AIshar Labs started with a question I kept hearing from founders: "Where do I find someone who can actually build this?"
I spent nearly a decade inside Apple and Instacart — building the ML systems behind search, recommendations, and personalization that hundreds of millions of people use every day. At Apple, I built & powered search for Maps, Safari, and Spotlight. At Instacart, I architected the ML platform for recipe recommendations, product search, and feed ranking. I filed 15 AI patents because we were solving problems nobody had solved before.
But here's what I noticed, over and over: the companies outside big tech couldn't access this level of engineering. They'd hire consultancies that delivered strategy decks but couldn't ship production models. They'd outsource to agencies that built prototypes that collapsed under real traffic. They'd spend months trying to recruit ML talent that Apple and Google had already locked up.
The gap wasn't knowledge.
It was engineering depth.
Founders and enterprise teams had the domain expertise. They understood their markets, their users, their data. What they didn't have was someone who'd built ML systems at billion-query scale and could apply those patterns to their specific problem.
That's the gap AIshar Labs fills. We're not a consultancy that learned AI. We're AI engineers who spent years building at the highest level — and now bring that same rigor to every company we work with.
We don't advise. We embed with your team and build. We don't create dependency. We transfer everything and make sure you can run it without us. And we don't staff projects with juniors. The architect who designs your system is the same person who writes the code.
AIshar Labs is deliberately small, intentionally senior, and completely focused on one thing: building production AI systems that work.