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Automate the repeatable work. Use AI where it earns trust.

I build practical automations, integrations, reporting loops, and AI-assisted workflows that remove manual work without handing your business to a black box.

Most automation wins do not need AI

If the work is rules-based, scheduled, repetitive, or data-driven, it probably needs a reliable automation — not a language model.

  • Pulling reports on a schedule
  • Applying payroll or commission rules
  • Sending reminders
  • Routing form submissions
  • Syncing data between systems
  • Generating PDFs
  • Logging approvals
  • Notifying the right person when something changes

AI belongs where the work involves language, context, or judgment support — and even then, the system should be bounded, logged, and reviewable.

What this is for

The work your team keeps doing manually:

  • Weekly reports that require exports, cleanup, and copy/paste.
  • Payroll or commission calculations that live in fragile spreadsheets.
  • Client follow-up that depends on someone remembering.
  • Data that gets entered into two or three systems.
  • Documents, notes, or messages that need to be summarized, tagged, or routed.
  • Recurring tasks that should happen the same way every time.
  • Owner approvals that need a paper trail.
Three layers

Automation is not the same thing as AI. AI is one tool in the box — not the default answer.

Layer 01

Rules-based automation

Scheduled jobs, webhooks, data syncs, report generation, PDF creation, notifications, and approval logs. No AI where no AI is needed.

Layer 02

Workflow integrations

Connecting the tools your business already uses: booking platforms, CRMs, project tools, email, forms, spreadsheets, databases, and dashboards.

Layer 03

AI-assisted operations

Summarization, research, document review, note cleanup, message drafting, task routing, and bounded agents with human approval for anything consequential.

No black-box automation

Every serious automation should answer:

  • What triggered it?
  • What data did it use?
  • What did it change?
  • Who approved it?
  • What happens if it fails?
  • Can a human override it?

If the answer is unclear, the automation is not ready.

Examples
Where I'd start instead

AI won't fix a process that isn't clear yet.

If the process is broken, automation just makes the mess faster. So we figure out what should happen, who approves it, and where the record lives first — which usually starts by mapping how the work runs.

Next step

Have a recurring process that should not require you anymore?

Let's map the loop, decide whether it needs rules, integration, AI, or all three, and build the smallest reliable version first.

Talk about automation