Forward Deployed Engineering
AI does not fix a broken process.
It automates it faster.
We embed forward deployed engineers inside your operation — mapping the edge cases your process documentation never captured, re-engineering the workflow for machine execution, and deploying agents directly onto the systems you already run. SAP. Salesforce. NetSuite. Dynamics. No migration. No rip-and-replace. No pilot purgatory.
Deployed onto your systems of record — not another platform to migrate to.
Execution was never the bottleneck. Context was.
The models have been good enough for a while now. What they are missing is everything your team knows and never wrote down — the exceptions, the workarounds, and the eleven-year analyst who is the actual system of record.
95% of enterprise GenAI pilots stall before production. Not because the model failed the demo — because nobody re-engineered the work around it.
Your process documentation is fiction
Every enterprise has an official workflow and a real one. The real one lives in the exception queue, the shared inbox, and a spreadsheet named final_v4. Generic AI is deployed against the fiction and then blamed for the gap.
The value is hiding in the edge cases
The happy path is most of the volume and almost none of the cost. Margin leaks through short-pays, mis-keyed POs, non-standard contract terms, and the ten-step manual recovery that nobody has ever documented.
Pilots are scoped to demo, not to run
A pilot proves a model can draft an email. Production requires it to survive audit, segregation of duties, master-data drift, and the Tuesday when the interface file arrives malformed at 04:00.
Nobody owns the last mile
The vendor ships a platform. Your team gets a login. The distance between an available API and a posted journal entry is exactly where every pilot goes to die.
Generic AI cannot handle the messy reality of enterprise operations — because the mess is the part that is specific to you.
A forward deployed engineer, inside your operation.
Not a discovery deck. Not a centre of excellence. An engineer at the desk beside your team, shipping into your environment from week one.
Map the Reality
We sit with the people doing the work and watch the exceptions, not the demo. We document what actually happens when the invoice does not match, the vendor is new, the approver is on leave, or the customer is a strategic account nobody is willing to auto-reject.
- Shadow the operators, not the org chart
- Instrument the exception queue to find the real volume
- Build a dependency graph of the workflow as it runs today
Re-engineer the Process
There is no one-step AI magic trick. We redesign the workflow as a system and decide, step by step, what runs autonomously, what needs a human in the loop, and what stays human-only because the risk or the relationship demands it.
- Autonomous where the rules are knowable and reversible
- Human-in-the-loop where judgment carries real exposure
- Human-only where trust is the product being sold
- Designed for adoption on the floor, not applause in the boardroom
Deploy on Systems of Record
No migrations. No parallel database. We build on top of SAP, Dynamics, Salesforce, or NetSuite — inside your controls, behind your SSO, writing through the same interfaces your auditors already understand.
- Native integration to the ERP and CRM you already run
- Your identity provider, your roles, your retention policy
- A full audit trail for every action an agent takes
- A rollback path defined before the first agent goes live
We built AI for our AI engineers.
Every forward deployed engineer walks in with FD Agent — our internal system for reading your world faster than any consulting bench can bill for it. Dependency graphs, custom retrieval, and codebase-aware models that ingest hundreds of pages of process documentation, integration specs and configuration workbooks before the first workshop starts.
Ingests your documentation on day one
Process manuals, SOPs, integration specifications, custom ABAP, configuration workbooks, prior consulting decks. Hundreds of pages parsed into something queryable before we have taken a single hour of your team's time.
Maps dependencies, not just text
It does not summarise your documents. It builds the graph of which fields, tables, approvals and downstream reports move when a single step in the process changes — so we know the blast radius before we touch anything.
Custom models per engagement
Tuned on your terminology, your material master, your GL structure and your document types — so the agent speaks your business rather than generic enterprise English.
Compresses the discovery bill
The multi-month, multi-consultant discovery phase collapses into weeks. You pay for engineering that ships, not for a bench learning your business on your dime.
FD Agent · Ingest
FD Agent is ours, not a reseller licence. It is why one engineer can carry the scope a discovery pod used to.
We do not do use cases. We do departments.
A single automated task is a rounding error on an enterprise P&L. We scope to the whole function — Finance, Procurement, Order-to-Cash, Service Operations — and we put a number against it before the work starts.
Revenue uplift
Faster quote-to-cash, fewer stalled orders, and recovered leakage on pricing, rebates and contract terms that were previously only caught by whoever happened to look.
Cost reduction
Capacity redeployed off exception handling and re-keying. The headcount question becomes what your best people do next, not how many of them there are.
Risk mitigation
Fewer control failures, cleaner audit trails, and policy applied consistently to every transaction instead of consistently to the ones that got reviewed.
Baselined during the audit, measured in your systems, and reported against your GL — not against our dashboard.
The questions your team will ask in the room.
Answered here so you do not have to defend them alone.
How is this different from hiring a systems integrator?
An integrator staffs a programme against a documented requirement. A forward deployed engineer starts from the undocumented reality, re-engineers the process itself, and ships working software into your environment. The deliverable is a running system in your ERP, not a design authority artefact.
Do we have to migrate off SAP, NetSuite or Salesforce?
No. That is the point. We deploy agents on top of your existing systems of record using the same interfaces, identity provider and controls you already run. Nothing moves, and there is a defined rollback path before the first agent goes live.
Our last GenAI pilot failed. Why would this be different?
Most pilots fail on context and last-mile integration, not on model capability. We spend the first phase mapping edge cases and exception handling, then re-engineer the workflow around a blend of autonomous, assisted and human-only steps. The AI is the final component, not the starting assumption.
How long before we see anything in production?
The audit runs about two weeks and ends with a scoped plan and a modelled ROI range. First agents in production typically follow within six to twelve weeks, depending on the department, the state of your integration layer, and your change-control cycle.
How do you handle security, audit and segregation of duties?
Agents run behind your SSO with your roles, write through interfaces your auditors already review, and log every action they take. Anything that would breach segregation of duties is designed as a human-in-the-loop step by default rather than automated and explained afterwards.
What does an engagement cost?
The audit is a fixed-scope engagement. Transformation work is quoted against the department and the modelled return, so the investment is set against a baseline we established together rather than against a day-rate card.
Start with the audit.
Two weeks. One department. We come in, map the workflow as it actually runs, quantify where the margin is leaking, and hand you a re-engineering plan with a number attached — whether or not you hire us to build it.
What you walk away with
- A dependency map of your real process, edge cases included
- A ranked backlog of what should be autonomous, assisted, or left alone
- A modelled ROI range with every assumption shown
- A deployment plan against your existing systems of record
We will tell you if the answer is that you do not need us yet.
Book an AI Audit