Real estate agencies · Applied AI

Ask your data in English, built around how a real estate agency actually works.

There is a version of AI data analytics that real estate agencies buy off a shelf and quietly stop using inside a month. Then there's the version that's wired into your real workflow, owned by a person on your team, and still in use a year later. We only build the second one.

What AI data analytics actually does

Stop digging through dashboards. Ask plain-English questions of your sales, jobs, and customer data – get charts, summaries, and the why behind the numbers in seconds.

  • 01 Natural-language queries over your Xero, Shopify, CRM data
  • 02 Weekly auto-summaries delivered to inbox or Slack
  • 03 Anomaly detection – flags weird weeks before you notice
  • 04 Forecasts that explain themselves, not black boxes

Built on: DuckDB Claude Metabase BigQuery Vercel AI SDK

Why real estate agencies are different

Real estate agencies run their businesses unlike anyone else.

  • Agents live on their phones between open homes, listing enquiries, and vendor updates that can't wait until Monday.
  • Lead response speed decides who gets the listing, and most agencies lose leads simply because nobody replied fast enough.
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How we build AI data analytics for real estate agencies.

We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for a real estate agency business, so value lands before the build is finished. Ask your data in English.

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The outcome for real estate agencies

The shape of the result for real estate agencies: Owners check the business in 2 minutes instead of 2 hours. Built on DuckDB, hardened with the rest of the stack as it scales.

Not your typical AI agency.

Honest about what AI can and cannot do

Ships the one workflow that pays for itself

Hours given back, never the size of the invoice

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*Every engagement is scoped and quoted up front. Results vary by workflow and business.

How much is not automating costing you?

Nine hours a week of admin is 468 hours a year. With Kiwi Dynamics, that drops to about 52.

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*Based on 9 hours a week of admin at Kiwi Dynamics' typical 80% automation rate. Your number may vary, the calculator uses your own.

Questions

FAQ

What's a typical engagement length for real estate agencies?

Six to twelve weeks for the build, then a short managed-services month while the system goes from "shipped" to "owned by your team". After that you keep us on retainer if you want, or take it from there yourself.

Do you do hourly billing or fixed price?

Fixed price for the pilot, every time. After that it's your call – fixed price per milestone or a small monthly retainer for ongoing iteration. We don't run open-ended T&M because it disincentivises us from finishing.

Can you walk us through a comparable build?

Yes – on the first call we'll pick the closest engagement we've shipped to what you're describing and walk through the outcome, the headcount and the time it took. Owners check the business in 2 minutes instead of 2 hours.

Can you work with our existing systems?

Yes. The default AI data analytics stack we reach for is DuckDB, Claude, Metabase, BigQuery, Vercel AI SDK, but we'll bend it around whatever you already run – Xero, HubSpot, Shopify, Cin7, your own in-house apps. The discovery week maps every data source before any build starts.

Ready to talk specifics?

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Tell us what you're trying to do and we'll reply with how we'd build it — no obligation.