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AI product build 8–14 weeks

Build an AI SaaS MVP that holds up in production

I build AI products from an empty repo to production in 8–14 weeks: retrieval, model calls, multi-tenancy, metering and billing. My own multi-tenant AI support platform, Evoriqa, went from first commit to live in about two months.

Who it is for

  • Founders building an AI product who need the whole thing built, not only the model call.
  • Products that need tenants, usage limits and billing from the first customer.

What the work covers

  • Retrieval over your own content, with every tenant's data isolated.
  • Model calls behind an interface, so the vendor can change without a rewrite.
  • Usage metering and limits per customer, so cost per request stays visible.
  • Accounts, roles and billing.
  • A deployed production system, and a codebase the next engineer can read.

Adding AI to a product you already run

The same work, scoped smaller: retrieval, an agent or an LLM feature added to an existing product, usually 2–5 weeks and typically $4k–$10k. It has its own page. RAG development

Proof

  • AI reply grounded in cited help-centre content, shadow-mode draft metrics per channel, and metered AI credits in billing.

    Evoriqa

    My own SaaS: a multi-tenant AI customer-support platform, live in production, built by the person who also pays its inference bill.

    • Next.js
    • TypeScript
    • PostgreSQL
  • PDF chat with document scope selector, landing page and upload queue of a RAG assistant that cites its pages.

    AI PDF Chat

    Upload several PDFs and ask questions across all of them or one; every answer cites the PDF and page, and the citation opens the passage highlighted.

    • Next.js
    • Express
    • LangChain

Questions

How long does an AI product build take?
Usually 8–14 weeks from first call to production, depending on scope. Adding one AI feature to an existing product is usually 2–5 weeks.
Which model provider do you use?
Whichever fits the job; I have shipped on OpenAI, Anthropic and Groq. I put the model behind an interface so changing vendor later is a small change.
How do you keep the model bill under control?
By metering usage per customer from the start and capping spend. Evoriqa meters AI credits per tenant, with soft caps and usage alerts.

Tell me what you’re building and where it’s stuck.

I’ll tell you the cleanest path forward, including if it’s “don’t build that.”

Or write tocontact@alihassan.dev

Ali Hassan in a dark winter jacket, looking off to one side, standing in a stone courtyard with a minaret and cloudy sky behind him.