A data product: 17,000 engagement data points turned into one answer per query.
A data-driven tool that tells content creators the best local time to post when their audience is in another country. Built on 17,000+ engagement data points across 8 platforms, with Google Gemini collapsing the dataset into a single recommendation per country-and-platform query.
Peak engagement advice on the internet is a blog post written once, about one country, and never updated. The genuinely hard part is not finding the data. It is time zones. A creator in Colombo targeting Los Angeles needs the answer expressed in their own local clock, across a platform whose peak differs by weekday, with daylight saving applied correctly on both ends. Get that arithmetic wrong and the tool is confidently, invisibly useless.
Aggregate before you infer
17,000+ data points across 8 major platforms collected and normalised into a single baseline of engagement patterns, so the model reasons over structured data instead of hallucinating from a prompt.
Gemini as a reducer
The LLM's job is to collapse a large, noisy dataset into a country-specific recommendation, a task it is actually good at, rather than to be the source of the numbers.
Time zones as a first-class concern
Every answer is converted into the creator's local clock with daylight saving handled on both sides, because that conversion is the entire value of the product.
One question, one screen
Pick a target country and a platform, get an actionable answer. No dashboard, no onboarding, no account.
How it is put together
Dataset
17,000+ normalised engagement observations across 8 platforms
Inference
Gemini used as a structured reducer over the dataset, not as the data source
Time engine
Target-country peak to creator-local clock, DST-correct on both ends
Delivery
Next.js on Vercel, statically rendered where the answer is stable
The calls worth defending
Asking an LLM 'when should I post in Germany' produces a confident answer with no provenance. Giving it a normalised dataset and asking it to summarise produces an answer that traces back to something. The distinction is the whole architecture.
What shipped
SocialTimetable
Landing and query entry
Best-time finder
Country and platform to a creator-local posting window
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