I'm launching Kehai here on Saturday, October 10. It's cookieless web analytics, and the part I most want opinions on is the forecast.
It forecasts one outcome: a goal's completions or its net revenue. Before it answers, it tests itself on your own history against the simplest baseline there is, repeating last week, and shows its skill and how often its 80% band actually held next to the number. With too little history it refuses and says what's missing.
My question to people who read dashboards for a living: what would you need to see before you'd act on a forecast like that? And is there a number in your current tool you've stopped trusting?
The demo is open without an account if you'd rather look first: https://kehai.io/sign-in?demo=1
Kehai is cookieless web analytics hosted in the EU. Reports are counted from recorded events without sampling, and imported or modeled numbers keep their own labels. The forecast tests itself on your history and shows its error next to the answer. Pacing tells you mid-month whether a target is still in reach. Sales and refunds come from the shop itself, AI referrals and bots get their own reports, and a read-only MCP server lets your assistant ask.
