What It Takes to Build Privacy-First AI - From Alpha to Infrastructure

​Building privacy-first AI goes far beyond model design. It requires hard product decisions, careful infrastructure planning, and trade-offs that only surface once systems run in the real world.

​In this live session, teams from Nosana and Arcium discuss what it actually takes to build and ship privacy-preserving AI, starting from an early alpha release and extending to infrastructure, compute, and long-term AI strategy.

​The discussion will cover:

• ​How privacy-first AI products are designed and why they matter

• ​Key takeaways from Arcium’s recent alpha release

• ​How privacy requirements shape AI execution and architecture

• ​Infrastructure and GPU considerations as workloads scale

• ​Lessons learned and emerging trends from years of building in this space

​The session will include a light technical segment to explore how these systems work under the hood, while keeping the conversation accessible to builders, founders, and infrastructure teams.

​This session is ideal for anyone building AI products, working on AI infrastructure, or interested in privacy-preserving systems moving from concept to production.