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Hey StartupBase! I built Ember because I kept forgetting the small things people told me - a friend's surgery date, what my nephew is into now, who just changed jobs. Contact apps store phone numbers; nothing helped me remember the human stuff.

With Ember you just type one sentence and the AI (we call it Keeper) files it under the right person. Ask later "what should I ask Mai about?" and it answers from everything you saved. Gentle reminders nudge you before birthdays or when you have been out of touch too long.

It is free to start on iOS and Android, and StartupBase folks get 1 month of Pro free with code SBASE-EMBER. Would love your feedback - especially on what would make you trust an app with this kind of personal data.

Geo link targeting plus UTM builder in the same tool is a smart combo - running region-specific store links (App Store vs Play Store by country) usually means chaining a shortener with a separate redirect service, so having it in one place with analytics attached saves real setup time. One question: on the privacy-first tracking, does that mean cookieless attribution? Curious how accurate the geo and device breakdowns stay without cookies.

The natural-language trigger examples are what stand out here - "update Salesforce based on recent customer emails" is exactly the kind of glue work that eats an hour a day and never gets automated, because setting up a traditional workflow builder takes longer than just doing the task. How do you handle mistakes though? If the AI mis-parses an email and writes wrong data into the CRM, is there a review step or an undo?

Consolidating feedback, support, and roadmap into one tool is a real pain point - most teams juggle a changelog tool, a support inbox, and a spreadsheet for feature requests, and things fall through the cracks between them. Curious how the roadmapping side handles duplicate requests: does it auto-merge similar feedback or is that manual? That is usually where these tools get messy at scale.