How It Works
I build practical AI solutions for small and medium businesses — tailored to your workflows, your data, and the specific problem you're trying to solve.
The Approach
Many businesses buy off-the-shelf AI tools and spend months trying to make them fit. I work the other way around: I start by understanding your problem, your data, and your workflows, and then build a solution designed around them.
The result is something your team can actually use, that solves the real problem, and that doesn't require a data science department to maintain.
Problems I Solve
These are the kinds of challenges businesses bring to me. Each maps to a capability I've built and proven in practice.
Scheduling, data entry, report generation, stock tracking — manual work that repeats every day or week. You don't need a research project, you need it automated.
Automate your documentsSales figures, operational logs, customer records — the information exists, but there's no pipeline turning it into decisions you can actually make.
Make better decisionsSomeone on your team re-enters the same data in two places every day. A spreadsheet exists just to bridge a gap between systems. That's fixable.
Automate your reportingYour weekly or monthly reports are assembled manually — pulling numbers from different places, formatting them, sending them out. That whole cycle can run itself.
Automate your reportingInvoices, order forms, delivery notes — your team reads them, types the data somewhere else, and files them. Every step of that can be automated.
Automate your documentsYour problem is specific enough that generic software doesn't cover it. You need something built around your situation — not the other way around.
Custom BuildProcess
Every engagement follows the same progression — from understanding your problem to a working solution you fully own.
I map your problem, your data, your existing tools, and what success looks like. No assumptions, no skipping ahead.
I propose what gets built, how it integrates, and what the end result looks like in your hands — before writing a line of code.
I build iteratively with regular check-ins. You see progress early and often, not just at the end.
Full documentation and a walkthrough so you understand exactly what was built and how to run it. No dependency on me to keep the lights on.
Engagement Models
Every business is different. Here are four ways to engage, depending on what the problem and timeline demand.
A clear problem, a clear output. We scope it together, agree on a price, and I deliver. Works best when the problem is well-understood and the success criteria are specific.
Best for: Automation systems, document processing, dashboards, reporting pipelines
When you know there's a problem but aren't sure what the solution looks like yet. I investigate, prototype, and validate before committing to a full build.
Best for: Businesses new to AI, feasibility questions, unclear problem definitions
I join your team for a defined period — working alongside your people, in your stack, on your priorities. Useful when you need technical depth without a permanent hire.
Best for: In-progress projects, capability gaps, short-term technical needs
A reserved capacity arrangement for businesses that need recurring support, system maintenance, or continued development beyond a first project.
Best for: Evolving systems, long-term integrations, continuous improvement
Why Custom?
Generic AI products are built to work for the average use case. If your problem is straightforward, they're fine. But when your data is specific, your workflow is unusual, or the stakes are high, averages don't cut it.
Custom-built means the solution is trained on your data, designed for your users, and integrated with your systems — not the other way around.
Discuss Your ProjectTell me what you're working on. If it's a good fit, I'll say so. If not, I'll point you in the right direction.
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