Our Story

We take a more thoughtful approach to building AI—grounded in real workflows, not assumptions.

// the problem

Companies Are Automating Without Thinking

The AI rush is real. Companies are implementing AI everywhere, chasing automation for its own sake. They’re not asking the right questions: What problem are we actually solving? Where does AI make sense? Where should humans stay in control?

The tool has become the goal. That’s backwards.

And it leads to predictable failures. Systems that break in production. Teams that resist tools forced on them. Millions wasted on automation that doesn’t work.

What we believe:

We believe AI should be built to understand your existing processes, not force you to rebuild everything around the technology. The best implementations help reconstruct workflows thoughtfully, keeping humans at the center and augmenting what they already do well.

// The Founder’s Journey

Aishwarya Naresh Reganti

LevelUp Labs was founded by Aishwarya Naresh Reganti, an AI researcher who’s been building production systems for over a decade.

Aishwarya has over 35 research publications in top AI conferences like NeuRIPS, AAAI, CVPR etc.She was on the early Alexa team at Amazon before generative AI was everywhere. Later, as a tech lead at AWS Generative AI Innovation Center, she led 30+ implementations for enterprise clients.

She saw the same mistakes repeatedly. Companies forcing AI into processes without thinking. Automation without intention. Teams left out of the design entirely. LevelUp Labs was born out of these patterns. We wanted to share what works with the wider world.

35+ Publications

NeuRIPS, AAAI, CVPR etc.

AWS GenAl Lead

Innovation Center lead.

Ex-Alexa Team

Early Amazon AI team.

30+ Enterprise Clients

Implementation lead.

// the problem

Companies Are Automating Without Thinking

Mission

We’re not typical consultants. We embed with your team. We understand your people, your processes, your actual constraints. We build AI that understands and fits into how you work.

We work across industries and teams, which lets us recognize patterns most organizations see only once. We share what we learn.