How we deliver
Senior engineers inside your business, accountable for what ships.
A small, senior team that works in your operation rather than next to it, owns a measurable outcome, and leaves your people able to run what it built. Made for the AI and modernization work that stalls when it is done at a distance.
Book a consultationThe problem
Most enterprise AI stalls between the pilot and the floor.
The pilot works. Then it meets the real data, the real workflow, and the people who have to live with it, and it stops. Requirements written months earlier no longer describe the problem. Each handoff between the business, the vendor, and IT loses a little of what mattered. By the time the feedback gets back to whoever is building, the budget is gone.
Forward deployed engineers close that distance. They sit with the operators and the data, learn what the problem actually is, and build against it in short loops. The work gets to production because the people building it never left the room.
What a forward deployed team does
Owns the outcome, not the backlog.
Takes an outcome, not a ticket
The engagement is scoped to a result the business can measure: a model in production, a process cut in half, a platform your teams can extend. Not hours, not seats.
Works inside the workflow
Engineers sit with product owners, operators, and the people who use the system. They see the data as it really is, not as the data dictionary describes it.
Senior by design
Small teams of people who have shipped this before. No bench to train, no pyramid to bill.
Ships in weeks
Working software in front of real users early, then improved in short loops. The build-learn cycle is measured in days, not quarters.
Builds with your constraints
Your security model, your platforms, your data access rules, your change process. The result has to run inside your operating reality, so it is built there.
Transfers the capability
Your engineers pair on the work from the start. When the team leaves, the system, the practices, and the judgment stay.
What it is not
Not staffing. Not a deck.
Forward deployed engineering sits between two models that often disappoint, and it borrows the best of each.
Versus staff augmentation
Augmentation adds individuals to your backlog and leaves the outcome with you. A forward deployed team arrives as a unit with a lead, a plan, and accountability for the result.
Versus traditional consulting
Consulting too often ends at a recommendation. Our engineers write the code, run the pipelines, and stay until it works in production.
Versus a vendor build
A vendor builds to the requirements you wrote at the start. A forward deployed team builds to the problem as it turns out to be, because it is there when the requirements change.
How an engagement runs
Discovery in the workflow, then build, then hand over.
- Weeks one to two: the team embeds with the business owner and the operators, maps the real process and the real data, and agrees the outcome the engagement will be judged on.
- Weeks two to eight: working software in front of users early, improved in short loops. Architecture, security, and governance decisions are made with your teams, not for them.
- Week eight onward: the system runs in production under your monitoring. Your engineers have paired on it throughout and take ownership on a date we set together.
- The team: an engagement lead, forward deployed engineers in AI, data, or software as the problem demands, and a technical program manager who keeps the work honest about scope and dates.
Where it fits
The work that does not survive a handoff.
- AI pilots that need to reach production: assistants, agents, document intelligence, and the data and governance underneath them.
- Data foundations where the real problems only show up at close range: pipelines, quality, lineage, and the semantic layer the business will trust.
- Legacy modernization where the system is still running the business and cannot be paused for a rewrite.
- Product and platform teams that need senior engineering capacity with an outcome attached, not another contractor to manage.
- Internal AI capability: standing up your first AI engineering team and leaving it able to run without us.
Outcomes
Measured by what your team runs after we leave.
Two engagements that show the model at work: an embedded team that established a Fortune 100 insurer's first AI engineering capability in eight weeks, and a children's hospital that used an embedded Fusion team to target 30% faster delivery across operational teams.
Common questions
Questions we hear often.
What is a forward deployed engineer?
A senior engineer who works inside the client's business, alongside the people who own the process and the data, and is accountable for getting a working system into production. The model comes from companies that learned that the hardest enterprise problems cannot be solved from a distance.
How is this different from staff augmentation?
Augmentation supplies people; you own the outcome. Forward deployed engineering supplies a team that owns the outcome with you, led by someone accountable for scope, quality, and the date.
How senior are the people?
Practitioners who have shipped the kind of system you need, usually with ten or more years in the discipline. We keep teams small so that every seat is senior.
How fast can a team start?
Discovery can begin within two to three weeks of agreeing the outcome. The first working software is typically in front of users inside the first month.
What happens when the engagement ends?
Your engineers have been pairing on the work since week one. We set the handover date together, document what matters, and stay available for a defined period afterward. The measure of success is how quickly you do not need us.
Related
Forward deployed engineering is how we deliver across Consulting, AI Solutions, and Talent. Read the thinking behind it in Forward deployed engineering: why the best AI teams embed.
Next step
Bring us the problem as it actually is.
Book a consultation and we will tell you whether an embedded team is the right answer, and what it would take to get the work into production.
Book a consultation