Resources · Comparison
What you're actually choosing between.
Forward Deployed Engineering and a traditional Big Four AI practice are different shapes of engagement — different team models, different IP boundaries, different post-engagement paths. Pick on fit, not on familiarity.
SIDE BY SIDE
Seven dimensions, two models.
Engagement model
Engineers and governance architects embedded inside the client environment for 6–12 months.
Strategy-led; engineers brought in later under a separate workstream, often outsourced.
Team composition
Frontier engineers + governance architects, dedicated to one engagement. No junior rotation.
Pyramid structure — senior partners on the front line, juniors shipping. Team rotates across clients.
IP ownership
Client owns all engagement-specific code, models, configurations, and artefacts.
Varies by firm — IP boundary often ambiguous on AI assets, methodology, and reusable frameworks.
Cost framing
Outcome-tied retainer per phase, with milestones. No hourly billing.
Time-and-materials common. Larger fixed-price engagements often anchored to scope, not outcome.
Governance approach
Governance, evidence chain, and cost attribution wired in from day one — by design.
Governance designed as artefacts (target operating models, risk frameworks); runtime enforcement bolted on after.
Capability uplift
Embedded delivery means the client team works alongside FDE engineers daily. Handover is the default end state.
Training delivered as a separate offer. Knowledge transfer happens via documentation more than co-build.
Post-engagement support
Three paths: continue to Control (managed ops), client takes over with Enablement, or hybrid.
Typically transitions to a managed-services arm — sometimes the same firm, sometimes a partner.
WHEN EACH WINS
FDE wins when
- The use case is genuinely production-bound — pilot success isn't the goal, governed operations are.
- Governance and audit evidence have to be real at runtime, not on paper.
- You want your team to come out of the engagement able to run AI without us.
- The engagement is at least three months long.
Traditional wins when
- You need a target operating model written before any build begins, and the writing is the deliverable.
- The work is enterprise change management more than AI engineering.
- You're running a procurement-led process that requires Big Four panel firms.
- You have a managed-services arm already in place and want the same firm to operate the system long-term.
ON COST
The cost conversation, honestly.
FDE engagements are rarely the cheapest line item — frontier engineers don't bill at offshore rates. They are usually the shortest path to a governed production system, and they leave behind a team that can run it. Big Four engagements often look cheaper on the strategy phase and more expensive on the long run, because the build and operate phases compound.
The right question isn't "which line item is cheaper" — it's "which path produces a governed AI system the fastest, with the least rework, and the most internal capability at the end." That's the comparison worth running.
Next step
See what FDE looks like in practice.
The FDE service page covers the three-phase engagement model, team composition, and the outcome pillars in depth.
Ready when you are
Ready to Outpace?
Book a 30-minute discovery call with the Lastmile team. No pitch decks, no pressure — a focused conversation on where AI can move the needle for your organisation, and whether the structured operating model is the right fit.