Service 02
Forward-deployed AI engineering
Forward-deployed means we work inside your environment, next to your engineers, on your real problem. No throwing a spec over the wall. We build in your repos, on your data, and stay on the hook for what runs in production.
What it includes
- An engineer embedded with your team, in your tools and repos
- Direct access to real data and systems, under your access controls
- Weekly working software, and a handover your team can run without us
What you get
- Production code in your repositories, reviewed and documented
- The infrastructure to run it, or integration with what you have
- A team that understands the system because they watched it get built
Common questions
What does forward-deployed actually mean?
We embed with your team and build inside your stack instead of delivering from a distance. Your engineers see every decision, and the code lives in your repos from day one.
Who owns the code?
You do. It is built in your repositories under your license. No lock-in to a platform only we can operate.
How is this different from a dev shop?
A dev shop delivers a spec and leaves. We stay embedded through production, own the incident response, and treat your constraints as ours.
Start a project
Name the workflow that eats your team's week
Name the workflow that eats your team's time. We will tell you honestly whether AI fits, and if it does, scope a first piece with a known price.