How I Built a Multi-Language SEO Funnel

Lanami was an experiment in rule-based MT5 breakout tools and multilingual search-led distribution. We have sunset the project; this is a retrospective, not a current product offering.

Project status: sunset

We tried Lanami, Vdea, and AquaClash and have since sunset all three. They are no longer active products. These pages remain as a record of what we built and learned.

The multilingual system we built

For Lanami, we explored a search-led content system using Next.js and version-controlled JSON. Each page had a stable content identity, language-specific copy and a localized path. A compiler turned the simple content into reusable page sections.

Why explicit relationships mattered

The architecture connected equivalent pages through a stable mainPage key, locale indexes and hreflang. Internal links were meant to respect the visitor’s language. Metadata, canonical URLs and the content hierarchy needed to agree.

The intended route was search query → useful article → project context → product explanation. The architecture made those relationships explicit; it did not guarantee traffic or conversions. Translation still needed editorial review rather than simply generating more pages.

What remains useful after sunset

We have since sunset Lanami. The useful lesson was the need to keep routing, content identity and metadata aligned as a site grew. Ideas such as better internal linking and conversion measurement remained possible improvements to that experiment, not an active roadmap for Lanami. The current portfolio applies the same care to clearly connected project pages and articles.

Lanami

Lanami was an experiment in rule-based MT5 breakout tools and multilingual search-led distribution. We have sunset the project; this is a retrospective, not a current product offering.

Current projects

Practical products across AI, learning and logistics, alongside a personal hobby in Chiang Mai. Explore what each project does and the thinking behind it.