Forward-deployed engineers inside your systems and your team
A forward-deployed engineer (FDE) works inside your team to deploy AI and connect the systems you already run: your standups, your codebase, your priorities, for an agreed period. The work is done where your team can see it, and the knowledge stays when we leave.
Inside your team, not off-site
The engineer picks up tickets from your board, sits in your reviews, and makes decisions in the open where your team can see the reasoning.
Much of the work is in the joins: between the tools you already run, and between a new AI feature and the data and permissions it depends on. When the engagement ends, the knowledge stays with your team.
When it makes sense
- You have developers, but nobody who has built this particular thing before — payments, offline sync, a security review, AI in production
- Something needs to move now, and a permanent hire is months away
- The work is too tangled with your existing systems to hand to an outside team
- You want your own team able to maintain it afterwards rather than dependent on a vendor
Deploying AI and connecting your systems
Deploying AI inside your systems
Taking an AI feature from a prototype to something running in your own environment.
- Wired into your data, with the access each step needs and nothing more
- Fitted into the workflows and approval steps your team already uses
- Evals before launch, and logging of what the system did and why
Integrating disconnected tools
Connecting the CRM, accounting, ERP, e-commerce and support tools you already pay for.
- Connections through their APIs, webhooks and scheduled syncs
- One source of truth for each record, agreed up front
- Errors that alert someone, rather than failing silently
- Documented, so your team can change it later
Structured, not open-ended
A defined period
Agreed up front — typically measured in months, not weeks.
Full or part-time
Working in your tools and your process.
Nothing held back
Code, documentation and decisions are yours throughout — not leverage for the next contract.
A stated handover
What was built, why it was built that way, and who on your team now owns it.
Backed by the practice
An embedded engineer can pull in a second pair of eyes on security, cloud or payments without a new contract.
Four ways to work with us
Advisory
We map the tools you run and how data moves between them, and hand you an integration plan: what to connect, which tool owns each record, and in what order.
Build
We build the integrations or the AI deployment as a project, against a scope and price agreed up front.
Run
We stay on to watch the connections and the AI features we built, fix failed syncs, and keep up with changes in the tools at either end.
Embed
One of our senior engineers works inside your team: your standups, your codebase, your priorities, for an agreed period. Not a body on a contract — someone who owns outcomes, makes architectural calls, and leaves your team better able to make them after. For teams that need depth they can’t hire for, or need to move on something before a permanent hire lands.
Straight answers on embedded engineering
What does a forward-deployed engineer do for a smaller business?
They join your team for an agreed period and do the hands-on work that is hard to hire for: putting an AI feature into production, connecting systems that don't talk to each other, or untangling a part of the codebase nobody owns. They work in your tools and your process, and leave the code, documentation and decisions with your team.
How do you integrate disconnected SaaS tools without replacing them?
Keep each tool for what it does well and connect them through their APIs, webhooks or scheduled exports. Decide which tool owns each record, such as the customer or the invoice, and sync from there. Add monitoring so a failed sync alerts someone, and document every connection so it can be changed later.
How is embedded engineering different from staff augmentation?
Staff augmentation adds a person to your team, directed by you and paid for their time. In embedded engineering, the engineer is accountable for an agreed outcome, makes technical decisions, and hands over what they built and why.
| Staff augmentation | Embedded engineering | |
|---|---|---|
| Who directs the work | You | Agreed together, against an outcome |
| Accountable for | Tasks assigned | The agreed outcome |
| Seniority | Varies by role | Senior engineers only |
| At the end | The person leaves | A stated handover: what was built, why, and who owns it |
| Scope and price | Time, per person | An agreed period and scope, priced up front |
How do you connect AI to our CRM, ERP or ticketing system?
Through the systems’ own APIs, webhooks or exports, under your existing access controls. Decide which system owns each record, give the AI step only the data it needs, and write results back where people already work, such as a field in the CRM or a draft reply in a ticket, for a person to approve. Log every call, alert when a sync fails, and document each connection so your team can change it later.
Who it’s for
Teams with a roadmap they can’t staff, companies facing a technical problem outside their team’s experience, and organisations that want the capability to stay in-house afterwards.
Who it isn’t for
Anyone looking to fill a seat. This is not staff augmentation, and we price and scope it accordingly.
Start with an honest look at what you run
Tell us what you're running today and where it hurts. We'll come back with the two or three changes worth making first — and if the answer is that your setup is fine, we'll say that instead.