Embedded AI Delivery
Some problems need someone in the room.
We put a senior technical person inside your operation. They build in your environment, on your data, and do not leave until it is running in production.
Why remote does not always work
Some builds are too specific to your environment to scope cleanly from the outside. The data is messier than it looks. The legacy systems have quirks nobody documented. The team has context that only surfaces in conversation.
For those engagements, we embed. One or two people inside your operation for a defined period, with a defined outcome agreed upfront. They write code in your stack, work with your team's schedule, and own the result.
This is not consulting with slide decks. It is engineering with skin in the game.
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Most AI projects fail in the gap between the demo and production.
What we build
End-to-end AI deployment
Full build in client environment, from data to production
Data pipeline architecture
Cleaning, structuring, and connecting the data the system needs
Legacy system integration
Connecting old infrastructure to new AI tooling
Custom AI application development
Software built in your stack, around your workflows, not ours
Workflow redesign and implementation
The process rebuilt around the new system
The process
How it works
We define the outcome
Agreed in writing before anyone shows up. What done looks like.
We embed
One or two people, your environment, your schedule, your stack.
We hand over
Documentation, training, running in production. Not a handoff, a transfer.