FORWARD DEPLOYED ENGINEER

Industry AI Adoption
Rebuild business workflows with AI agents

The real starting point of AI adoption is not the model — it's a scenario that closes the loop.
With the FDE model we work inside your business: consulting, building, training — accountable end to end.

THE GAP

AI is hot. Adoption is hard.

Three numbers from enterprise AI surveys tell the truth.

58.2%
of enterprises cite weak data foundations
as the top barrier to AI adoption
49.8%
lack hybrid talent who understand
both business and AI
43.2%
find AI returns hard to quantify

The problem is not model capability — it's the absence of a scenario where AI actually runs, produces results, and accumulates experience.
That is exactly what FDE solves.

HOW WE WORK

The FDE three-stage engagement

01

Consult · Identify

Work inside your front line, map workflows, and find rule-clear, closable, ROI-measurable AI scenarios. Deliver an adoption plan and roadmap.

02

Build · Deploy Agents

Custom AI agents with supporting workflows: Skill rules, proprietary knowledge bases, and business system integration — running in real scenarios.

03

Train · Transfer

Teach your team to use, tune and manage the agents — keeping capability inside your organization for long-term self-operation.

WHY US

Why Infocloud

We run what we teach

Lingyun AI Operations is our own AI adoption practice: agents, Skills, knowledge bases and human-AI collaboration — a methodology proven in production.

15 years of enterprise service

From data center construction to managed operations, we understand real enterprise constraints: budget, compliance, security, staffing. Our plans stay grounded.

Clear data boundaries

Skills and knowledge bases deploy locally — data never leaves your facility. LLMs can run fully private, safe even for sensitive industries.

You own the assets

At contract end, all Skill rules, knowledge bases and history are handed over. Your experience becomes your asset — no vendor lock-in.

THE PATH

The right way to adopt AI

Start Small One closed loop Measure Results Efficiency · Cost · Quality Build Assets Skills · Knowledge Scale Up More scenarios

Don't boil the ocean. Prove value with one closed-loop scenario, then replicate the pattern across your business.

Which part of your business
should adopt AI first?

Let's map it together — thirty minutes is enough.