Our Work

Everything here is running for real. Ask us anything about it.

These four systems run our founder's own businesses today, which means every claim on this page is one you can press us on in a live call. Read the one that looks most like your problem — each one ends with what the same pattern would do for you.

Standing AI team

Five AI executives run a company's back office

The problem

An owner-operator can hire one person to write the marketing, or one to watch the numbers, or one to keep the build on track — but not all five. So the work that isn't on fire waits, and the recurring work slips first. The real fear underneath: an AI can do a one-off task, but can it actually run a function — show up every day, remember yesterday, and own a result for months?

What we built

A standing team of five scheduled AI executives for our founder's health company: a CMO that drafts content and tracks the pipeline, a CTO that watches the build, a CFO that pulls revenue and flags anomalies, a CRO that reads the other three and sets the week's single most important bet, and a chief of staff that hands over one clear operating order each morning. Each one wakes on a schedule, pulls the live state of its world, writes a dated brief, and passes through a review gate before anything publishes.

The result

Weeks of dated daily briefs on record. In one real week, the CRO noticed that the marketing and product agents had independently flagged the same bottleneck and collapsed five scattered decisions into one batched call. And when a data source is missing, the agents say so — "error, credential not set" — instead of inventing a number.

What this means for your business

The weekly numbers review happens every week. The content pipeline gets drafted on schedule. The "what's the one thing" question gets answered every Monday — without you holding it all in your head. You still approve everything; you stop being the reason it didn't get done.

Automation infrastructure

Scheduled workflows that run without babysitting

The problem

Most automations are scripts on someone's laptop. They work in the demo, then the person leaves, and three weeks later the Monday report quietly isn't there. The fear is reasonable: will this keep running after the builder walks away?

What we built

Our own back office runs on 18 scheduled jobs on an always-on workflow engine — daily operating briefs, weekly reviews, a monthly financial close, research loops, a publishing pipeline. The worker restarts itself if it crashes, failed jobs retry, every run is logged, and a separate watchdog job checks daily that everything that should have fired actually did.

The result

In production for months, refined continuously. One dashboard shows every run: what fired, what succeeded, what failed. The system watches itself and raises a flag when something misses — which is exactly the property a client automation needs to have.

What this means for your business

The recurring things that only happen because someone remembers — the Monday report, the month-end reconciliation, the follow-up that fires when a client hits a status — move onto infrastructure that runs them on schedule and tells you if one ever misses.

Agent-driven research

A 530-source market study in an afternoon

The problem

You want to know what your market actually thinks — the real, unfiltered words people use when they complain, compare providers, and warn each other off. Normally that's weeks of analyst time and an expensive report written in the analyst's voice, not your customers'.

What we built

A research system where coordinated waves of AI agents find the conversations worth reading across Reddit, Trustpilot, the BBB, app stores, YouTube, and consumer-review sites; capture them verbatim with attribution; and synthesize ranked themes — top complaints, unmet needs, what people say about each competitor by name.

The result

The first run captured 530 attributed customer sources and a structured findings report in about three hours, for roughly $150 in compute. A later effort captured nearly 1,400 sources. The output is real enough that quotes from it anchor actual marketing copy today.

What this means for your business

Your competitor and customer research, done in an afternoon, in your customers' own words. You write your website, intake, and ads from real demand instead of guesses — no survey panel, no agency retainer, no waiting.

End-to-end product build

A shipped native iOS app with health data and billing

The problem

Most "tech" you're shown by a vendor is a slide deck or a no-code mockup, and you can't tell whether the person can build the real thing until after you've paid. Slideware looks identical to working software until you try to use it.

What we built

A native SwiftUI health app, built end to end by one operator with AI agents doing most of the engineering: Apple Health integration reading steps, sleep, heart rate, and weight with background sync; an offline queue so no data is lost; a cloud backend; and a full Stripe subscription rail — intro pricing, trials, renewals, failed-payment retries, automatic account creation.

The result

A complete working pipeline — install, connect health data, subscribe, get an account — distributed through TestFlight under a real Apple developer account. Shipped software, not a concept.

What this means for your business

If your project needs someone who can take an idea all the way to a working product — the app your customers use, the payment that lands in your account, the data that flows without staff re-typing it — you're hiring a builder who has already done it, not a consultant who hands you a plan and disappears.

Which of these maps to your problem?

Bring it to a free 30-minute teardown and we'll map what the same pattern would look like in your business.

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