AI knowledge base designed around the way a Singapore team actually runs.

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

Singapore sits in a regional context that genuinely changes the build. Connectivity assumptions, the rhythm of the working week, the proximity of your team to your customers - none of those are details our default AI knowledge base template would catch.

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 Singapore.

  • Singapore has one of the highest AI adoption rates in the world, and the CBD runs on banking, wealth management and regional HQ operations - AI here has to meet a market that's already fluent in it.
  • Home to the regional headquarters of most major global banks and a dense wealth management sector, sitting inside a government that's pushed AI adoption harder than almost any other country. Singapore businesses expect AI that's precise, compliant and genuinely production-ready, not a pilot.

We work with teams across Singapore: Raffles Place · Marina Bay · Shenton Way · Tanjong Pagar · City Hall.

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How we build AI knowledge base for a Singapore team.

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

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How the work runs

The outcome for Singapore teams

We'd call the engagement a success when Singapore teams are using the system without thinking about us. New staff get to productive 3x faster - less senior-team interruption.

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

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".

Is AI knowledge base worth it for a smaller Singapore?

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.

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 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 Singapore team can actually run after we hand the build over, not what looks good on a vendor sticker.

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.