One team that designs, builds, tests, and ships your product, with AI workflows running through every layer. A senior developer, product designer, QA engineer, and project manager, accelerated by AI tooling that does the time-heavy production work.

Most agencies hand work between design, development, and QA shops, with weeks lost to translation. The AI Product Team runs as one unit on a single timeline, with AI accelerating the parts that used to eat half the engagement.

Real workflow. AI handles research synthesis, code generation, asset production, documentation, and test scaffolding. Senior engineers and designers make every architecture and product decision. We can walk you through the actual stack on a discovery call.

AI drafts boilerplate code, generates design variations, scaffolds tests, writes documentation, synthesizes research, and produces assets. The senior developer and designer review everything and make every meaningful call. More output per week, same level of judgment.

Because the gap between design and development is where most products lose weeks. One team means one conversation, one timeline, and design decisions that engineering can build the same week.

Four to six weeks from kickoff to a Minimum Sellable Product live in production. Discovery and design foundation come first, then design and development run in parallel, then quality assurance, deployment, and handover.

A clickable prototype lands in the first couple of weeks. The first working build follows shortly after, and daily progress lives in Slack or Teams throughout the engagement.

You receive the full source code in your GitHub, the design system in your Figma, the staging and production deployments running, the test suite, and complete documentation. Your team can take it from there, or extend the engagement for ongoing build.

We talk it through and adjust the plan. AI gives us flexibility most agencies lack, since variation and iteration cost less time. Many scope changes can be absorbed within the same window.

Full source code in GitHub. Design system in Figma. Staging and production deployments running. QA report and test suite. Documentation covering API, README, and architecture. Everything in your hands, fully transferable.

You do. Full transfer of source code, design files, and documentation. The AI Product Team builds it, you own it.

MVPs prove an idea exists. Minimum Sellable Products earn revenue. We build the second kind: a real product live in production that your first paying users can use, sign up for, and stay with.

Yes, this is a common path. We start with a discovery to assess what to keep and what to rebuild, then ship a production-ready version with proper architecture, real test coverage, and the deployment pipeline a vibe-coded prototype lacks.

Yes. Compliance shapes the architecture from the first sprint and informs every technical decision the team makes. We've worked across healthcare, fintech, and other regulated spaces.

Yes. The AI Product Team can run alongside your team, take a defined module, or own a discrete product or feature while your team focuses on existing work. We plug into your GitHub, Figma, Slack, and existing tooling.

Yes. The project manager translates everything into plain language and surfaces decisions the way a co-founder would. You see daily progress in Slack or Teams, and the work shows up in places you can read: the prototype, the staging environment, the design files.

Daily updates in Slack or Teams, weekly review calls, and a shared workspace where you see designs, code, and progress in real time. The project manager keeps the cadence and you stay informed.

Enough to make product decisions when they come up, usually a few hours a week. The project manager filters, summarizes, and brings you the calls that matter. Everything else runs in the background.

Your GitHub, your Figma, your Slack or Teams. We work inside your stack, with everything visible to you and your team from kickoff.

The Discovery phase is built to surface that early. If the idea has problems, we say so before the build. If new information emerges mid-engagement, we adjust scope rather than push through. Either way, you own everything built up to that point.

We use enterprise AI tooling with private workspaces, with client data kept out of training and signed agreements covering anything sensitive. Your code, your designs, your business data stay yours.

Yes. The handover includes full source, documentation, and a codebase any senior developer can pick up. You can take it in-house, hand it to another team, or come back to us for the next build.