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Product and MVP development

AI Product & MVP Development in San Francisco

The best AI Product & MVP Development in San Francisco, at the best available price.

$0 upfrontPay per accepted checkpointSenior engineer, no agency markup

A real, production-grade build you can put in front of users or investors. Frontend, backend, mobile, the agentic AI underneath, and the cloud or private infrastructure it runs on, as one engagement rather than four vendors.

San Francisco has the densest concentration of AI companies and venture money anywhere, which cuts both ways: the talent is excellent and almost all of it is already spoken for. Seed-stage teams compete with the largest labs for every senior engineer, so many ship their first product with outside help and hire once the product has shown what kind of engineer it needs.

Investors here have seen a thousand demos. What moves a round is real usage, so the build aims at a product people can sign up for and use, with analytics in from day one so you can show the numbers.

What you get

  • Full-stack build on Next.js, Node or Python, with a database and API design that survives past the MVP
  • AI where it earns its place: LLM features, retrieval over your own documents, agent flows that call real tools, voice
  • Auth, payments, analytics and an admin surface, not a demo that breaks on the second user
  • Deployment across AWS, GCP or Azure, or private and on-premise hosting where the data demands it
  • Clean, documented code on your own infrastructure, written to make us replaceable on purpose
Working MVPs from $1,000. Full production builds from $12,000.

Final pricing depends on scope, features and complexity, so we settle it on a call before any work starts.

Invoiced in USD, payable by Wise or bank transfer.

Request a callback

You speak to the engineer who does the work. No sales rep, no deck.

No spam and no sales team. You talk directly to Neeraj.

San Francisco, California

Who builds here

AI labs and model companiesSeed and Series A SaaSDeveloper toolsThe accelerator and angel network
Best fit in San Francisco

AI Product & MVP Development

The usual San Francisco situation is a funded founder who needs a working product in front of users before the next raise, and cannot wait four months to hire a team to build it.

You are on it
Three founders around a laptop in a sunlit office, celebrating the moment their product went live
Timeline of a production MVP built in six weeks and paid per checkpoint. Today costs $0. Week 1 locks scope and architecture; weeks 2 to 4 build the core product with a demo every week; week 5 adds sign in, billing, admin and analytics; week 6 hardens the product and hands it over, live on your own accounts. Each stage ends in a checkpoint that is accepted, then invoiced.
Four checkpoints, each invoiced only after you accept it. Nothing is due before the first one.
How you pay

Get it built at $0.

That is not a discount. It is when you pay. The work is split into checkpoints with acceptance criteria written down before anything starts, and each checkpoint is invoiced only after you have seen it and accepted it. No deposit.

$0 to start
You hold every dollar until a checkpoint is delivered and you accept it. No approval, no invoice.
Fixed cost, unlimited features
Or hire the team outright: one fixed monthly cost, unlimited feature development, any stack.
The engineer takes your call
The person on your first call is the one who architects and writes it. No account managers, no bench time.

A US agency quotes $50,000 to $150,000 for the same build and asks for 40 to 50% of it before a line is written. Account managers, project managers, sales commission and bench time. None of it appears in your product.

How it works

Three stages, nothing hidden.

01

Twenty-minute call

You talk to the engineer who will build it, not a sales rep. We scope the problem and you get told plainly if this is the wrong fit.

02

Fixed proposal in 48 hours

Fixed price, fixed timeline, defined deliverables, in writing. No hourly billing surprises and no open-ended scope.

03

Weekly demos until it ships

Working software every week, direct access over Slack or WhatsApp, and documentation handed over at the end.

Working in San Francisco

What actually applies here.

Regulation and data

California's privacy law, the CCPA as amended by the CPRA, is enforced by a dedicated agency, the California Privacy Protection Agency, and applies to businesses above its revenue or data thresholds wherever they are based. The agency's rules on risk assessments and automated decision-making technology add obligations that phase in over the next few years. If your product makes significant decisions about people, plan for opt-out and access requests from the start rather than after the first enterprise customer asks.

Contracting and payment

You contract with an individual consultant based in India rather than a US entity. Invoices are issued in USD and paid by Wise or bank transfer, with no payroll and no benefits load on your side. Whatever documentation your finance team or counsel needs from an overseas contractor is provided before work starts.

Working hours

Calls in your morning, Pacific time, and work handed over at the end of your day so the next round of changes is waiting when you start.

Is it a problem that you are not in the Bay Area?

Not for the work itself. You get calls in your morning Pacific time and work handed over at the end of your day, so the next round of changes is waiting when you start. Everything lives in your repository and your accounts.

Can you help us get ready for technical due diligence before a raise?

Yes. That usually means tightening security basics, documenting the architecture and making sure more than one person can deploy. It fits naturally into a fractional CTO or build engagement.

Is three days realistic?

For a working, demoable version of a core idea, yes, and that is what the three-day build is. A full production system with billing, admin and hardening takes weeks, not days. We will tell you which one your situation actually needs.

Do we own the code?

Entirely. It ships into your repository on your own cloud accounts, documented so your team or your next hire can pick it up without us.

Can you also host the AI model privately?

Yes, and as part of the same engagement. If compliance means inference cannot leave your network, the serving layer and the application are built together rather than handed between vendors.