Case studies: applied AI, documented in public
SI1 recommends methods it is already using. Each pillar has a live proof case, built and measured in the open, so you can see what AI did, what stayed human, and what the numbers say.
Christian Ganaban / ganaban.com
Before offering Personal Intelligence to anyone else, SI1 is applying the method to its own founder, in public.
Proves the person · Read the case study →Domestic Robot
A new Australian publication about home robots, researched, branded, built and launched with AI as part of the founding operating model.
Proves the build · Read the case study →Melbourne venue group
AI brought into an established multi-venue business under real commercial pressure, one workflow at a time.
Proves the transformation · Read the case study →SI1 itself
The practice itself is a case study: set up with AI, for almost no new spend, with the hiccups recorded.
Turns the lessons into a system · Read the case study →Each case proves one thing.
Together they show the full range of SI1's work: a person, a new business, an established organisation, and the system that ties them together.
- The person.
- Christian Ganaban proves Personal Intelligence: an identity search engines and AI assistants describe accurately.
- The transformation.
- A Melbourne venue group proves Operational Intelligence: AI working inside a business that is already running.
- The build.
- Domestic Robot proves Business Intelligence: a new business researched, built and launched with AI.
- The system.
- SI1 turns the lessons into playbooks, templates, agents and training others can use.
How we document.
Case studies are only useful if you can trust them. These rules apply to every one.
- DatedEvery decision and milestone is logged with the date it happened.
- Real numbers onlyMetrics come from real sources such as Search Console, analytics, affiliate dashboards and invoices. Estimates are labelled. Nothing is rounded up.
- AI and human, separatedEach case says what AI did and what a person decided, checked or approved.
- Failures includedChanges of direction and things that went wrong are recorded alongside the wins.
- Baselines firstStarting numbers are captured at launch, then reported monthly.
- Privacy keptBusinesses that haven't agreed to be named are anonymised, and no private data is published.
Start with one conversation about where AI fits in your business.
We'll look at how you work now, where the time goes, and which opportunities are worth pursuing first. You leave with a short written summary either way.