We've worked with enough operators in San Jose to know that the brief that arrives in our inbox is rarely the brief that ends up shipped. The first thing we do on any AI compliance monitoring project is sit with your team for a day before we propose anything.
Built and supported here - the way a San Jose business would actually use it.
Our goal is to give San Jose businesses a three-day weekend, so people can spend more time with their families and the people they love :)
What AI compliance monitoring actually does
AI that watches your forms, calls, contracts, and emails for compliance risk - Health & Safety, Privacy Act, Fair Trading, FMA. Flags issues before regulators or lawyers find them.
- 01 Reviews documents and recordings against your obligations
- 02 Risk scoring with explanations a manager can act on
- 03 Auto-redacts personal info in records you share externally
- 04 Audit-ready logs for WorkSafe, FMA, or Privacy Commissioner
Built on: Claude Vercel Postgres AWS S3
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 compliance monitoring 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 San Jose 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 compliance monitoring 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 |
Where San Jose operators actually lose hours.
- San Jose sits in the middle of Silicon Valley, where the AI bar is set by the companies inventing it - AI here has to be genuinely production-grade, not a wrapper on a public API.
- The commercial and cultural centre of Silicon Valley, surrounded by the companies that build the models everyone else uses. San Jose businesses expect AI built with real engineering discipline, because they can tell when it isn't.
We work with teams across San Jose: Downtown San Jose · Santana Row · Willow Glen · North San Jose · Almaden Valley · Berryessa.
Talk to us about this →
How we build AI compliance monitoring for a San Jose team.
We scope narrow, ship a working pilot, then harden it into production. The first slice is the highest-leverage workflow for your San Jose business, so value lands before the build is finished. AI compliance + audit.
Talk to usHow the work runs
- Find the one workflowWe look for the job costing San Jose 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 San Jose teams
Compliance review effort cut 70% with fewer escalations. For San Jose teams, that almost always shows up as fewer interruptions and a calmer week, not a dashboard chart.
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
What's a typical engagement length for San Jose businesses?
Six to twelve weeks for the build, then a short managed-services month while the system goes from "shipped" to "owned by your team". After that you keep us on retainer if you want, or take it from there yourself.
Are there hidden costs we should plan for?
Three to know about: model/API spend (which we set up under your own account, not ours, so you see and control it), any new SaaS subscriptions we recommend, and your team's time during rollout. We surface all three in the quote so there are no surprises.
Anyone else in this space using AI compliance monitoring?
Plenty. Compliance review effort cut 70% with fewer escalations. 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.
Can you work with our existing systems?
Yes. The default AI compliance monitoring stack we reach for is Claude, Vercel, Postgres, AWS S3, but we'll bend it around whatever you already run - Xero, HubSpot, Shopify, Cin7, your own in-house apps. The discovery week maps every data source before any build starts.
Worth a conversation?
Even if you don't end up working with us, you'll leave the call knowing what's worth building.
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.