Upskill and certify your team in Applied AI
The capability gap
Production AI needs more than AI knowledge
The models are available. The harder part is finding people who can make them work against real data, systems, workflows and business constraints.
That requires engineers who already understand how to ship production software and can add the Applied AI layer on top: agents, retrieval, evaluation, observability, LLMOps and production deployment. It also requires people who can work through an ambiguous business problem, identify where AI can create value and scope the smallest credible system capable of delivering it.
Rather than competing for a limited pool of ready-made Applied AI Engineers and FDEs, we can build them.
How it works
01
Hire
02
Train
03
Deploy
04
Develop
05
Convert
Every participant arrives with an established engineering foundation. The training adds the Applied AI and delivery disciplines needed to operate effectively in live enterprise environments.
What they are trained to do
- GenAI and agentic engineering
- Retrieval and tool use
- Evaluation and observability
- AI safety and governance
- Production deployment and LLMOps
- Customer discovery and technical scoping
- Commercial thinking and business value
Built around real delivery
Training shaped by what production actually demands
FDECo’s role is to ensure the capability being developed reflects the realities of Applied AI delivery.
That means training around the problems engineers face once AI leaves the demo environment: enterprise integration, evaluation, governance, observability, cost, stakeholder alignment and handover.
This specialist training and talent infrastructure allows us to combine real-world delivery expertise with structured technical development.