AI & automation for real estate teams
Put a copilot on the work that keeps agents off the phone.
We build and run AI copilots for the repetitive layer of a brokerage: listing prep, pricing signals, offer packets. One loop at a time, measured against your own baseline.
Starts with a paid assessment. You keep the roadmap either way.
1420 Maple Ave · new listing
Listing Intelligence Copilot · draft 1
- Headline & premium descriptionDrafted
- Feature list from MLS + seller notesDrafted
- Comp set, two outliers excludedNeeds your call
- Agent review & publishWaiting on you
“Priced at $412k the confidence signal is high. Two comps on Elm sold above trend and were excluded. Open them before you publish.”
80-130 min
What one buyer offer packet took by hand, timed by the brokerage before we built anything
5.6 sec
Intake submitted to a drafted packet and a review email, measured end to end
16/16
Offer-drafting eval cases passed by the model tier we run in production
25
Additional Provisions blocks chosen by deterministic rule, never by model judgement
Measured on our Wisconsin buyer-offer-automation pilot, not a client-wide average, and the drafting time is the brokerage's own baseline for the manual process. We publish the method on the Trust page.
The problem
We automate the layer that quietly costs you deals
Every brokerage has the same four leaks. We build a copilot for one at a time and prove the number before scaling to the next.
Listing quality swings with the author
One agent writes a premium listing, the next writes three lines, and the property undersells for reasons nobody can name.
Pricing is a gut call
Comps get eyeballed under time pressure, and the number moves depending on which agent you ask.
Offer packets built by hand
Pick the form, fill the fields, hope nobody grabbed the wrong WB. The mistake surfaces at the worst possible moment.
Prep time instead of selling time
Hours per property go to writing, formatting and re-checking, instead of to showings and negotiation.
How it works
How an engagement runs
- 1
Assessment
We map where the hours actually go, then score every loop on volume and error cost.
- 2
Scope one copilot
The highest-leverage loop, fixed in writing: what it does, what it does not, and the number it has to hit.
- 3
Build on your forms and data
Your own forms, MLS fields and templates, with a human review step before anything leaves the office.
- 4
Prove it before you scale
Measured against the step-one baseline. If the number is not there, you hear it from us.
- 5
Operate and extend
We run it, watch for drift, and scope the next loop on plumbing the first one already paid for.
Getting started
No platform rollout. One loop.
Start with a paid assessment and a single copilot on a real workflow. Scale only once the number holds.
01
Book a working session
Show us how your team writes a listing and drafts an offer today. Thirty minutes, no deck.
02
Run a paid assessment
We map every repetitive loop and come back with a scored, priced roadmap you own either way.
03
Ship the first copilot
One loop, fixed scope, measured against your baseline. Scale to the next one only once it earns it.
Frequently asked questions
01Who do you work with?
Residential teams and brokerages where listing and offer volume makes the repetitive work a real cost. Typically 5 agents and up, or one high-volume team.
02Do the copilots write things my clients see without me?
No. Listing copy, offer packets, and follow-ups are drafts. A licensed human reviews and approves before anything leaves your office, and every draft is logged with the inputs it used.
03How is this different from the AI already in my CRM?
Generic tools write generic copy. We build on your forms, your MLS data, and your templates, wire the output into how your team actually works, and measure it against your baseline.
04What does an engagement cost and how long does it take?
It starts with a paid assessment: fixed price, about a week, and you keep the roadmap whether or not you continue. The first copilot is a fixed-bid build scoped from it.
05What if the numbers do not hold up?
We set the target before we build and evaluate against it. If a copilot misses, you get the evaluation report saying so rather than a renewal pitch.
06Who owns what we build?
You own the prompts, configurations, and outputs produced for your brokerage. We reuse our own delivery kits across clients; we do not reuse your data or your content.
AI & automation for real estate teams