Every app wants a piece of your monthly budget now. Your note-taking app, your weather app, your calculator (yes, really). It's exhausting.

We get why developers do it. Predictable revenue. Sustainable business. All that good stuff. But somewhere along the way, subscriptions became the default even when they don't make sense.

When subscriptions actually make sense

If we're running servers for you — syncing your data, processing things in the cloud, keeping infrastructure alive 24/7 — then yeah, we need ongoing revenue to cover ongoing costs. That's fair.

But a utility app that runs entirely on your device? A tool that doesn't phone home? Why should that cost you $5/month forever?

Our approach

Pay once for apps that don't need servers. Simple. If an app does need ongoing infrastructure, we'll be upfront about it. We'll tell you exactly what you're paying for and why.

No dark patterns. No "free tier" that's deliberately crippled. No sudden "premium" features that used to be included.

Is this the most profitable approach? Probably not. But we're not trying to maximize extraction. We're trying to make good tools and charge fairly for them.

Every AI feature today seems to require sending your data to some server farm. Your photos, your documents, your conversations — all uploaded to be processed by machines you don't control.

But here's the thing: modern phones and laptops are incredibly powerful. The M-series chips, the latest Snapdragons — they can run surprisingly capable AI models locally.

Why does this matter?

Privacy. Your data never leaves your device. No server logs, no training data harvesting. What happens on your device stays on your device.

Speed. No network round-trip. No waiting for a server response. On-device inference can be instantaneous.

Offline. Works on a plane. Works in the subway. Works in that dead zone at your parents' house.

The trade-offs (being honest)

On-device models are smaller. They can't match GPT-4 for complex reasoning tasks. But for most everyday tasks — smart autocomplete, photo organization, quick summaries — local models are more than good enough.

Our bet

We're building with on-device AI first. Not because it's trendy, but because it aligns with how we think software should work: your tools, your data, your control.