Manual, fragmented workflows
People spend their days copying data, chasing approvals and assembling reports, but nobody can show where the hours actually go.
02 Enterprise AI & FDE
FDE Cost Reduction
Put engineers next to the work. Let AI change the real process.
A Forward Deployed Engineer does more than write code. They sit with the business, find the waste, build quickly and push adoption — measured by delivered outcomes, not by the number of tools installed.
DEFINITION
What is an FDE (Forward Deployed Engineer)?
An FDE is a forward deployed engineer. Instead of taking requirements from a distance, an FDE works inside the customer’s operating environment with frontline teams, understands the workflow, data and constraints, builds working software or AI solutions quickly, and owns adoption through launch.
FIT
Who this is for
Most cost-reduction programs fail because they sit too far from the work. The value of an FDE is proximity: see the real waste, change it within days, and make the change stick with the people doing the job.
Urgent cost pressure
You need measurable efficiency gains within one or two quarters without damaging quality or customer experience.
Tools changed, behavior did not
Collaboration software, RPA or AI platforms are live, but people still work the old way and the benefit cannot be attributed.
OUTCOMES
What you walk away with
Not a feature list — outcomes that enter the business, get measured and can be owned.
01
A verified cost baseline
Turn “it feels inefficient” into time, headcount, error-rate and cycle-time data. Find the waste worth changing.
02
Automation that enters daily work
Start with high-frequency, rule-based, recoverable steps. Build tools frontline teams actually choose to use.
03
A way to measure efficiency
Track handling time, first-pass yield and output per person — not the number of “AI features” launched.
04
An internal FDE seed team
Through paired delivery and retrospectives, leave behind the habits of finding, building and measuring improvement.
DELIVERABLES
What is delivered
Exact scope is tailored per project. Every deliverable has a clear acceptance method.
Process and time-cost map
Cost-reduction opportunity list and priorities
Two-week working prototype
Production automation or internal tool
Efficiency dashboard and review report
Runbooks and team handover
PROCESS
How we deliver
Every stage has a reviewable output, so the project never becomes a long black box.
01
Shadow
Follow real tasks with frontline staff. Record waiting, rework, context switching and manual handoffs.
02
Quantify
Estimate time saved, people affected, implementation effort and risk. Pick one wedge that can be proven in two weeks.
03
Build
Iterate with the people doing the work. Integrate with existing systems. Design exceptions and human fallback. Launch into real use.
04
Measure
Compare against the baseline. Lock in metrics and runbooks. Train an internal owner. Decide whether to scale or stop.
USE CASES
Where it shows up
These are typical entry points, not fixed templates. The real scope starts with your workflow.
Finance and reconciliation
Read invoices, match orders and bank records, flag exceptions and reduce month-end manual work.
Support and tickets
Classify, summarize, retrieve knowledge and draft replies so agents can focus on complex issues.
Content and operations
Generate multilingual assets, check compliance and sync channels to shorten campaign lead time.
Engineering delivery
Automate environment setup, test data, release checks and documentation to reduce waiting and rework.
STACK
Tools and technology
Tools serve the use case. We stay technology-neutral and reuse your existing systems first.
PythonTypeScriptNode.jsPostgresn8nDifyOpenAIAnthropicCloudflareLark / WeCom
FAQ
Common questions
Something else? Email us. We usually reply within one business day.
How is an FDE different from an outsourced or on-site developer?
Outsourcing usually delivers against a requirements list. An FDE owns the business outcome, finds what should change, and proves it with the smallest viable build. We write code, but we also care about process, adoption and measured impact.
How do you measure cost reduction?
We agree on a baseline at the start — handling time per case, daily throughput, error rate or cycle time. After launch we compare on the same basis and separate gains from tooling from gains from process redesign.
Do we need a long-term on-site team?
No. A typical rhythm is two to three days of observation on site, then a mix of remote and on-site iteration. After launch we reduce involvement and hand ownership to an internal team.
What if AI is not the right answer?
We will say so. Often the better fix is process redesign, deterministic automation or a better interface — not a large language model. The goal is to solve the problem, not to force AI into every step.
RELATED
Related services
These capabilities are often combined with this service.
Start a concrete conversation
Is this use case worth building?
Thirty minutes to lay out the goal, workflow and constraints. We decide the next step together.