Mani Kandasamy

I build systems that are supposed to be too complex to simplify — and then I try to make them simple enough that people can actually trust and use them.

I work at the intersection of enterprise data, agentic AI, and large-scale architecture. In practice, that means helping organizations move from fragmented systems to connected, intelligent platforms that can reason, act, and scale in real-world conditions.

As CTO at Deloitte Consulting LLP, I work with teams building large-scale data and AI platforms across North America. My work sits between design and delivery — I stay close to architecture decisions, but also close enough to see what actually reaches production.

Most of what I share comes from that gap between intent and reality — where systems behave differently under real load, real constraints, and real deadlines, especially when agentic and real-time components are involved.

I’ve worked across ecosystems including Databricks, AWS, Microsoft, and Snowflake, and have been recognized as a Databricks MVP (2025, 2026) and North America Partner Champion (2024).

But what matters more than titles is whether systems actually hold up when they’re used for real decisions, at real scale.

I care most about the translation layer — taking complex systems (especially data, AI and agentic-driven ones) and making them understandable enough that better decisions get made faster.

If you’re working on ambitious problems in data, AI, or enterprise transformation, I’m always open to exchanging ideas.