Automation that gives business owners their time back
“My team retypes the same information into three systems, and the report everyone needs takes a day to put together.”
Most businesses don't need an AI strategy deck. They need the Tuesday-afternoon busywork to stop: copying a new lead from the website into the CRM, re-keying invoices, assembling the same report every week by hand.
I start there. The first wins are usually plain automation between systems you already pay for. AI earns a place where the work needs reading, summarizing, or judgment, and even then it gets a second step that checks the result before anyone relies on it.
How the work goes
Find where the hours go
We walk through the work as it really happens, not as the process chart says it does, and rank tasks by time lost and risk of error.
Automate the verifiable parts first
Anything with a clear right answer gets automated and tested against real records before it touches production.
Add AI where judgment helps
Language models handle reading, drafting, and classification, with a separate validation step and a human in the loop where it matters.
Hand over something you can run
You get monitoring, logs that explain failures, and documentation written for the person who maintains it next.
Where I've done this
Built a multi-agent pipeline that turns a plain-English report request into validated SQL, with separate agents for requirements, retrieval, drafting, and checking. See more
Built Client Hub, a customer-intelligence service that collects leads and bookings from multiple websites into one database with an API. See more
Run automations daily across my own companies for operations, notifications, and data movement between systems.
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Common questions
Do I have to replace the software I use now?
Rarely. Most of the value comes from connecting the systems you already have. Replacement only makes sense when a system can't expose its data at all.
What happens when the AI gets something wrong?
It will, sometimes. That's why every AI step I build has a check behind it: a validation rule, a second agent, or a person approving the result before it goes anywhere important.
Where does my data go?
That's a design decision we make up front. Sensitive work can run on AI models you host yourself so the data never leaves hardware you control.
How big does a first project need to be?
Small is better. One painful workflow, automated and measured, tells you more than a six-month roadmap.
Tell me what's slowing the business down.
Describe the problem in plain terms. I read every message myself and reply when there's something I can genuinely help with.
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