Forward-deployed AI engineering
Close enough to the work to ship something useful.
Forward-deployed engineering means building with a client’s team, in the context of their real operation—not delivering a generic recommendation from a distance.
Why embed?
Most valuable workflows have details that are hard to see from a briefing: exceptions, unwritten checks, old tools, hand-offs, and the judgement people apply every day. An embedded approach lets us learn those details before committing to a solution.
How FDE Crew works.
- Embed on-site. Learn the workflow with the people who run it.
- Ship an agent, not a demo. Build a production system connected to the tools and information it needs.
- Hand it over and stay available. Help the team operate the system, then extend it when there is another workflow worth improving.
A practical standard for AI work.
We care about whether an agent makes a measurable difference to a real business process. That means starting with the workflow, testing against the exceptions that matter, and keeping people involved wherever judgement or accountability belongs.
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