We build or finish your app. Then we find your customers.

You should, as long as it’s working. We use AI app builders ourselves: several of our own repos started as scaffolds in Bolt, one of the popular ones. But there is a line they don’t cross: auth you’d trust with strangers’ data, real payments, integrations with the systems your business runs on, and deployment with backups and a rollback plan. If you haven’t hit that line, keep building. We mean it. If you have, the free Production Gap Review shows exactly where the line is and what crossing it takes.

Both, in a specific order: AI drafts, senior engineers decide. Every change that ships is reviewed by a named senior engineer who is accountable for it. The AI features we build into client products follow the same discipline: the LLM extracts, the server decides, with read-only data roles, audit logs and kill-switches. You keep the speed that made AI tools feel like magic, without handing your product to a model.

No. Your prototype is the most valuable spec you could hand us: validated product decisions, made cheaply. Sometimes the honest path is rebuilding parts of it on production foundations, and when it is, we’ll say so in the review and show you why. What we won’t do is quote a from-scratch rebuild to pad the invoice. Part of our portfolio is finishing projects other developers left mid-stream, including one whose own README admitted every phase was incomplete.

Three structural differences, not promises. The diagnosis is free, so you see our thinking before you spend anything. We’re founders too: we run our own products on the same rails we sell, so bad engineering costs us personally. And we’re not an offshore body shop: you work with the senior team, directly.

You bring what you have so far: just the idea, an app started in an AI app builder like Lovable or Bolt, a freelancer’s or agency’s half-finished project, or a product that’s already live. We walk it together for 30 minutes, and afterward you get a written gap map across deployment, security, data, payments, integrations and growth readiness. It’s yours to keep, act on, or take to another shop. If there’s a fit, we’ll quote a fixed, scoped path. If there isn’t, we’ll say that too.

Because our favorite number is the unflattering one. On a consumer-fintech account, we publish that most funded bills are not Google-attributed; the measurement exists to tell the truth, not to flatter the invoice. On another account, a line-by-line audit found a monthly spend leak, and the data behind it showed the real blocker: a reorder rate too low for any ad budget to fix. Both figures, with their sources, are on How we count. We hold this site to the same standard: every number on it is registered with its source, method and verification date, and a check in our build pipeline blocks the deploy if a banned claim slips into the copy.

The review costs nothing and ends with a fixed, scoped price, so you know the cost of graduation before you commit a dollar. AI-assisted delivery is why the math can work at your size. We don’t publish blanket discount percentages; we publish one documented delivery velocity example, with its receipts. Most clients graduate in stages: production first, then the growth engine once there’s something to fill.

Small is why you get senior engineers instead of a junior bench. And the ceiling is proven: this same team built an operations platform of dozens of modules for a 12-rooftop auto group with hundreds of employees, and has engineered the rails of a consumer fintech in production for years. The graduation path doesn’t end at your first launch.