Advaith Prasanna

I'm a product engineer building AI-native operational tooling at Kaya AI — currently focused on construction and supply chain. My work sits at the intersection of data systems, applied AI, and customer-facing product.

What I find most interesting isn't any single technology — it's the challenge of translating chaotic operational reality into something a software system can reason about. Construction sites, manufacturing floors, and logistics networks are messy. The data is fragmented, the workflows are informal, and the people doing the work often don't have time to learn new tools. I like solving that.

Before Kaya, I spent time in aviation analytics at NetJets, industrial ML at Rockwell Automation, and operational analytics at Ohio State Athletics. Each role gave me a different vantage point on how organizations actually use data — often imperfectly and always under real constraints.

NCAA Division I Fencing

I fenced varsity for Ohio State — one of the country's top fencing programs. Four years of Division I competition gave me something no class or project could: experience operating under genuine pressure with immediate feedback. The habits of training — consistent preparation, honest self-assessment, and learning from failure without dwelling on it — carry directly into how I approach engineering.

AI systems

How LLMs integrate into production operational workflows — not demos, real deployments

Operational intelligence

Turning messy real-world operations into structured, queryable data

Data infrastructure

The pipes and models that make reliable data products possible

Human-centered software

Tools built for people who don't have time to learn tools

Supply chain + logistics

Physical world complexity at scale, ripe for better software

Forward deployment

Engineering that lives at the boundary between product and customer

B.S. Computer Science & Engineering — Artificial Intelligence

The Ohio State University · 2022–2026

B.S. Data Analytics — Computational Analytics

The Ohio State University · 2022–2026

Let's build something useful.

Open to conversations about product engineering, operational AI, and building systems that make messy work legible.

Advaith Prasanna · 2026

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