Infrastructure-first product studio built byVikas and Hitesh
Vikas is a systems-focused AI technologist and venture builder specializing in high-performance agentic infrastructure, developer tooling, and scalable AI platforms.
With a Master’s in Electrical & Computer Engineering from UNC Charlotte, Vikas designs AI systems that are secure, efficient, and production-ready from day one. His work emphasizes guardrails and control planes for AI agents, infrastructure optimization, and capital-efficient execution. He has led multiple production AI platforms across legal, enterprise automation, and developer tooling, always with an infrastructure-first mindset.
Hitesh focuses on product strategy, user journeys, and growth execution so each MVP solves a real business problem and can be validated quickly with users.
Together, we combine product clarity and engineering depth: Hitesh shapes what to build and why, while Vikas architects and ships the platform with production-ready AI infrastructure.
Ramachandra Vikas Chamarthi
Systems Architect · AI Infrastructure Builder
Designs and ships reliable AI systems with a strong focus on control, performance, and scale readiness.
- Agentic AI infrastructure and control planes with strong governance.
- High-performance AI systems with optimized throughput and latency.
- Full-stack product engineering from CLI tools to SaaS platforms.
Hitesh Sharma
Product Strategy · User Validation · Growth Execution
Converts complex ideas into a clear MVP narrative users understand, adopt, and trust. Shapes messaging, scope, and feedback loops before and after launch.
- Shapes clear product positioning and user value narrative.
- Designs user validation loops to de-risk product decisions early.
- Builds practical go-to-market plans for launch and adoption.
How we help founders and teams
- Turn raw ideas into a clear MVP scope, user journey, and launch plan.
- Design and build secure AI products with scalable backend architecture.
- Ship quickly, validate with users, and iterate based on real feedback.