Forward-deployed engineering
Forward-deployed engineering means our engineers work inside your business, on your systems and your data, and do not leave until the software is running. This page explains where the model came from, why it is suddenly everywhere, and what it looks like at a company your size.
Palantir invented the role in the early 2010s. Its customers were intelligence agencies with problems no product spec could capture, so Palantir sent engineers to sit inside the customer, write code against real data, and stay until the system worked. Palantir called them forward-deployed engineers. For a decade the model was dismissed as too expensive to scale.
In 2026 that argument ended. OpenAI formed a majority-owned deployment company with more than $4 billion in funding. Anthropic, Blackstone, Hellman & Friedman and Goldman Sachs launched Ode, a $1.5 billion AI-implementation firm. Both gave the same reason: enterprise demand for hands-on deployment outran what an API or a consultant could deliver. Palantir's U.S. commercial revenue grew 133% in the first quarter of the year.
Most AI pilots die between the demo and production. The demo runs on clean sample data. Production runs on your ERP, your CRM, your accounting system, and a spreadsheet somebody built in 2019 that the whole company depends on. A consultant hands you a deck and leaves before that gap opens. A forward-deployed engineer is on the other side of the gap, inside your systems, when it does.
The second reason is domain. Your AI vendor knows models and does not know your business. Your team knows the business and does not know models. A forward-deployed engineer sits in the middle and owns the result, not the recommendation.
The firms above do not take a $20 million company. We do. The engagement starts with a fractional Chief AI Officer who finds the two or three AI moves that actually pay and validates the ROI before you spend. Then forward-deployed engineering builds them. The work covers four things:
Your team keeps the keys. We work inside your access controls and hand the system to a named owner in your company before we leave. The engagement ends with running software, not a roadmap.
A full-time AI engineer in Nashville costs well into six figures with benefits, takes months to hire, and needs a manager who can judge the work. A consultancy delivers a strategy and bills again for the build. Forward-deployed engineering is priced against the process it fixes: we baseline the hours and dollars first, and if the number does not clear, we tell you before you spend.
An engineer who works inside your business, on your systems and your data, and does not leave until the software is running. The term comes from Palantir, which built the model for intelligence agencies in the early 2010s.
A consultant delivers a recommendation. Forward-deployed engineering delivers running software and stays through the gap between demo and production, where most AI projects fail.
We work inside your systems and with your team. Most of the work happens remotely inside your access controls; we come to Nashville-area clients when it helps.
You do. It runs in your accounts, under your access controls, with a named owner on your staff trained to run it.
No. Your data stays in your systems. We set the guardrails, monitoring, and audit trail so you can show a customer or an auditor exactly what the system did.
Start with a complimentary industry analysis. You leave with the one project worth deploying first.
Schedule a Consultation