AI knowledge base that lives in your stack, not on a vendor's roadmap. Shipped from California.

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

The reason we take on work in Oakland is that the businesses here tend to be sharper about what they want than the brief lets on. AI knowledge base for an Oakland team almost always ends up looking different to AI knowledge base for a downtown Auckland one.

What AI knowledge base actually does

Your team's tribal knowledge, finally searchable. Upload your SOPs, training videos, past emails, and Slack threads - your team asks questions and gets answers with citations.

  • 01 Ingests PDFs, Word docs, videos, Slack, Notion, Drive
  • 02 Answers with citations back to source documents
  • 03 Permission-aware - staff only see what they should
  • 04 Detects stale docs and prompts owners to update

Built on: Claude Pinecone Vercel AI SDK Postgres MCP

What you actually get

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

How AI knowledge base 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

What we keep seeing in Oakland.

  • Oakland runs on logistics, healthcare and a wave of businesses priced out of San Francisco - AI here means Bay Area capability without Bay Area rent.
  • One of the busiest container ports on the West Coast, a major hospital network, and a growing tech and creative scene that moved across the bay for the rent. Oakland businesses want the same AI rigor as San Francisco without the San Francisco price tag.

We work with teams across Oakland: Downtown Oakland · Jack London Square · Temescal · Fruitvale · Rockridge · West Oakland.

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How we build AI knowledge base for an Oakland team.

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

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How the work runs

The outcome for Oakland teams

The shape of the result for Oakland teams: New staff get to productive 3x faster - less senior-team interruption. Built on Claude, 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.

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 AI knowledge base with an Oakland?

Most Oakland businesses 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".

What does AI knowledge base cost for an Oakland?

Pilots start from a fixed scope priced to land a measurable result inside 6 weeks. Pricing depends on data volume, integration complexity, and whether you need us on managed services afterwards. We'll quote precisely after a 30-minute scoping call.

Anyone else in this space using AI knowledge base?

Plenty. New staff get to productive 3x faster - less senior-team interruption. The interesting question is rarely "does it work" - it's "is your team ready to use the output." That's what we'd scope on the call.

What happens if we want to swap a vendor out later?

AI knowledge base 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. Claude, Pinecone, Vercel AI SDK, Postgres, MCP 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.