Forward deployed engineering
A forward deployed engineer (FDE) is a senior engineer embedded in your team who owns the outcome until it runs in production. The model enterprise AI uses for its hardest deployments, sized for SMBs and startups.
What is a forward deployed engineer (FDE)?
An FDE is a senior engineer who moves into your team for as long as the collaboration lasts and answers for one thing: that the AI ends up running in production. That means sitting with the people who do the process today, reading your systems as they are and not as the diagram says, and doing the part no demo ever shows: the connections, the permissions, the exceptions, the failures that hurt the business but that nobody gets to fix because of other priorities. The FDE is not the person who explains what should be built. The FDE builds it, ships it and stays until everything works.
Why the role exists
AI projects rarely fail on the model. They fail in the last mile: integrations between systems that were never designed to talk to each other, security constraints no brief captures, data spread across tools, and people with different definitions of success. That last mile is where most projects quietly die.
An SMB has the same last mile as a bank, with a smaller team and less room for a failed project. So someone has to own it from the inside. That is the FDE's job.
How it differs
A consultancy
Delivers a report or a roadmap and leaves the implementation to you.
Delivers the implementation. If there is a report, it is a by-product of building it.
A software agency
Takes a spec, builds it off-site and hands it over.
Discovers the spec inside your team, builds it with your systems and stays until it runs.
An AI platform
Fits your problem to its product.
Has no platform to sell. We pick the tool for the problem, and change it if the problem changes.
A fractional CTO
Leads the transformation and decides what to build.
Delivers what was decided. They often go together, and we offer both.
Is it for you?
A good fit when
- You have a real process with real volume, and it costs you time every week.
- Someone on your side owns the outcome and can make decisions.
- You want it running in production, not a demo.
- You want your team to run and extend it after we leave.
Probably not when
- You want a generic chatbot on your website.
- You are looking for the cheapest outsourced development team.
- Nobody internal will own the project.
- You want an AI strategy deck without the implementation.
Common questions
Do you replace our team?
No. We work alongside it. The engineer joins your tools, your repositories and your meetings, and the goal is that your people run the workflow without us.
Which tools and models do you use?
Whatever fits the problem. We work with the main model providers and with the automation, integration and observability tools your stack already has. We have no platform of our own, so there is nothing to push.
How long does a deployment take?
Weeks, not months, for one workflow: a few days to map it and connect the context, then iterations in production. Larger scopes are a sequence of workflows, not one big project.
How do you protect our data and code?
We work inside your infrastructure and your accounts, with the permissions you grant. Data stays where it is. Security and access are designed in the second step, not bolted on at the end.
What happens when you leave?
The workflow is documented, observable and yours. Your team has run it with us, and the training service exists precisely so the capability stays.
Book your FDE
Tell us the process that eats your team's week. We will tell you whether AI belongs in it, and how your FDE would take it to production.