Semantic search (RAG) that lives in your stack, not on a vendor's roadmap. Shipped from Texas.

Our goal is to give Austin businesses a three-day weekend, so people can spend more time with their families and the people they love :)

Austin businesses don't need another generic AI pitch. Semantic search (RAG) only earns its keep when it's built around the workflow you actually run on a wet Tuesday, and that's how we scope every engagement we take on in Texas.

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

What you actually get

Every engagement is scoped and quoted up front. This is what is in the box.

How semantic search (RAG) compares

The two things most businesses do instead, and where each one runs out.

 Hiring for itAn off-the-shelf toolKiwi Dynamics
Fit to how you workFits perfectly, costs a salaryYou bend your process to suit the toolBuilt around the workflow you already run
Time to something usefulImmediate, and permanentQuick to switch on, slow to make fitA working slice in weeks, then hardened
Who owns the dataYou doThe vendor, on the vendor's termsYou do, in your own accounts
When it breaksThat person sorts it, if they are inA support queue and a ticket numberThe people who built it
What it costsA salary, every year, foreverPer seat, forever, used or notScoped and quoted up front

The pattern across Austin engagements we've shipped.

  • Austin is the tech and startup capital of Texas, and every business here has already seen an AI pitch - AI that ships is the only kind that gets taken seriously.
  • A dense startup and venture scene, major tech company offices, and a live-music and hospitality economy layered on top. Austin teams have high AI literacy already, so the bar is a working product, not a pitch deck.

We work with teams across Austin: Downtown Austin · South Congress · East Austin · The Domain · Round Rock · Cedar Park.

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How we build semantic search (RAG) for an Austin team.

We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Austin business, so value lands before the build is finished. AI search over your data.

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How the work runs

The outcome for Austin teams

The shape of the result for Austin teams: Average search time drops from 6 minutes to 12 seconds. Built on Pinecone, 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.

FAQ

How quickly can we see something running?

Week three for a clickable internal demo against real data. Week six for a slice your team can actually use. We hold ourselves to those numbers because they're what stops a project drifting into "endless discovery".

What's the smallest engagement you'd take on?

A two-week paid discovery for Austin businesses that aren't sure whether the build is worth doing at all. You get a one-page write-up of what we'd build, what we'd skip, and what it would cost. About 30% of those discoveries end with us recommending you don't proceed.

What's the realistic outcome for Austin businesses?

Average search time drops from 6 minutes to 12 seconds. We don't promise tenfold lifts because we don't see them outside of marketing decks.

What tools do you build semantic search (RAG) on?

For semantic search (RAG) we usually reach for Pinecone, Claude, Postgres pgvector, Vercel AI SDK. We're tool-agnostic at heart - we pick what your Austin team can actually run after we hand the build over, not what looks good on a vendor sticker.

One reply, one direction.

We don't run sequences or follow-up automation. One useful answer, one decision on your side.

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.