Whakatāne businesses don't need another generic AI pitch. AI knowledge base 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 Bay of Plenty.
Internal AI knowledge base - wired into a Whakatāne workflow, not bolted on the side.
Our goal is to give Whakatāne businesses a three-day weekend, so people can spend more time with their families and the people they love :)
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
Without Kiwi Dynamics
With Kiwi Dynamics
What you actually get
Every engagement is scoped and quoted up front. This is what is in the box.
- A working pilot, in productionNot a prototype on someone's laptop. The first slice of AI knowledge base runs against real work within weeks.
- Your data stays yoursIt runs on your accounts and your tools. If we part ways you keep the system and everything in it.
- The workflow mapped before codeWe write down what good looks like for Whakatāne businesses first, so nobody is guessing at handover.
- Support after it landsThe people who built it stay reachable when the business changes shape around it.
How AI knowledge base compares
The two things most businesses do instead, and where each one runs out.
| Hiring for it | An off-the-shelf tool | Kiwi Dynamics | |
|---|---|---|---|
| Fit to how you work | Fits perfectly, costs a salary | You bend your process to suit the tool | Built around the workflow you already run |
| Time to something useful | Immediate, and permanent | Quick to switch on, slow to make fit | A working slice in weeks, then hardened |
| Who owns the data | You do | The vendor, on the vendor's terms | You do, in your own accounts |
| When it breaks | That person sorts it, if they are in | A support queue and a ticket number | The people who built it |
| What it costs | A salary, every year, forever | Per seat, forever, used or not | Scoped and quoted up front |
The pattern across Whakatāne engagements we've shipped.
- Eastern Bay of Plenty runs on horticulture, aquaculture, and Māori-led enterprise - AI here works when it respects relationships first.
- Kiwifruit, aquaculture, marine tourism, and a strong iwi economy. AI tools that work offline and bilingually find their home here.
We work with teams across Whakatāne: Whakatāne · Ōhope · Kawerau · Edgecumbe · Murupara · Ōpōtiki.
Talk to us about this →
How we build AI knowledge base for a Whakatāne team.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your Whakatāne business, so value lands before the build is finished. Internal AI knowledge base.
Talk to usHow the work runs
- Find the one workflowWe look for the job costing Whakatāne businesses the most hours or the most leads, and deliberately ignore the rest for now.
- Ship a working sliceA narrow version goes into production in weeks, against real work, so the value shows up before the build is finished.
- Prove it, then widenWe measure it against what the work cost before. If it does not pay for itself, we say so rather than scaling it.
- Harden and hand overLogging, fallbacks and a real handover, so it keeps running when we are not in the room.
The outcome for Whakatāne teams
The shape of the result for Whakatāne 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
*Every engagement is scoped and quoted up front. Results vary by workflow and business.
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 Whakatāne 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.
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. New staff get to productive 3x faster - less senior-team interruption.
What tools do you build AI knowledge base on?
For AI knowledge base we usually reach for Claude, Pinecone, Vercel AI SDK, Postgres, MCP. We're tool-agnostic at heart - we pick what your Whakatāne team can actually run after we hand the build over, not what looks good on a vendor sticker.
Twenty minutes, your call.
You describe what's broken. We'll tell you what we'd actually do about it.
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.