While giants fight for AI headlines, a tiny, stealthy startup is building the plumbing that makes ML actually work. Iterative.ai isn't chasing AGI—it's solving the messy, unsexy problem of data pipelines, and its traction tells a story of pure product-market fit.

"They aren't building a product for everyone—they're building a tool for the 1% of engineers who actually care about data lineage."

The company's focus on data preprocessing and management reveals a critical insight: the real bottleneck in ML isn't model training—it's data preparation. While competitors chase flashy AI capabilities, Iterative.ai is building the foundational layer that makes everything else possible. With a revenue-to-employee ratio of $75K, they're either in early R&D mode or deliberately keeping the team small and focused—a classic founder-led engineering culture.

• Extreme focus: 8 people covering the entire MLOps lifecycle
• Niche dominance: Targeting specific Python ecosystem pain points (fsspec, shtab)
• Zero marketing reliance: Pure product-led or community-driven growth
• Modern stack: Built for speed and developer experience (Vite, Tailwind, Cloudflare)
• Revenue-first: $0.6M with no funding noise suggests self-sustainability