AI implementation
Put AI to work in your product and your team
AI features in your mobile app, AI agents in your workflows, and an AI development process for your engineers. Built the way I run my own business: agents that read, propose and prove their work.
AI that ships, not AI that demos
Most AI projects stall between the demo and the real work. The model is impressive; nobody trusts its answers, nobody knows what it costs, and nobody can say what happens when it is wrong.
I build the part that closes that gap: the harness around the model. What it can read, what it may do, how its work is checked, and what a person still decides. It is the same harness I run my own business on, every day.
Four ways I implement AI
AI features in your mobile app
Assistants, smart search, summaries and automation inside your Android or iOS app: grounded in your data, with answers that cite their source and a cost you can see.
AI agents in your workflows
Agents that take the repetitive work in support, sales, operations or reporting. They read through typed tools and propose changes; your team approves them in one click.
An AI SDLC for your dev team
Spec-first development with coding agents, AI code review that reads the files, not just the diff, tests written alongside, and a human merge. Faster delivery without losing control.
The harness: evals, guardrails, metering
Daily evals, guardrails in code, a ledger of every model call, privacy by design. The part that makes AI safe to depend on, in your product and your company.
Small pilot, proven, then scale
No big-bang transformation. One workflow that works, measured, then the next.
- 1MapWe find the workflow or feature where AI saves the most time or money, and decide what the AI does and what a person decides.
- 2PilotA working version in weeks, on your real data, with the guardrails in from day one: read-only tools, proposals you approve.
- 3ProveEvals, cited answers and a cost per call. We keep what the numbers support and cut what they don't.
- 4Scale and hand overRoll it out to the team, document it, and leave you a system your engineers can own.
I run my own business on this
These are not client case studies with borrowed numbers. They are the AI systems I build and use myself, every day.
9
AI agents in my command center
10
AI teammates in my content team
10+
Years building mobile apps
3M+
App downloads
Questions I get about AI
Where do we start?
With one workflow or one feature that costs you real time or money today. We map it, decide what the AI does and what a person still decides, and build a pilot you can measure. One thing that works beats a strategy deck.
Can AI work with our existing app and tools?
Yes. The AI layer sits on top of what you have: your app, your backend, your database, your issue tracker. It gets typed, read-only tools first; anything that changes data goes through a step a person approves.
Will the AI make changes on its own?
Not by default. In the systems I build, agents read what they need and propose changes; a person accepts them. Automation that acts alone is earned per workflow, with limits, logs and a way to switch it off.
How do you keep it reliable?
Evals that run every day, answers that cite their sources, a ledger of every model call with its cost, and guardrails written in code rather than in a prompt. If a check can't prove something works, it isn't done.
What about privacy and our users' data?
An explicit allow-list decides what an AI may see at all. Sensitive data is read on demand, only by the one agent that needs it, and never leaves in a log or a prompt it doesn't belong in.
How long does it take?
A focused pilot usually takes a few weeks; a production rollout across a team takes longer and depends on your stack. We agree the scope and the first measurable result before any build.
Is this a mobile project or an AI project?
Often both. I have been building native Android and iOS apps for 10+ years, so AI features land inside a real mobile architecture: offline states, performance, store rules and all.
Ready to put AI to work, safely?
Tell me the workflow or feature you have in mind. I'll tell you honestly whether AI is the right tool for it.