A Forward Deployed Engineer works inside your company's real systems, maps the workflow, ships the logic, and keeps it running in production, without asking your team to learn a new tool.
The gap
Most AI projects don't fail at the model. They fail in the last mile: connecting real systems, understanding messy workflows, handling edge cases, and getting users to trust it inside real teams.
Where most AI projects stall
Idea
One person is carrying it
It moves while they push it. Their priorities change and it stops.
Prototype
Systems don’t connect
Data sits in silos with no clean path between the tools that hold it.
Pilot
Security & permissions
Access is layered and slow. Risk review outlasts the pilot.
Handoff
Nobody owns it
Handoff ends the accountability. No one is paid to finish it.
Production
No production path
No process for testing, iterating, or supporting it once it is live.
What you hear six months in
Sales lead
It worked in the demo. Why isn’t it working for us?
Engineering
We can’t get the data or the access it actually needs.
RevOps
We don’t trust it enough to point it at real records.
Support
It’s faster to go back to doing this by hand.
The gap
AI is capable. Your systems are complex.
01
Your systems, workflows, and exceptions were never designed for an AI agent.
02
The prototype is easy. Production requires integration, permissions, testing, and iteration.
03
The farther builders are from users, the worse the system becomes.
From demo to dependable.
What is an FDE?
A Forward Deployed Engineer, or FDE, is how Clientell brings AI into production inside your actual Salesforce org, Marketing Cloud instance, and CRM, not a sandbox, not a staged demo.
Instead of starting with a generic rollout, the FDE works directly with your team to fix one real, stuck problem first, prove that it works, and only then automates whatever repeats.
This is what moves AI from a pilot that never ships to something running in production, without anyone on your team needing to learn a new tool.
One workflow
Nothing about who asks or what they ask for changes. What changes is the path between the question and the answer.
Operating principles
The goal is simple: make AI systems that work inside your business, not just in a demo.
The context an FDE maps on day one is the same map our Context Graph keeps governed for every agent that comes after.
The part everyone else skips
Your teams keep using the tools they already know. A Forward Deployed Engineer maps the workflow, connects the systems, deploys the logic, and keeps it running in production.
What your teams see
New account
Acme Co.
Ticket #8421
Customer issue
Vendor payment
$18,450.00
Inventory update
SKU-1937
What happens underneath
Everything the work already lives in gets pulled into one deployment path: mapped, wired, shipped, and watched by the same engineer who owns whether it stays up.
FDE-owned deployment layer
Live in production
What your team still does
What's different underneath
How it works
One engineer, scoped to the workflow costing you the most, embedded in the systems you run today, and measured on what it actually saves. Scroll to see how it moves.
Days 1–3
The FDE starts with a diagnostic, not a workshop: which processes are burning the most hours, slipping the most deals, or putting the most revenue at risk.
Not included: a generic rollout plan, a menu of AI use cases, a workshop.
From a live engagement
One person used to be the only one who knew how this workflow worked. Every question went through them. The FDE rebuilt it so the knowledge lives in the system now, not in someone's head.
Before
Knowledge lived in one head. Every question queued behind one calendar.
After
Knowledge lives in the system. A person is needed for the edge cases, not the routine.
Compounding
When an FDE solves a workflow, that fix becomes a permanent part of the platform, not a favor you have to ask for again. The problem gets solved once. It doesn't come back as new work next quarter.
Questions
An implementation partner scopes a project and hands it off. A forward deployed engineer embeds inside your team and owns the backlog until it is done. The same person who built it is the one running it.
Scoped, flat fee, embedded
Send us what's stuck in your queue. No training deck, no rollout plan. Just the backlog, and an engineer who starts inside it.