Embedded AI Engineering
Forward Deployed AI Engineers (FDE)
The Forward Deployed Engineer (FDE) model, popularized by companies like Palantir, puts AI engineers to work directly inside your organization — not remotely or from behind a support ticket. A Web Systems FDE embeds with your team, understands your real infrastructure, and deploys AI solutions directly into production, iterating based on real feedback from your operation, not from a lab environment.
Why Choose This Solution
Direct integration with your team
The FDE works side by side with your technical and business teams, not as an isolated external vendor.
Deployment on your real infrastructure
Solutions are built and tested directly on your production systems, not in a separate demo environment.
Fast iteration based on real feedback
Short test-and-adjust cycles on the concrete business problem, not on theoretical specifications.
Focus on the problem, not the technology
The goal is to solve your specific use case, choosing the AI technology that fits best — not imposing a generic solution.
Knowledge transfer
By the end of the engagement, your internal team is equipped to maintain and extend what was deployed.
Frequently Asked Questions
What is a Forward Deployed Engineer (FDE)?
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It's an engineer who works embedded within your organization (on-site or full-time remote during the engagement) instead of delivering a closed product from the outside. Popularized by companies like Palantir, the model prioritizes solving real problems over delivering generic software.
How is this different from hiring a freelance developer?
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An FDE doesn't just write code: they embed in your business process, understand the real constraints of your infrastructure, and prioritize production deployment over documentation or the fixed scope typical of a traditional freelancer.
How long does an FDE engagement last?
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It varies by case, but typically between 2 and 6 months, with the option to extend if scope grows or to transition into an ongoing support model.
Does the FDE work at my offices or remotely?
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Both arrangements are possible. For integrations that require access to critical systems or intensive collaboration, we recommend at least the first few weeks be on-site or with significant overlapping availability.
What kinds of problems does an FDE typically solve?
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Cases where a generic AI solution isn't enough: automation of complex processes specific to your industry, agents that operate on proprietary internal systems, or data pipelines unique to your operation.
Do I need to already have an internal AI team?
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Not necessarily. The FDE can operate autonomously, but the greatest value comes from collaborating with your existing technical team, to whom knowledge is transferred throughout the process.
How is the success of an FDE engagement measured?
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We define concrete business metrics at the start (time saved, accuracy of a process, revenue influenced) and not just technical deliverables — success is measured in real impact, not lines of code.
What happens to the code and systems once the engagement ends?
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All code, models, and documentation remain your property. There's no mandatory ongoing dependency on Web Systems to operate what was deployed.
What's the difference between FDE and the Applied AI Engineer service?
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The FDE focuses on intensive, embedded engagements with broad scope within your organization. The Applied AI Engineer is a more focused service, centered on applying a specific AI model or use case to your business. See Applied AI Engineer.
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