Senior engineers who join your team and stay
No juniors. No bench-filling. Every engineer works inside your tools and process — one pod spanning AI and product engineering — then keeps the system running after launch.
What "dedicated team" means here
A dedicated team is a group of senior engineers who work only on your product, inside your own process, instead of a one-off project team. Every engineer on the pod is senior, and one pod can cover both AI engineering and standard product engineering. The same engineers who build your system stay on afterward to maintain it.
Who's on the pod
Every role below is filled by a senior engineer, never a junior filling a headcount number. Each of these roles will get its own page soon, with the exact scope, stack, and proof for that discipline.
AI Agent Developers
Build agents that plan a task, act inside your tools, and hand back finished work in production, not a demo.
RAG / ML Engineers
Build the retrieval, permissions, and evaluation layer that keeps AI answers grounded in your data.
LLM / GenAI Developers
Build production software on top of large language models — tool use, agents, and retrieval pipelines.
React / Python / Full-Stack Developers
Build and maintain the production interface and backend systems around every AI feature.
Mobile Developers
Build and maintain native and cross-platform mobile apps to the same senior, production standard.
How the pod works with your team
- You keep your tools. The pod works inside the stack you already use — your ticketing system, your repo, your CI — instead of asking you to adopt a separate one.
- They join your standups. The engineer reports into your existing sprint ceremonies, not a separate offshore process running on its own schedule.
- Code lands in your repo, under your review. It goes through the same pull-request and review steps your own engineers use.
- You set the priorities. The pod owns delivery. You decide what ships next; the engineer is accountable for getting it into production.
What you own
You own everything the pod builds: the code, the trained models, and the infrastructure it runs on. None of it is licensed back to us, and none of it depends on us to keep running.
Maintained after launch
The pod that builds your system is the pod that maintains it. After launch, you choose an ongoing maintenance agreement or a documented handover to your own team. Nobody hands you off to a different support team at go-live.
Proof — enterprise and startup
Enterprise: TankAware, for Sutherland Excavating Ltd. A senior pod built an AI and IoT platform for petroleum site inspections, replacing spreadsheets and paper logs. Reported results: 40% fewer manual errors and 30% higher monitoring accuracy.
"TankAware has revolutionized how we manage petroleum sites. The real-time data and automation have exceeded expectations." — Blake Sutherland, President, Sutherland Excavating Ltd.
Startup: PremiumAudit.io. A senior pod built an AI-powered insurance-audit platform on Bubble.io, using the Claude API to extract data and validate calculations.
