Forward Deployed Engineering
Make AI Actually Work
PowerOn FDE provides Forward Deployed Engineers (FDEs): AI engineers who embed in your business, work side by side with your frontline teams, and turn AI from a demo into a production system that runs every day — in weeks, not quarters.
Why FDEs for AI Implementation
Most enterprise AI projects never make it past the demo. We believe the key to AI implementation is not a bigger model — it is engineers who sit closer to the business.
On-site Delivery
Engineers work inside your workflows to understand the real problem, instead of guessing from a requirements document.
Fast Iteration
A usable release every week. Ship, learn, and validate every change with data.
Secure & Compliant
Private deployment and in-region data residency to meet enterprise compliance and audit requirements.
Capability Transfer
When the engagement ends, your team can run and extend the system on its own — no vendor lock-in.
AI Implementation Guide: What Can an FDE Do for Your Business?
In five minutes: the 4 things FDEs do, the 4 things they cannot do, how a project runs, and a 5-point checklist to see whether you are ready.
Products & Services
Platform capabilities plus on-site engineering, covering the full AI implementation lifecycle.
FDE Agent Platform
Enterprise agent orchestration and runtime
Visually orchestrate multi-agent workflows with built-in tool calling, knowledge retrieval and human approval steps — one platform for every AI application in your company.
FDE Knowledge Hub
Instant answers from company knowledge
Connect documents, tickets, databases and internal wikis. Permission-aware search and Q&A with every answer traceable to its source.
FDE Evaluation Center
Measure every AI improvement with data
Build evaluation sets automatically, compare model and prompt versions, catch regressions before release and monitor quality after.
On-site Engineering
Engineering squads deployed on demand
A squad of senior AI engineers embeds with your team and owns the outcome — from problem definition to production and operations.
The FDE Method: From Idea to Production
A clear cadence with a deliverable you can sign off at every stage.
Discovery
Map your workflows within a week and pinpoint where AI delivers the highest ROI.
Prototype
Run a working prototype on real data within two weeks and agree on success metrics.
Production
Integrate with your existing systems and set up permissions, monitoring and evaluation.
Operate
Track live metrics, keep improving, and train your team to take over.
AI Implementation Case Studies
Focused on e-commerce, retail and manufacturing — from GEO, SEO and AI customer service to equipment maintenance, AI quality inspection and procurement.
Chinese Beauty Brand · Generative Engine Optimization (GEO)
Getting the brand recommended in AI assistants such as DeepSeek, Doubao, Kimi and ChatGPT — brand mention rate on core category questions rose from 8% to 46%.
Retail Chain · Omnichannel AI Customer Service
Covering pre-sales questions, order tracking and after-sales — 70% of conversations are resolved end-to-end by AI, absorbing 10x volume during peak sales.
Auto Parts Plant · Equipment Troubleshooting Assistant
Twenty years of maintenance records and equipment manuals in one assistant — frontline workers snap a photo to get a fix, and average downtime fell 40%.
What is an FDE?
+
FDE stands for Forward Deployed Engineer. An FDE works directly inside the customer’s business — understanding the problem, writing the code, integrating systems and running the solution in production. It is the engineering role that turns AI technology into real business results.
How is an FDE different from outsourcing or consulting?
+
Consultancies deliver strategies and reports; outsourcing teams build to a requirements document. FDEs embed with your business team, find the problems themselves, write the code themselves and own the production outcome, iterating weekly and delivering systems that actually run.
How is an FDE different from a regular software engineer?
+
A typical software engineer builds against internal product requirements. An FDE serves a specific customer: on top of strong engineering skills, they bring business understanding, communication and fast decision-making, and can ship independently within the customer’s real data and system constraints.
How long does an FDE engagement take?
+
A typical PowerOn FDE engagement: on-site discovery in week 1, a prototype validated on real data in weeks 2–3, integration and launch in weeks 4–6, then ongoing operations. Average time to production is about 6 weeks.
Which companies are a good fit for the FDE model?
+
Companies with a clear business use case whose AI projects are stuck at the demo stage — for example GEO and SEO content operations, AI customer service and trend-driven product selection in e-commerce and retail, or equipment maintenance, AI quality inspection, process knowledge, procurement and safety in manufacturing: long processes, lots of documents, complex rules.
What is GEO, and how is it different from SEO?
+
GEO (Generative Engine Optimization) makes sure your brand and products are accurately mentioned and recommended in the answers of AI assistants such as ChatGPT, DeepSeek, Doubao and Kimi. SEO improves your ranking in search engines such as Google and Baidu. They work together: SEO gets you found, GEO gets you recommended by AI. PowerOn FDE delivers both for e-commerce and retail brands.
How do you keep our data secure?
+
We support private deployment and in-region data residency — running inside your intranet or a dedicated cloud — with access control, audit logs and human review steps to meet enterprise security and compliance requirements.
Ready to put AI to work in your business?
Tell us what you need. An engineer will get back to you within one business day with a free feasibility assessment.
Book a Free Consultation →