From analytics to agentic systems.

I'm Revanth Pattipati.

My career has taken the scenic route, and honestly, that route did most of the teaching.

I started in software and IT, moved into analytics and data science, spent years around cloud platforms and infrastructure, and eventually found my way into applied AI and agentic systems. Each chapter taught me a different kind of discipline. Software taught me precision. Analytics taught me how to find signal. Cloud taught me reliability and cost. AI is where all of those lessons now collide.

Today, I focus on building AI systems that are useful beyond the demo. That means thinking about orchestration, evaluation, security, observability, governance, cost, and the very inconvenient fact that real users do not behave like test cases.

I care about AI that feels practical, trustworthy, and usable for technical and non-technical people. Not magic tricks. Not hype confetti. Systems people can understand, adopt, and improve.

Outside work, I seem to collect hobbies that involve a suspicious amount of calculated risk. I have finished multiple half marathons, I am training for a full marathon and a triathlon, I have 75 skydives, and I am currently learning how to swim properly.

That probably explains my engineering philosophy too.

Good systems are not fearless. They are designed to fail safely, recover quickly, and get better with every iteration.