AGMM / Forward deployed AI engineering
Engineers for problems that cannot be solved from the outside.
Sam Wall and Adam Gillett work inside the real workflow, alongside the people closest to it. We find the constraint, build the software or AI system and stay with the work through deployment.
Greater Manchester / UK and international delivery
- 01 Diagnose
- 02 Design
- 03 Build
- 04 Deploy
The operating model
Forward deployed means the engineering happens where the problem lives.
It is not a report passed across a table. We work with the business leaders, operators and frontline people who understand the process, then take responsibility for the technical route from first diagnosis to a production system.
AI is an enabling layer, not the starting assumption. If the right answer is conventional software, an integration or a simpler process change, that is what we recommend and build.
One route through the work
Discovery, engineering and deployment stay connected.
- 01
Work inside the real problem
We speak to the people doing the work, inspect the tools and trace the hand-offs. The operating reality is the brief.
- 02
Find the constraint
We identify the step where time, margin or momentum is being lost and agree what a useful result must change.
- 03
Build where it has to run
We design, write, integrate and test the system against your actual data, rules, exceptions and existing software.
- 04
Deploy it into ordinary work
We put the system into use, improve it with the people relying on it and leave your business able to operate it.
The people in the room
You speak to the people doing the work.
AGMM is Sam and Adam working together from the first conversation through implementation. There is no separate sales team and no hand-off to an anonymous delivery bench.
01
Sam Wall
Architecture, engineering and deploymentSam works across the technical system: architecture, software engineering, integrations, AI behaviour, testing, deployment and the decisions that keep the build reliable.
02
Adam Gillett
Process, implementation and adoptionAdam stays close to the people and process around the build, keeping requirements grounded in daily operations and helping the new way of working land clearly inside the business.
When to bring us in
The problem is important. The route through it is still unclear.
- An AI pilot works in a demonstration but has not reached production.
- A critical process crosses inboxes, spreadsheets and software that never agree.
- The business problem is clear, but the technical route is not.
- A system has to fit the way your people actually work, including exceptions.
- You need somebody to own discovery, engineering and deployment together.
What we deploy
The category changes. The practical work stays the same.
Forward deployed engineering is how we work. These are the systems we build around the operational need.
- 01business process automation
Work that should happen once happens three times, in three places, and nobody owns the gap between them.
↗ - 02custom CRM development
The CRM describes a business you do not run, so nobody keeps it up to date, and the numbers in it cannot be relied on.
↗ - 03quoting and estimating software
Revenue waits on a quote, and the quote waits on the one person who knows how to price it.
↗ - 04scheduling and booking software
Scheduling depends on somebody remembering, so the busier you get the more it costs you.
↗ - 05custom process systems
A commercially important process is spread across inboxes, spreadsheets and memory because no off-the-shelf product matches how the work actually moves.
↗
Ways to work together
A defined deployment, an embedded contract or continuing improvement.
Project deployment
One operational constraint, owned from discovery through a working production system.
Embedded contract
Forward deployed engineering capacity inside your team for an agreed period and outcome.
Continuing improvement
An ongoing route for operating, measuring and improving systems already in use.
Whichever shape fits, the route in is the same: a free discovery call, then a fixed £2,000 constraint audit that scopes and prices the work before anyone writes code. See what it costs.
Clear answers
Forward deployed AI engineering, without the jargon.
What is a forward deployed AI engineer?
A forward deployed AI engineer works directly with a business inside its real systems and workflows. They move from discovery and technical scoping through design, engineering, integration and production deployment, rather than handing over a recommendation for somebody else to build.
How is forward deployed engineering different from AI consulting?
Consulting can stop at analysis, recommendations or a roadmap. Forward deployed engineering includes the hands-on technical work required to make the change real: writing code, connecting systems, testing edge cases, deploying the result and improving it with the people using it.
Can we hire AGMM as contract forward deployed AI engineers?
Yes. AGMM can work on a defined deployment, as an embedded contract team for a fixed period, or through a continuing programme of improvements. The same discovery call is used to understand the problem and decide whether the fit is sensible.
Do we need an internal technical team?
No. We can work directly with business owners, operators and frontline teams, or alongside an existing technical team. What matters is access to the people, systems and decisions around the workflow being changed.
Is a forward deployed AI engineer the same as an AI deployment engineer?
The terms overlap. Forward deployed AI engineer, AI deployment engineer, embedded AI engineer and applied AI engineer can all describe customer-facing engineers who turn an operational problem into a working production system. Forward deployed puts particular emphasis on working inside the customer environment from discovery through deployment.
Start with the constraint