At Inithouse, we run a lab that ships a growing portfolio of AI products in parallel. Not one product at a time. Not a pivot-heavy path from idea to idea. A deliberate strategy: build multiple MVPs, measure what sticks, double down on what works.
Here is how we actually do it, and what we learned shipping products like Magical Song (studio-quality custom songs from your story), Be Recommended (AI Visibility Reports for brands), and Ziva Fotka (AI photo-to-video tool, multi-domain across 5 languages).
1. Start with one product, then fan out
We did not start with a portfolio. We started with a single MVP, validated the build pipeline, then replicated it. The key lesson: don't scale the number of products until you can ship one in under 3 weeks. If your first product takes 3 months, your tenth will too.
2. Standardize the tech stack
