The FDE model
Senior engineers, embedded where outcomes happen.
A Forward Deployed Engineer pod works inside your environment with product, data, security and operations. The brief isn’t “ship an AI feature”. It’s “move a business measure and keep moving it.”
Comparison
Why FDE beats outsourcing and staff augmentation.
| Traditional outsourcing | Staff augmentation | Entrans FDE | |
|---|---|---|---|
| Accountability | Deliverables | Hours | A business KPI |
| Speed to production | Months | Depends on you | Weeks |
| Outcome ownership | Vendor ships specs | Client owns everything | Shared scoreboard |
| Pricing model | Fixed bid / T&M | Rate card | Sprint, pod or outcome-linked |
| Knowledge transfer | Handover document | Leaves with the person | Built in from week one |
Pod composition
Small, senior, accountable.
FDE Lead
Owns the outcome and the client relationship.
Engineers
2–4 senior engineers across agents, data and platform.
Evaluation specialist
Builds golden datasets and keeps the scoreboard honest.
Engagement models
Pick the commercial shape that fits.
Fixed scope · 6–8 weeks
Outcome sprint
One outcome, one production release, measured end to end.
Monthly
FDE pod
A standing pod improving a portfolio of AI outcomes.
Fee tied to KPI
Outcome-linked pricing
Part of our fee rides on the number we agreed to move.
Stop building technology. Start engineering results.
Start with an outcome audit. We’ll map the systems, measures and FDE pod needed to move from AI ambition to production impact.