FORWARD DEPLOYED ENGINEERS
Forward deployed engineers who take AI from pilot to plant floor
A forward deployed engineer (FDE) embeds with your team, connects AI to your real systems and stays until people use it every day. Modelcam runs FDEs on a 24-hour build cycle: named engineers on site by day, our India bench building by night.
- FOR
- AI-native companies, systems integrators and enterprises
- ENGAGEMENT
- 4–6 week sprint, pod or retainer
- FIRST WORKING RELEASE
- Week 2, with an exit option
- CONTRACT
- Modelcam Technologies LLC (US)
01 · THE GAP
Why do most AI pilots never reach production?
Because the value is lost between the pilot and daily operations, not in the model. MIT's 2025 study found 95% of enterprise gen-AI pilots showed little or no measurable P&L impact. The Modelcam Bridge™ closes that gap from both sides.
- 1The Factory. Our India bench builds, tests and hardens while you sleep.
- 2The Field. Named engineers on site, in your time zone, with the people who use the AI.
- 3The daily deck. One working release crosses from build to use every 24 hours.
- 4Your ground. Everything runs on your systems and your data. Nothing leaves without your say.
02 · THE ENGINE
What does a forward deployed engineer do?
An FDE turns an AI model into a working part of your company. With the Modelcam 24-Hour Engine™, what your users ask for at 6 pm becomes a tested release by 8 am the next morning.
- DOn site, 9 am to 6 pm. Engineers sit with your users and connect AI to your ERP, PLM, CAD data and documents.
- AEvening handoff, 6 pm. Today's requests become tonight's build list.
- NOvernight in India. The bench builds, tests, and adds evaluations and monitoring.
- BMorning handoff, 8 am. A tested release is waiting before your users log in.
Up to 10 releases in a two-week sprint, against one for a single-shore team (illustrative).
03 · THE GATES
How does a Modelcam FDE engagement run?
In five gates, from a 15-minute call to scale. Every two weeks you see something real. At each gate the decision is yours, and the evidence is on the table.
- 1Day 0 · Scope. Pick one workflow and the one number to move.
- 2Week 1 · Embed. Engineers land on site and measure a baseline on your own data.
- 3Week 2 · First release. Your exit option: stop here and it costs two weeks.
- 4Weeks 3–6 · Production. Live at one site, with a test, security and monitoring pack.
- 5Week 6+ · Scale. More sites with a Pod, or keep it running with a Retainer.
Who hires Modelcam forward deployed engineers?
Three kinds of teams that have chosen their AI and now need it working in production, on site, on their customers' systems.
AI-native companies
Your product works. Your customers need someone on site to connect it to their systems. Our engineers do that under your name.
Global systems integrators
You are building an FDE practice and need engineers who start now, on the 24-Hour Engine™, with delivery from India and the US.
Enterprises rolling out agents
You have picked the AI. You need engineers who connect it to ERP, PLM, CAD data and documents, and stay until it is used.
04 · THE ECONOMICS
What does an FDE engagement cost, and when does it pay back?
The most expensive AI project is the pilot that never ships. A gated engagement caps your downside at two weeks of sprint spend. Move the sliders to test it with your own numbers.
Which engagement model fits?
Start by proving one workflow. Expand with a pod. Keep it running with a retainer.
4–6 week sprint
One use case, live at one site, through all five gates.
How you pay: a fixed fee per gate. Spend stops when you stop.
FDE pod
A lead on site plus two or three bench engineers, scoped to one customer deployment from kickoff to handover.
How you pay: a monthly run-rate, reviewed at every gate.
Named FDE on retainer
One engineer who learns your stack and your customers, month after month.
How you pay: monthly, with an option to put part of the fee at risk against the agreed number.
QUESTIONS
Questions about forward deployed engineers
Updated 21 October 2026
What is a forward deployed engineer?
A forward deployed engineer (FDE) is a software engineer who embeds with your team, and your customers' sites, to turn AI into a working part of daily operations. At Modelcam, FDEs connect our products or custom agents to your ERP, PLM, CAD data and documents, then stay until people use them every day.
How is a forward deployed engineer different from a consultant?
A consultant advises. An FDE ships. Modelcam FDEs write and deploy production code on your systems, and are measured against one agreed number, not a slide deck.
What is the Modelcam Bridge™?
It is our model for closing the gap between an AI pilot and daily use. Two teams stand on either side: the Factory, our India build bench, and the Field, named engineers on site. Every 24 hours one working release crosses from build to use, on your systems and your data.
How does follow-the-sun delivery work?
Through the Modelcam 24-Hour Engine™. Engineers work on site from 9 am to 6 pm your time. At the 6 pm handoff, the day's requests go to our India bench, which builds and tests overnight. At the 8 am handoff, a tested release is ready before your users log in.
How soon will we see results?
Your users get a first working release in week 2. Production at one site follows in weeks 3 to 6. These are the gates of the Modelcam Five Gates™.
What if it is not working?
Stop at Gate 3. After the first release in week 2, you decide whether to continue. If you stop, your cost is two weeks of sprint spend.
Does our data leave our environment?
Not without your approval. Engineers work inside your systems, and your data stays where it is. For fully sovereign deployments, we run on the modelcam AI engine, on your premises.
How do you price FDE engagements?
Three ways. A sprint is a fixed fee per gate. A pod is a monthly run-rate. A retainer is monthly, with an option to tie part of the fee to the agreed number. Every engagement starts with a 15-minute scoping call.
Who do we contract with?
Modelcam Technologies LLC, our US entity. Delivery runs from India and the US.
Related AI services
Find the one workflow worth fixing first.
Fifteen minutes. One workflow. One number to move.