people who know it are the people already carrying a full pipeline.

Recapture

The client you already closed refinances somewhere else

A broker earns on the new loan too, so bringing an old borrower back is a second fee on a relationship already paid for. Losing that borrower to whoever called first is the most expensive thing that happens quietly.

What Refi Engine does with the book you already have.

Every maturing loan surfaced 12 to 24 months out

Your closed book gets watched by maturity date, and each loan surfaces while the structure is still a live question.

Term sheets, LOIs, and rent rolls read once into fields

The paper behind each deal gets parsed into the fields your team actually queries on, so any loan is findable by sponsor, asset class, leverage, and maturity.

A lender database that holds who takes what

Lenders, programs, structures, leverage bands, and the constraints attached to each, held on one record and matched against the specific loan in front of you.

Market intelligence attached to the individual loan

Rate moves, program changes, and the conditions that make one structure work this quarter and not last, attached to the individual loans they change the answer for.

The recapture conversation drafted per borrower

Each borrower gets an outreach draft built from their own loan and the options that fit it, written for a person to read, edit, and send.

Build anything

We build whatever your operation needs.

Every system on this site started as one sentence from an operator describing the part of the job that eats the week. Write yours in the box below. Jake reads it himself and replies within one business day with what it would take to build.

Describe it in your words.

Plain language is enough. The more detail in the box, the more specific the reply.

The systems

What we would run in a commercial mortgage brokers operation.

Deal Engine

A sales system that sources prospects, answers every lead in minutes, and works the follow-up until there is an answer.

Refi Engine is the Deal Engine build for a mortgage desk. It watches maturities across your closed book, scopes each one against the lenders and structures that could take it, and drafts the borrower conversation for you to send.

Deep Brain

Everything the company knows, held in one private place the whole team can ask in plain language.

Every loan, sponsor, lender, and structure your firm has ever touched stays on one queryable record, so a maturing deal gets read against your own closed history.

Document Desk

Paperwork in, finished packets out, on deadline, with the trail intact.

Term sheets, letters of intent, rent rolls, and closing documents get read once into the fields your team works from, with every ambiguous read flagged for a person.

Two very different starting points, one build.

A two-person shop and a national brokerage have the same maturity problem and completely different reasons they have not solved it. The build meets each one where it is.

Independent and small shops

The problem

A book of closed loans sits in a folder structure and a few people's memory, and the maturity calendar is whatever someone happens to check.
There is no team to build a parsing layer and no budget for an enterprise platform to sit unused.

What we build

The whole book read into one record, maturities surfaced 12 to 24 months out, and the recapture conversation drafted per borrower.
It runs as a standing system, so it needs nobody on staff to keep it going.

Large brokerages

The problem

There is a technology team and there are working internal tools, so build capacity is already covered.
The constraint is the underlying data: broker inboxes, term sheets, and messages, all of it unstructured, and a general platform brings no capital markets judgment to validate what it extracted.

What we build

A parsing foundation shaped by how the deals actually read, a lender database maintained against it, and the cost of every run visible on the run itself.

Get started

Interested in making your commercial mortgage brokerage AI-native?

First name, last name, and a work email is all it takes. Jake reads every one of these himself and replies within one business day with what to automate first.

Send the details

First name, last name, and a work email. Jake replies within one business day.

Before you call

Three things you can check on us.

Risk

Seven-day money-back guarantee

Ask for your money back inside the first seven days of the build and you get it. After day seven the standard terms in your agreement resume.

Team

Engineering from Fortune 500 companies

The team includes former Fortune 500 developers, with prior experience at Microsoft, Morgan Stanley, NASA, T. Rowe Price, Perplexity, and Cognizant, and is drawn from Dartmouth, Brown, and Case Western Reserve. Read the roster.

Proof

We run Terso on the systems we sell

Our sales, research, and operations run on Deal Engine, Deep Brain, and Command Center every day. Ask on the call and we will show you ours running.

Where to start

See what this costs you before committing to anything.

Send the details of your commercial mortgage brokers operation and the reply comes back with the hours and the revenue currently going to the problems above, and which one to solve first.

A reply within one business day, written by Jake
The first build named, with the return it targets
No obligation to go further

Send the details

Name, email, and company. Jake reads these himself and replies within one business day.

Name

Work email

Company

Phone (optional)

Industry (optional)

What do you do, and what do you want automated the most? (optional)

Or .

A reply comes back from jake@tersoai.com within one business day. Details stay with Terso AI and are covered by the privacy policy.

Where it starts.

It starts with a free discovery call, then an audit that maps where the hours and the leads are going. The build starts with the highest-value piece, and we host, monitor, and keep improving the system from there.

Read how we work

Deal EngineA sales system that sources prospects, answers every lead in minutes, and works the follow-up until there is an answer.Deep BrainEverything the company knows, held in one private place the whole team can ask in plain language.Commercial real estateDeals scored against your own buy-box, with the source cited.

Common questions.

Where does the loan data come from?

Your own closed book first, because that is the data nobody else has and the only place a recapture can come from. Third-party lender and market data gets scoped during the audit, and we confirm each source before promising a connection we have not built.

We have developers in house. What are we actually adding?

The parsing foundation and the domain judgment that has to sit on top of it. Extracting a number off a term sheet is the easy half. The hard half is recognizing when that number is wrong for a real estate reason, and that judgment is what we bring to the build.

Does the system contact borrowers on its own?

No. Every message is drafted for a named person and sends on an explicit click. You decide which sequences run on their own and which wait.

Does our data leave, or train an outside model?

No. Deployments run with zero data retention on the model side, and your loan documents and borrower records stay inside your environment.

Is this only for commercial mortgage?

The maturity math is the same for any mortgage broker with a book of closed loans and a lender market to scope against. Commercial is where the structures are most varied, which is where scoping early is worth the most.

What if our loan history is mostly scanned PDFs?

That is the normal starting point. Scanned documents get read into structured fields, and any ambiguous read goes to a person to resolve.

Work your own book before anyone else calls it.

A free consultation walks through your closed loans and your maturity calendar and shows what is recoverable in the next twenty-four months.

Or send the details and we come to you.

Send the details instead

Name, email, and company. Jake replies within one business day.