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Contact NavyaAI

Build it, optimize it, or bring it in-house.

Three ways to work with NavyaAI — pick the one that matches where your AI effort is today. Every path starts with something concrete: a scoped plan, a written leak map, or a deployment architecture.

Reply within 1 business dayEvery intake read by the founderNo sales sequence, no spam

Build

Ship an AI product

A working MVP in 14 days from $5,500, production builds from $24,000, or a senior AI pod with fully transparent pricing. US, Canada, UK, EU & Australia delivery with timezone overlap.

14-Day AI MVP SprintDedicated Team PlansEnd-to-End AI Product Development
Book a scoping call

Optimize

Cut your AI bill

Spending $20K+/month on LLM APIs or GPUs? Get a free written inference audit — a leak map of where the bill inflates and what to change first. No call required.

Free AI Inference AuditFree Cloud Egress Audit
Start the free audit below

Deploy Private

Run AI in your perimeter

On-prem and colocation LLM deployment in your facility — GDPR and EU data residency by architecture, sized from published benchmarks.

On-Prem & Colocation AI DeploymentSelf-Hosted LLM Deployment
Book a deployment consult

Company

NAVYAAI PRIVATE LIMITED
Kovvur, Andhra Pradesh, India

Prefer a call?

Book 30 minutes

Audit Intake

Get a written leak map before a call.

Best fit for teams spending $20K+/month on OpenAI, Azure OpenAI, Anthropic, Bedrock, Vertex, RAG, agents, or self-hosted LLMs.

  • Where token, retry, RAG, agent, or GPU waste is most likely.
  • Which metric to inspect first before buying more capacity.
  • Whether the next step is a written question set, estimator review, or call.
Add stack details — optional, but it makes the leak map sharper

Takes 3 minutes. No call required — I reply with where to look first, even if we never speak.

Vikas Chamarthi, Founder of NavyaAI

Your intake goes to me — and I read your whole stack.

I work where AI meets HPC, with a view that runs from transistor-level architecture to cloud-scale inference. That full-stack span is how I find cost leaks others miss — in the silicon, the serving layer, and the system design at once.

Transistor→Kernel→GPU→Cluster→Cloud

Vikas Chamarthi · Founder, NavyaAI

LinkedIn

Track record

Head of AI/MLHeyNeoUSHead of MLOpsCode and Theory · Stagwell GroupUSResearchTeCSAR Lab, UNC CharlotteUS

M.S. Electrical & Computer Engineering, UNC Charlotte

Founder experience — US roles & engagements at

Code and Theory (Stagwell Group)ProsciaWolframHeyNeoTeCSAR Lab · UNC Charlotte