FDE for AI Companies
Your product is ready. Your customers' environments aren't.
Every enterprise deal you close comes with an implementation. That is where deals stall: the customer's data, their SSO, their security review, the workflow nobody wrote down. Your engineers are building the product. Your FDE reqs have been open for months.
Our Forward Deployed Engineers join your deployment team under your brand, sit in your customer calls, and get implementations live. Without the 4–6 month hiring cycle.
What you get
White-label. Your customers see your team, on your email, in your calls.
Python, TypeScript and Java, plus LLM integration, RAG, evals and agent orchestration.
Ramp-up on your product in 10 days.
Full US business-hour overlap and C1+ English. They talk to your customers directly.
Held to the Vitzi FDE Standard: senior, production code, at least one LLM project already in production.
How a white-label deployment runs
Discover
We learn your product and map the customer's data, systems and workflow. We define "live" with a metric the customer signs.
Embed
Your FDE joins your deployment team and the customer's channels under your brand.
Ship
Integrations, evals and guardrails built inside the customer's infrastructure, until your product runs there.
Hand off
Runbooks and training for the customer's team or yours. Or we stay and run it.
Who this is for
AI companies, Series A to C, selling to enterprise, with more signed implementations than engineers to deliver them.
Questions we get
- Will our customers know the engineer isn't our employee?
- Only if you tell them. White-label means your customers see your team.
- How fast can an FDE start on our product?
- Ramp-up on your product takes 10 days. The Vitzi Deployment Method then runs Discover in week 1 and Embed in weeks 1–2.
- What if the customer's stack is a mess?
- That is the job. Forward Deployed Engineers write production code inside the customer's systems and stay until it runs.
Have implementations waiting on an engineer? Let's talk this week.