Most real estate agencies we talk to aren't short of dashboards or tools – they're short of an hour back in the week. That's the lens we put on semantic search (RAG): not a tech showcase, but a careful look at the one or two workflows where a real estate agency is paying for the same problem to be solved twice.
Real estate agencies · Applied AI
Built for the real estate agency who's already tried the off-the-shelf option and bounced off it.
What semantic search (RAG) actually does
Search that understands intent, not just keywords. Your team types what they mean – and gets the right document, ticket, or product from across every system, with citations.
- 01 Indexes Drive, SharePoint, Notion, Slack, your CRM
- 02 Returns answers with source links – no hallucinations
- 03 Permissioned so staff only see what they should
- 04 Re-indexes nightly so results stay fresh
Built on: Pinecone Claude Postgres pgvector Vercel AI SDK
Without Kiwi Dynamics
With Kiwi Dynamics
What gets in the way
The friction real estate agencies hit that other industries don't.
- 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.
How we build semantic search (RAG) 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. AI search over your data.
Talk to usThe outcome for real estate agencies
If we build the right slice first, real estate agencies feel the difference inside the first month. Average search time drops from 6 minutes to 12 seconds.
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
*Every engagement is scoped and quoted up front. Results vary by workflow and business.
Questions
FAQ
What's the realistic timeline for semantic search (RAG) with a real estate agency?
Most real estate agencies have their first usable slice in week 5 or 6. We'd rather ship narrow and real than broad and aspirational – your team gets to use the thing well before the engagement is "done".
Is semantic search (RAG) worth it for a smaller real estate agency?
Often, yes – and counterintuitively the ROI is sometimes faster than for the big end of town because there's less integration overhead. We'll tell you honestly on the scoping call if it isn't.
Do you have proof this works for real estate agencies?
Direct case study: Average search time drops from 6 minutes to 12 seconds. Happy to walk you through full numbers on a call.
What happens if we want to swap a vendor out later?
Semantic search (RAG) is built behind a small adapter layer specifically so swapping a model provider or a data source is a one-day job, not a re-architecture. Pinecone, Claude, Postgres pgvector, Vercel AI SDK are our defaults, but the build is intentionally portable.
One reply, one direction.
We don't run sequences or follow-up automation. One useful answer, one decision on your side.
Get in touch
Talk to us about this
Tell us what you're trying to do and we'll reply with how we'd build it — no obligation.