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AI SaaS / AI Product Development

Complete AI-native products: architecture, frontend, backend, auth, billing, agents, pipelines, dashboards and cloud.

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The problem

An AI product is a product first. Models change monthly; billing, onboarding, permissions, latency and cost control do not. Teams that start from a demo notebook spend the second half of the project rebuilding the first half. We start from the product loop and place the model where it earns its keep.

What we build

  • Multi-tenant SaaS with auth, roles, billing and usage metering from day one
  • Model pipelines with evaluation, fallbacks and per-customer cost tracking
  • Customer-facing dashboards and admin tools that show what the AI did and why

Product strategy, AI architecture, Billing and subscriptions, Dashboards, Monitoring

How it works

  1. 01

    Product loop

    One core loop, one paying user profile, one metric. Everything else waits.

  2. 02

    Architecture

    Stack chosen for speed now and scale later; data model, AI plan, cost model and a week-by-week build plan.

  3. 03

    Weekly sprints

    Design system, core loop, AI features, integrations, billing. A live demo every week on a staging URL.

  4. 04

    Launch and iterate

    Real users, analytics from day one, fixes shipped daily, then the roadmap.

Work that proves it

  • RotateProduct home page: product photos turned into studio-quality video, with a drink can example

    RotateProduct

    AI product photo to rotating video for e-commerce

    Designed and developed for the client: the product-photo to rotating-video pipeline and the self-serve plan flow.

  • PDFData home page: an extracted invoice card beside a review queue of ready and flagged documents

    PDFData

    AI invoice and receipt processing to Excel, CSV and JSON

    Designed and developed for the client: extraction pipeline, bulk processing and the export and API surface.

  • Userdesk home page: AI assistants that collect leads, beside a chat preview and content sources

    Userdesk

    No-code AI support and lead assistant trained on your site, Notion, PDFs and Drive

    Designed and developed for the client: retrieval pipeline, the embeddable assistant and the lead hand-off flow.

What you get

  • Product scope and architecture document

  • Working product on your cloud accounts

  • Billing and subscription setup

  • Model evaluation set and cost dashboard

  • Analytics instrumentation

  • Admin panel

  • Documentation and runbook

Questions

What's included in an AI product engagement?
A scope and architecture document, then the product: the core loop, auth and roles, billing, the AI features and the admin panel, running on your cloud accounts. Alongside it you get a model evaluation set and a cost dashboard, analytics instrumented from the first deploy, and documentation with a runbook. A live demo on a staging URL every week is part of the arrangement, not a milestone.
How long to a first release users can pay for?
Six to twelve weeks to a first release that real users can pay for. The range is set by how many roles the product has, whether billing is a flat subscription or something usage-based, and how much of the AI work needs its own evaluation loop. We cut scope to protect the date rather than the other way round.
What do you need from us?
One person who can make product decisions in the week they are asked, the cloud and payment accounts in your name, and access to whoever will use the thing. Weekly demos need forty-five minutes of your time, and the first ten customers you have in mind shape the build more than any feature list.
Who owns the code and the data?
You do, from the first commit. The repository, the cloud accounts, the payment account and the model keys are yours throughout, so there is nothing to transfer at the end except knowledge. Handover is the documentation, the runbook and a session with whoever takes over.
Can you take over a product someone else started?
Often, yes. We start with a short review of the code, the data model and the infrastructure, and come back with what is worth keeping, what needs replacing and what it costs to carry on. If the honest answer is that rebuilding one part is cheaper than repairing it, we say so before you commit to a plan.

Not sure where to start?

Describe the problem in a few lines. You get a straight answer on what we would build and how long it takes.

Book a 5-minute growth call
Book a 5-minute growth call