SMB AI Implementation
AI applied to your back office the way we apply it to ours — automated categorization, close checks, reporting, and AI assistants connected safely to your accounting data.
Why buy this from an operator, not a consultant
Most SMB "AI transformation" advice comes from people who have never run a back office with it. We're practitioners. Our own firm runs on AI every day: automated transaction categorization, a 20-check automated close, AI-generated reporting packs, and AI assistants wired to live QuickBooks data through our own API platform. We sell what we operate.
The shape we implement is automation with a human touch. The machine handles the volume and stops the line when something looks wrong; a human reviews the exception, not the whole pile. That is exactly the right shape for finance AI: it should do the 95% that's pattern, and route the 5% that's judgment to a person. Fully manual and fully autonomous are both the wrong answer for money.
The failure mode is buying an "AI strategy." The success mode is picking one workflow that eats real hours — categorization, AR follow-up, close checks, report assembly — automating it, measuring the hours recovered, and expanding from there. That's the firm's namesake in practice: kaizen, small improvements, compounding, every month.
What's included
- Back-office workflow audit — where the hours actually go
- Automated transaction categorization with a rules engine plus AI review
- Automated close checklists and data-quality scans that run themselves
- AI-assembled monthly reporting
- AR follow-up and inbox/document automation
- AI assistants connected to your QuickBooks data with scoped, read-only-by-default keys
- Staff training on safe day-to-day AI use
- Measurement — hours recovered and defect rates, tracked monthly
How Kaizen runs it
Every engagement starts as a fixed-scope first project. We pick the one workflow with the biggest hour drain, automate it, verify it against a month of parallel run, and hand it over documented. If you'd rather we run it than own it, an optional monthly operations layer keeps the stack tuned and measured.
The security posture is non-negotiable and specific. Connections to your accounting data go through scoped API keys — read-only unless you grant more — every action is audit-logged, data passes through rather than being stored, and nothing is trained on your books. The same platform is available as a product — the Kaizen API — for firms that want to connect Claude or other AI tools to QuickBooks themselves.
Pricing
Frequently asked questions
Is my financial data safe?
Connections use scoped keys (read-only unless you grant more), every action is audit-logged, data is passed through rather than stored, and your books are never used to train models.
What tools do you implement?
Claude and the modern AI stack, connected to QuickBooks Online, Ramp, and Gusto via our own API platform, plus rules engines for the deterministic work — the tool follows the workflow, not the other way around.
Do we need technical staff?
No. We build, document, and train, and can operate the stack monthly if you'd rather not own it.
What's a typical first project?
Automated categorization plus close checks is the most common; AR follow-up automation and report assembly are close behind — all three pay back in recovered hours within a quarter.
Related services
Free automation audit
Twenty minutes on where your team's hours actually go — we'll tell you which workflow to automate first and what it would recover.
Or call us directly: +1 786 789 0969