Sravya Avasarala

GTM Lead, AI Infrastructure Partnerships @ NVIDIA | Cloud-to-Edge AI · Ex-Microsoft |

NVIDIAex-Microsoftex-CA Technologies

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The next era of enterprise AI won't be decided by who has the best model. It will be decided by who builds the partner ecosystem that gets AI safely and reliably into production at scale.

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That's the problem I've spent 12 years obsessing over — first at Microsoft, where I built the first Azure AI GTM program from zero with no playbook and no precedent, then at NVIDIA, where I architected three routes to market with Power and Cooling, Colocation, and Storage partners. What I've learned: the gap between an AI demo and a production AI system is enormous, and almost nobody is building the partner infrastructure to close it. The ISVs need technical validation. The channel partners need reference architectures and financial incentive structures that actually work. The enterprises need a trusted intermediary who understands both the technology stack and the business case. When those three things come together, AI actually lands — at Domino's, at Dow Chemical, at Kroger. My edge is that I've operated at every layer of that stack. I've written the rebate structures and the reference architectures. I've recruited the ISVs and hunted the lighthouse accounts. I've built sovereign NCP models with Singtel in Singapore and hybrid cloud-to-edge data layers with storage partners and NCPs. I don't just design partner programs — I build the flywheel that makes them self-sustaining. The question I'm most focused on right now: as AI infrastructure matures from GPU clusters to purpose-built accelerators, what does the partner ecosystem need to look like to make that transition happen responsibly and at scale? The channel GTM for that transition doesn't exist yet. I'm building it.