AI Product Studio · AI Infrastructure
We build, optimize, and deploy AI. Measured.
A working AI product in 14 days, an inference bill that stops leaking, or private AI running inside your own perimeter — engineered by a team that publishes its benchmarks with raw data. Delivery for the US, Canada, UK, and EU.
Fixed sprint from $9,900 · Product teams from $11,500/mo · Audit is free, no call required.
Trusted by teams behind
What we do
Three ways to work with us.
Build
AI products, shipped fast
- 14-day fixed-scope MVP sprint — working product, not a deck
- End-to-end product teams: discovery to operated production
- Evals and cost telemetry in every build, full IP transfer
Sprint from $9,900 · Teams from $11,500/mo
Book a scoping callOptimize
AI bills, stopped leaking
- Free written inference audit for $20K+/month spenders
- Leak map: agent loops, retries, routing, idle capacity
- Measured before/after — $47K→$28K in our published case
Audit is free · No call required
Start the free auditDeploy Private
AI inside your perimeter
- On-prem & colocation LLM stacks in your chosen facility
- GDPR and EU data residency by architecture, not by clause
- Sized from published benchmarks — edge boards to H100 pairs
Consult free · TCO before hardware
Book a deployment consultThe HPC difference
Engineered from the transistor up.
Most AI agencies start at the API call. We start at the silicon — electrical & computer engineering roots, HPC research lineage, and hardware-aware serving that squeezes measured performance out of every layer between the die and your product.
Benchmarks with raw data
We publish throughput, power, and cost measurements with unedited CSVs — including the configurations that failed. Judge the engineering by data, not a portfolio page.
Jetson edge benchmark reportEdge to HPC, one ladder
8-watt Jetson boards serving 16 concurrent users at ~$14/month, up through L40S nodes to H100 pairs serving 70B models at $0.47 per million tokens. Sized by measurement, not vendor sheets.
GPU requirements: edge to HPCCost telemetry by default
Every system ships knowing its own unit economics — per-request and per-workflow spend visible from the first deploy. The 42% cheaper inference playbook is public.
The Token Tax benchmarksShipped Work
The proof is shipped.
No borrowed logos, no stock quotes — products we engineered, live in production for our clients and ventures.
BuildUNIX
Construction execution platform for PMC firms — phase-gated workflows, tamper-proof site records, and snag-to-handover tracking that replaces spreadsheets and WhatsApp threads.
Full-stack platform: Next.js, Postgres, async job pipeline, field-team mobile flows.
VectraGPT
Secure AI chatbots for HR, support, and sales — RAG-powered answers from company documents with audit trails, aligned to GDPR and SOC 2 expectations.
RAG platform end to end: ingestion, retrieval, guardrails, multi-tenant serving.
XeoRank
SEO, AEO & GEO intelligence engine for developers — triple scoring, Search Console integration, and CLI-first plus MCP agent workflows.
Agent-first product: MCP server, site crawler, scoring engines, WordPress control plane.
AdFargo
AI creative strategist — learns a brand from its URL and generates on-brand ads, video, and copy built to convert, in minutes.
Generative pipeline: brand ingestion to multi-format creative output.
Rankgent
Programmatic SEO platform — generate, preview, and publish thousands of service + location pages in minutes. Trusted by 500+ SEO professionals.
Page-generation engine: templating, bulk preview, and publishing at 50K+ pages scale.
Cheval
Web design and development agency serving UAE brands — high-volume portfolio of business sites built for speed and search.
Engineering partner: platform performance and search infrastructure.
Also trusted by
How we work
Speed is a process, not a promise.
Step 1
Scope in days, not months
A 30-minute call, then a frozen scope, architecture, and fixed quote within 48 hours. Honest feasibility first — if an idea doesn't fit the window, we say so.
Step 2
Build with demos
Working software from week 2 at the latest. Demos at every phase, your feedback folded in while the build runs — no final-reveal surprises.
Step 3
Evals & cost telemetry, by default
Golden sets, regression gates, and per-request cost visibility ship inside every build. The demo that survives production is the one that was measured.
Step 4
Handover or operate
Your repos, your cloud, full IP assignment — take it over with runbooks and training, or keep us on under an SLA that fits your stage.
Who you work with
“Autonomy without control becomes risk. Intelligence without governance becomes liability.”
Vikas is a systems-first AI technologist specializing in high-performance agentic infrastructure, developer tooling, and scalable AI platforms. With a Master’s in Electrical & Computer Engineering from UNC Charlotte and HPC research roots, he designs AI systems that are secure, efficient, and production-ready from day one — control planes for agents, hardware-aware serving, and capital-efficient execution.
Transistor→Kernel→GPU→Cluster→Cloud
Track record
M.S. Electrical & Computer Engineering, UNC Charlotte · 98% export revenue mix · every intake read personally
Already running AI?
Find the leak before you buy more capacity.
Teams spending $20K+/month on OpenAI, Azure OpenAI, Bedrock, RAG, agents, or self-hosted LLMs get a free written leak map — where the bill inflates and what to change first. 20 seconds to start, no call required.
What the leak map covers
- Agent loops and retries multiplying token volume
- Prompt and context bloat on every request
- Frontier models serving small-model work
- Idle or overprovisioned GPU capacity
- RAG, vector-store, and egress overhead
$47K → $28K
Monthly bill after one audit — published case study, measured before and after.
Read the case studyEngineering blog
We publish what we measure.
FAQ
Common questions
Still unsure which path fits? Thirty minutes on a call maps your situation to a concrete plan with a price on it.
Book a call insteadHow fast can NavyaAI build an AI product?
A working, deployed MVP in 14 days through the fixed-scope AI MVP Sprint (from $9,900): scope frozen on days 1-2, working software by day 6, evaluation gates and cost telemetry by day 13, handover on day 14. Larger products run as phased builds with working software from week 2.
What does AI product development cost with NavyaAI?
The 14-day MVP sprint is fixed-price from $9,900. Phased end-to-end builds start from $24,000, and ongoing senior product teams from $11,500/month — typically 40-60% below equivalent US or UK agency pricing, because senior engineers work from an India cost base with US/EU timezone overlap. Full IP assignment in every contract.
How does the free AI inference audit work?
Teams spending $20K+/month on LLM APIs or GPUs share their spend range, provider/workload, and stack in a 3-minute intake. NavyaAI replies with a written leak map — where the bill inflates across agent loops, retries, routing, and idle capacity, and what to change first. No call required; our published case cut one bill from $47K to $28K per month.
Can NavyaAI deploy AI on-premise for GDPR compliance?
Yes — we design, deploy, and operate private LLM and RAG stacks in your data center or your chosen colocation facility, so prompts, documents, and embeddings never leave your jurisdiction. EU data residency holds by architecture rather than contract clauses, and every tier is sized from our published benchmarks, from 8-watt edge boards to H100 clusters.
Which regions does NavyaAI work with?
Most clients are in the US, Canada, UK, and EU. Engagements run with deliberate timezone overlap for standups and demos, communication in your tools, contracts under mutually agreed jurisdiction with full IP assignment, and deployment in your cloud region — GDPR-aware by default for EU data.
What makes NavyaAI different from other AI agencies?
Hardware-up engineering and published proof. The team spans transistor-level architecture to cloud-scale inference, and publishes benchmarks with raw data — 158 tokens/sec on a $499 edge board, $0.47 per million tokens on an optimized 70B stack — including the configurations that failed. Every build ships with evaluation gates and cost telemetry.
Start here
One call. Three ways forward.
Thirty minutes to map your goal — build, optimize, or deploy private — to a concrete plan with a price on it. Or skip the call entirely and start with the free written audit.