Discover, from the inside
The FDE sits with the people who do the work, maps how things actually happen versus how the org chart says they happen, and finds the friction nobody documented. That is where the real thing to build gets defined.
Forward Deployed Engineering
You bought the AI. Who owns making it work?
Most AI initiatives don’t fail on the technology. They fail at the two ends around it — figuring out the right thing to build for your operation, and getting your team to actually use it. A Forward Deployed Engineer is a senior iGenAI engineer embedded in your business who owns both ends, and the build in between, until the new way of working is the default.
The Gap
The two ends nobody owns.
MIT’s 2025 study found roughly 95% of enterprise AI pilots deliver no measurable return — and it is almost never the model. Discovery, build and adoption end up owned by three different people answering to three different priorities. The person who knows the operation can’t build it. The person who can build it is buried in their own roadmap. And nobody has the mandate to stay until the organisation actually changes how it works.
Hiring it out usually widens the gap. A consultant runs discovery and leaves before a line of code is written. A contractor builds exactly what is on the ticket, won’t say the ticket is wrong, and won’t stay to see if anyone uses it. One owns discovery without delivery; the other, delivery without ownership. The Forward Deployed Engineer role exists to close that gap.
The Engagement
One accountable owner, end to end.
Three phases, one senior engineer across all of them. The same person who discovers the problem builds the solution and drives its adoption — which is what keeps it honest.
Build, in your environment
Built against your real constraints and your real data — not a sanitised sandbox. Read-only from a copy, human review on anything client-facing, fully audit-logged.
Adopt, until it sticks
Workshops run, workflow friction debugged, internal champions trained, usage measured — the FDE stays until the solution is how the team works, not a tool sitting next to how the team works.
Hand over capability
When the FDE leaves, your team is more capable, not more dependent. You keep the working solution, the documentation and the people who know how to run and extend it.
The Difference
Not a consultant. Not a contractor. Not a systems integrator.
A consultant
Owns discovery, hands you a strategy, and leaves before a line of code is written. You get a plan — not a working, adopted system.
A contractor
Builds exactly what is on the ticket, won’t tell you the ticket is wrong, and won’t stay to see whether anyone uses it. Delivery without ownership.
A systems integrator
Fragments the work across specialists, so integration — where most AI projects actually fail — falls between them. No single owner of the problem.
An iGenAI FDE
One senior engineer accountable for the discovery, the build and the adoption. Nothing falls between roles, because there is nothing between roles.
The Measure
We don’t measure whether it shipped.
The metric we hold ourselves to is whether the solution is still in use after we are gone. Every engagement is measured against a baseline locked at the start — from your own system of record — so the result is a reading, not a debate. What you keep:
- A working solution, deployed in your environment on your real data
- An adopted workflow — measured, not assumed
- Documentation, and your own people trained to run and extend it
- A governance trail formatted for your risk partner and insurer
- A measured result against the baseline we agreed on day one
How You Buy It
Proof before commitment, at every step.
A staged ladder, so you buy evidence before you buy scale. Each rung is a decision point — you see a result on your own operation before committing to the next.
Discovery sprint
A short, fixed-fee embed: map the operation, define the buildable target, lock a baseline. Credited toward the build if you proceed — and useful on its own if you don’t.
Embedded build
The FDE builds, deploys and drives adoption in your environment. Adoption is inside the engagement, not an optional extra — it is the point.
Run & extend
Once it is working and adopted, an ongoing retainer keeps it healthy — monitoring, model updates, and extension to the next workflow.
Where It Fits
For problems that can’t be handed over as a spec.
A tool you bought that nobody uses
You picked it, deployed it — and three months later the team still works the way it always has. The FDE owns the adoption nobody else did, and makes the investment pay.
A process only your people understand
Too specific to brief a contractor, too operational for a consultant to build. It has to be discovered from the inside — which is exactly how an FDE works.
Workflow-heavy operations under governance
Intake, prebilling, claims, quoting, compliance chasing — document-heavy work in legal, accounting, distribution and professional services, built governed from day one.
Built For The Mid-Market
The enterprise model, at a scale a 20–500-person firm can use.
Forward Deployed Engineering was proven inside the world’s largest AI companies, at price points only the largest enterprises could reach. iGenAI productises the model for Australian mid-market firms — fractional and pod delivery, a fixed-fee discovery entry, and independence throughout: no licences resold, no vendor commissions, your data kept in your environment or in Australia.
Next Step
Start with the workflow that isn’t working.
Twenty minutes to find the one workflow where a tool already exists and isn’t used — or a process only your people understand. Then a fixed-fee discovery sprint proves the case on your own operation before you commit to anything ongoing.
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