Electrical contractors-grade semantic search (RAG), shipped by people who've done it before.

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

Most electrical contractors 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 an electrical contractor is paying for the same problem to be solved twice.

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 friction electrical contractors hit that other industries don't.

  • Electricians juggle callouts, compliance certificates, and quoting, usually from the front seat of a van.
  • Certificates of compliance and quote turnaround are where electrical businesses either look professional or lose the job.
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How we build semantic search (RAG) for electrical contractors.

We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for an electrical contractor 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 electrical contractors

What changes for electrical contractors after this lands: the work that used to need a person stays done, the work that needs a person gets done with their attention undivided. 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

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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.

Try the calculator

*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

What's the realistic timeline for semantic search (RAG) with an electrical contractor?

Most electrical contractors 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 electrical contractor?

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 electrical contractors?

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.

Sketch this with us.

We'll map your real workflow before quoting anything.

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.