FORWARD-DEPLOYED ENGINEERING

Forward-Deployed Engineering. One Senior Engineer Inside Your Team, a Studio Behind Them.

For mid-market teams whose AI pilot stalled or never started. A senior engineer works inside your team and puts one workflow into production in the tools you already run. You keep the code.

Forward-deployed engineering services put a senior engineer inside your team to get AI and automation into production. At DK Studio that engineer maps the process as your people run it, builds inside your systems of record, adds evals and human approvals, and hands over code you own. A Diagnostic is $7,500 fixed. Embedded work is $16,000-$20,000 a month.

By Christian Vismara

WHAT YOU GET

Everything in the box.

A senior engineer in your stand-up

One named engineer, 2-3 days a week, in your Slack or Teams and in your meetings. Christian, our CTO, is in New York and can be on site. The rest of the studio works remotely.

The real process, written down

What your team does day to day, exceptions and workarounds included, side by side with what the manual says. Pilots built on the manual version break on the first exception.

Built where your data lives

Our engineer builds inside your ERP or CRM and commits to your own repositories. Your team keeps working in the tools it already knows.

Evals from your own cases

A test set built from real past cases, scored on every change. "It feels better" becomes a number your ops lead can check.

A person signs off where money moves

Payments, refunds, bank-detail changes and anything with legal risk wait for human approval. An audit trail records every action the system takes.

Code you own, and a way out

The code sits in your repository, prompts and evals included. Ownership and the exit plan are written into the scope before we start. That is our answer to Gartner's warning about vendor lock-in.

THE PROCESS

How we build it.

1

Map the real process

Deployment Diagnostic, 2-3 weeks. We sit with the people doing the work and set baseline numbers for one workflow from your live systems.

2

Decide where AI goes

A model goes only where a step needs judgment. The rest is plain code, and anything that moves money waits for a person. You get an eval plan and a fixed quote.

3

Build inside your tools

Production Sprint, 6-8 weeks. One workflow built in your systems of record and tested against the eval plan as it grows.

4

Shadow mode, then go-live

The system works next to your team on live cases before it acts alone. At go-live you get the written handover. The AI Team retainer is there if you want us to keep running it.

STACK

Tools we use.

Claude (Anthropic)GPT (OpenAI)Gemini (Google)Open-source modelsVercel AI SDKLangfuseOpenTelemetryNetSuiteSalesforceHubSpotQuickBooks OnlineSlackMicrosoft Teamsn8n
PRICING

What forward-deployed engineering costs.

A Deployment Diagnostic takes 2-3 weeks and costs $7,500 fixed, credited against the Production Sprint if you go ahead. That Sprint takes one workflow live in 6-8 weeks at $25,000-$60,000 fixed, and we quote it at the end of the Diagnostic. For ongoing capacity there is the Embedded Engineer: a senior DK engineer inside your team 2-3 days a week, with the studio behind them, at $16,000-$20,000 per month. After launch, the AI Team retainer keeps the system running from $3,000 per month.

Still deciding what to build first? That is the five-day AI Readiness Audit, from $800, a different product made for owners and founders. The Diagnostic is for teams that already run the process and have systems to map.

FAQ

Common questions.

Forward-deployed engineering services put an engineer inside the client's team to build AI and automation in the client's own systems. Palantir popularized the forward-deployed engineer title, which borrows from military language. A product engineer builds one capability for many customers, while a forward-deployed engineer builds many capabilities for one customer. At DK Studio that means one senior engineer embedded 2-3 days a week, with the rest of the studio behind them.
A consultant hands you a recommendation, and a remote build team works to a spec from outside your company. An embedded engineer sits with the people who do the work and builds inside your systems, so the exceptions show up before go-live. Watch the label, though, because Gartner warns about "FDE washing", its term for ordinary consulting relabelled as FDE. The name itself proves nothing either way: some firms have embedded engineers for years under other titles. Ask who will be in your meetings and what they have put into production.
No, and the way we work is designed around that. Gartner expects 70% of enterprises to abandon agentic AI built by vendor FDEs by 2028, because costs climb and the client cannot evolve the system on its own. The code lives in your repository and comes with evals plus a written handover your engineers can follow. Ownership and the exit plan are written into the scope before any build starts, and keeping us on the AI Team retainer afterwards is your choice.
At DK Studio, a Deployment Diagnostic costs $7,500 fixed and is credited against the Production Sprint, which runs $25,000-$60,000 fixed for one workflow in production. An Embedded Engineer, 2-3 days a week, costs $16,000-$20,000 per month, and the AI Team retainer starts at $3,000 per month after launch. For comparison, Gartner puts vendor FDE consulting fees at up to about $200,000 per quarter per use case. We publish our prices so you can compare them before the first call.
Hire one if you need the role for years and can wait for the search. Gartner estimates about 2,000 active FDEs exist, and one recruiter quoted by Pragmatic Engineer guessed that maybe 10% of engineering candidates want the role. Paraform puts FDE searches at 8-12 weeks, with a stated placement fee of around 25% of first-year base salary. An embedded engineer can get the first workflow into production while you search, and the written handover gives your new hire something solid to inherit.
The engineer needs access to the systems the workflow touches, time with the people who do the work, one owner for the process and someone who can approve changes involving money or risk. Without system access the work drifts back to demo data, which is how pilots stall. We agree the days and the first goal before the start date.
Yes, in New York, where Christian Vismara, our CTO, is based and can be on site. The rest of the studio works remotely. On-site time matters for this work because the undocumented exceptions show up when you sit next to the team. For scale, OpenAI's own FDE postings ask for up to 50% travel, and Pragmatic Engineer reports Palantir FDEs spend around 25% of their time on site.
You get one senior engineer as your day-to-day contact, inside your team 2-3 days a week. Behind them, the studio adds more engineering or design help when the agreed scope needs it. If the job needs a second engineer for a stretch, we add that person to the scope and the price before they start. One accountable engineer keeps the context in one head, which is the point of forward-deployed work.
FREE FIT CALL

Want the engineer in your stand-up, not in a status report?

Tell us the workflow and the systems it runs on. We'll tell you whether a Diagnostic or an Embedded Engineer fits better.

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