Why I Built SendMind
Most AI email tools generate confident-sounding nonsense. SendMind is built around real signals — accurate analytics, clean lead scoring, real-time tracking — for indie creators who actually send.
I kept trying AI email tools and giving up on them.
The drafts were fine. The analytics were a lie. Open rates that didn't match what my inbox showed. "Lead scores" that ranked unsubscribes higher than buyers. Sequences that double-counted refunds as revenue. The output looked clean enough to share in a screenshot, and crumbled the moment you actually used it to make a decision.
I'm a solo founder. I don't have an analyst to sanity-check the dashboard. If the numbers are wrong, I'm wrong — and I find out two weeks later when a campaign I thought worked actually didn't.
So I built SendMind around one stubborn rule: every number on the screen has to be true.
That sounds obvious. It isn't. It means deduping revenue when refunds hit. It means counting opens with the pixel that fired, not the one that should have. It means a lead score that down-weights unsubscribes instead of celebrating the engagement event. It means building the warm-up logic and the dispersion checks and the CSV import error surfacing — the unglamorous middle layer that most "AI email" products skip because it doesn't demo well.
The AI part is real, and it's good. But the AI is downstream of the data being honest. A model trained on broken signals gives you confident lies. A model with clean signals gives you a product you can actually run a business on.
That's the bet.
If you're an indie creator who's been burned by tools that talk like a CMO and break like a side project — SendMind is built for you. I'm one user away from being you. Daniel is user one. You can be user two.
I'll write more here as we ship. Real notes, not marketing.
— Matt