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FORWARD DEPLOYED ENGINEERING

From workflow
to production.

Forward Deployed Engineers work beside operators, product teams and IT leaders until AI becomes part of the business.

02 — HOW WE WORK

We do not ship one AI project. We keep raising how much work AI carries.

01

Discover

Work beside the team. We do not ask what AI they want; we observe repeated work and repeated decisions.

02

Diagnose

Break down workflow, people, data, systems, permissions and ROI, then rank the opportunities.

03

Prototype

Deliver a working prototype in 7–14 days, running on the client’s own data.

04

Deploy

Connect ERP, CRM, databases, knowledge, APIs and collaboration tools, then enter the real production environment.

05

Iterate

Usage → feedback → evaluation → agent improvement → a wider automation scope.

03 — WHY FDE

Not consulting.
Not outsourcing.
Not just SaaS.

An FDE combines the roles of product manager, AI engineer, solution architect and business operator. One team owns business understanding, product judgment, engineering, integration and long-term iteration.

ConsultingSaaSAI outsourcingPucheng FDE
Business understandingStrongWeakWeakStrong
EngineeringWeakStrongMediumStrong
CustomisationDocumentsConfigurationPer projectPer workflow
Systems integration—Standard APIsPer contractEnd to end
Production deployment—Self-serviceEnds at deliveryWe own it
Continuous iterationProject endsVersion updatesNew quoteEmbedded
Owns the business outcomeNoNoNoYes
04 — PRODUCTION READINESS

Show the working system, not a slide deck.

AI Sales Agent

WORKING EXAMPLE
“Quote 800 stainless-steel fittings for delivery within 30 days.”
  1. Read the request and identify the account
  2. Match SKUs and approved substitutes
  3. Check inventory and lead time
  4. Retrieve pricing history and discount bands
  5. Generate the quote and sales email
Output: quote PDF + send-ready email · 3 minutes

AI Data Analyst

WORKING EXAMPLE
“Why did East China sales fall this month?”
  1. Interpret the question and decompose metrics
  2. Locate tables and generate SQL
  3. Compare YoY, MoM and channel structure
  4. Generate charts and isolate the main driver
  5. Recommend the next actions
Output: conclusion + charts + 3 executable actions
05 — TECHNOLOGY

Model agnostic. Business first.

Models

  • OpenAI
  • Claude
  • Gemini
  • Llama
  • Qwen
  • DeepSeek

AI infrastructure

  • Agents
  • RAG
  • MCP
  • Fine-tuning
  • Evals
  • Observability

Enterprise integration

  • SAP
  • Salesforce
  • Oracle
  • Microsoft
  • Slack
  • WeCom · Lark · DingTalk

Security

  • SSO
  • RBAC
  • Audit logs
  • Data isolation
  • Private deployment

We choose models, infrastructure and deployment around the business problem—not the other way around.

Start with one high-value workflow.

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FDE Methodology · Pucheng