An AI development agency that ships every Friday, not someday.

The AI Dev Team is a weekly-sprint engagement where senior engineers, paired with AI, ship working code to production every Friday. You get a senior crew that holds to a predictable cadence, without the cost or hiring cycle of building the same team in-house. Each sprint ends with a working demo, tests, documentation, and a pull request you can actually read.

Internal dashboards, SaaS platforms, AI copilots and agents, mobile apps, customer portals, enterprise systems, and the integration layers that hold them together. If it needs a backend, a frontend, and AI somewhere in the middle, we have shipped one.

Both. We build MVPs for founders who need to ship before their runway runs out, and we extend production systems for engineering teams that need senior capacity without a six-month hiring loop.

It depends on scope. Most MVPs land in four to six weeks with an AI Product Team. Larger platforms run as a sequence of weekly sprints with a working demo every Friday, so you see progress against the plan instead of guessing.

Yes. We handle the database, the API layer, the frontend, the integrations, and the deployment, with the same team writing each layer so nothing gets lost between specialties.

Yes. CRMs, ERPs, payment systems, internal databases, legacy custom systems. Integration work is most of what modern software engineering actually is, and our engineers have plugged into enough of these systems to know where the sharp edges hide.

.NET and C# on the backend, with Node.js where the use case calls for it. React, Vue, Angular, or Blazor on the frontend. Python where the AI or data work specifically demands it. We pick the technology that fits the project, not the technology our team is most comfortable repeating.

Senior engineers review every change before it ships. AI handles a first pass on style and routine bugs, then a person signs off on logic and architecture. Automated tests cover the core paths, CI/CD pipelines catch regressions, and our internal quality framework verifies that AI-generated code meets the same standards as human-written code.

Yes. We stay on through monitoring, bug fixes, infrastructure scaling, and feature work that comes out of real user behavior. The team that knows the product best is the same team you keep working with after launch.

Yes. We set up environments on Azure, AWS, or Google Cloud, configure monitoring and alerting, schedule backups, and tune infrastructure cost so you are not paying for capacity you never use.

Security is part of the architecture from the first sprint, not an audit at the end. We use encrypted data at rest and in transit, secure authentication patterns, role-based access where it matters, and documentation that survives the audit conversation when it comes.

Yes. Weekly sprints, Friday demos, async-friendly documentation, and a backlog you can rearrange when the market changes. We are not religious about the rituals, but we are serious about shipping working code on a predictable cadence.

Every Friday, you see a working demo of what shipped in the sprint. Between Fridays, you have access to staging builds, the project board, and the team's Slack channel. There is no monthly status report standing in for actual progress.

We staff senior engineers only, equip every engineer with paid AI tooling, run design and engineering in the same repository, and sell fixed time blocks with clear deliverables. The result is software that ships faster than a traditional agency would deliver it and costs less than hiring the same team in-house.

Yes. We can extend an existing engineering team as a senior AI-native squad, plug into your repository and rituals, and keep your in-house people focused on the work only they can do.

AI products, fintech, healthcare, analytics platforms, marketplaces, education technology, and SaaS in general. The process adapts to the regulation, the data sensitivity, and the user expectations of each industry.

Yes. We migrate data, upgrade architectures, refactor old codebases into modern frameworks, and document everything as we go so the next round of changes does not require us in the room. AI accelerates the boring parts of refactoring, like rewriting tests and translating between framework conventions.

Always. Every project ends with technical documentation that another engineer can actually use, repository access, setup guides, and the architecture decisions in writing so nothing important lives only in a former contractor's head.

You own 100% of the code and 100% of the intellectual property. We sign the IP assignment on day one, hand over the repository at the end, and document the architecture so the code is actually usable by whoever takes it from there.

Yes. Support options range from on-demand fixes when something breaks, to monthly retainers for ongoing feature work, to longer engagements where we run the product team as a fixed extension of your business.