Production AI Engineering
NavyaAI builds agents, RAG systems, private LLMs, and AI infrastructure with evals, budgets, observability, and transparent delivery built in from day one. Daily written progress on every engagement: tasks, commits, blockers, and spend. US, Canada, UK, EU & Australia.
Sprint from $5,500 · Production builds from $24,000 · Audit is free, no call required.
Why teams pick us
Don't take our word for it. Inspect the price, the progress, and the proof.
Price you can inspect
Know what the team and the delivery layer cost, itemized on every invoice, with a public calculator.
Check the mathProgress you can see
Daily written progress on every engagement: tasks, commits, blockers, scope changes, and spend stay visible. Calls only when useful.
How we workProof you can reproduce
Evals, benchmarks, and methodology, with raw CSVs and the failures included. Judge the team by data, not a portfolio page.
Read the reportsWhat we do
The demo is the easy 80%. Every lane ships the production 20% too.
Build
One idea to a deployed, evaluated product (agents, RAG, LLM apps) with the production 20% engineered in from day one.
Measured
Sprint from $5,500 · Builds from $24,000
Get a build planOptimize
A written map of where spend inflates (agent loops, retries, routing, idle capacity) before you buy more.
Measured
Audit is free · No call required
Start the free auditDeploy Private
Private LLM and RAG stacks in your facility and jurisdiction, sized from benchmarks we ran, not vendor claims.
Measured
Consult free · TCO before hardware
Book a deployment consultThe HPC difference
Most AI agencies start at the API call. We start at the silicon, with 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.
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 report8-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 HPCEvery system ships knowing its own unit economics, with per-request and per-workflow spend visible from the first deploy. Our Token Tax benchmark cut 70B serving cost 42%, and the method and raw data are public.
The Token Tax benchmarksShipped Work
No borrowed logos, no stock quotes. These are products we engineered, live in production for our clients and ventures.
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.
Secure AI chatbots for HR, support, and sales, with 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.
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.
AI creative strategist that 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.
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.
Also trusted by
How we work
Step 1
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
Working software from week 2 at the latest. Demos at every phase, your feedback folded in while the build runs, so there's no final-reveal surprise.
Step 3
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
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.
Already running AI?
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. Name and email, no call required.
Cloud bill leaking instead? Free egress auditWhat the leak map covers
$47K → $28K
Monthly bill after one audit, measured before and after in our published case study.
Read the case studyEngineering blog
FAQ
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 insteadA working, deployed MVP in 14 days through the fixed-scope AI MVP Sprint (from $5,500): 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.
The 14-day MVP sprint is fixed-price from $5,500, and phased production builds start from $24,000. Ongoing teams run as senior AI pods with fully transparent per-role pricing: role compensation plus a flat, itemized 20% delivery layer, with the complete math in a public calculator. Full IP assignment in every contract.
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 showing 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.
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.
Every NavyaAI engagement runs with automatic AI progress tracking: an AI agent watches the repositories and task boards and sends you a daily plain-English report on what shipped, what's in flight, what's blocked, and spend against budget. Every task, commit, blocker, scope change, and spend variance stays visible, and calls happen when they're useful rather than as status theater. Combined with itemized invoices and benchmarks published with raw data, nothing about the engagement is hidden.
NavyaAI is a production AI engineering company: we build, optimize, and deploy AI systems (agents, RAG, private LLMs, and the inference infrastructure underneath) with evals, budgets, and observability engineered in. Unlike most AI engineering companies, the pricing, daily progress, and benchmarks are all inspectable.
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.
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
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.
Last updated September 28, 2026 by Ramachandra Vikas Chamarthi, founder.
