Forward Deployed Engineering
ServiceNow AI specialists embedded in your team and accountable for a production outcome.
Bring ServiceNow platform mastery, AI engineering and domain understanding together inside the customer environment.
The gap between a promising AI pilot and a production result is rarely another product. It is often the absence of people who understand the platform, AI engineering and the business problem at the same time.
Traditional hand-offs separate discovery from engineering and make accountability for the final outcome unclear.
What changes
From fragmented activity to a controlled outcome.
Before
A use case moves between advisers, engineers and operational teams with context lost at each hand-off.
With an FDE pod
The same specialist capability finds the right problem, builds inside the environment and stays accountable through production.
After
One workflow is working under real constraints, with a clear evidence base for whether and how to expand.
How it works
A practical route from the current problem to an operational result.
Find the problem
Work with users and domain experts to choose a bounded workflow with material value.
Build for real
Use the customer instance, data, permissions, governance and integration conditions.
Prove in production
Measure the outcome with real users rather than stopping at a demonstration.
Compound
Harden proven work into reusable capability so each subsequent outcome becomes faster.
Capabilities
What the solution brings together.
ServiceNow platform mastery
Native patterns, data, workflow, security and operating knowledge.
AI & agentic engineering
Model selection, orchestration, evaluation, guardrails and monitoring.
Domain understanding
Translate the mission and user context into the right technical problem.
Reusable accelerators
Apply existing knowledge, assessment, testing and delivery components where they genuinely help.
What you receive
Defined outputs, not open-ended activity.
- Prioritised production use case
- Working solution on the customer instance
- Evaluation and control evidence
- Operational ownership and handover
- Expansion recommendation based on results
Approach & potential benefits
Proof before commitment
The First Value Sprint creates a bounded way to judge the model on a production result. The relationship expands only when the evidence supports it.
Where it fits
Use this solution when…
- A valuable AI workflow is stuck between pilot and production.
- The problem requires both ServiceNow and AI engineering expertise.
- You need delivery accountability without building a permanent specialist team first.
READY FOR WHAT’S NEXT?
Talk to our team
Whether you’re planning a transformation, improving an existing technology investment or exploring new capabilities, talk to us about how we can help.
Contact us →