01 / Hero

From data integration to AI Agent execution —
building your enterprise's own digital workforce.

Helping enterprises:

Automate repetitive workflows to reduce operational costs
Break down data silos so AI understands your full business landscape
Build private AI Agent systems — evolve from assistant to digital employee
Agent RAG RPA MCP Private AI Deployment Enterprise System Integration

Covering core operations, supply chain, management decisions, and more with AI transformation.

Cross-border E-commerce Supply Chain Management ERP System Integration Enterprise Knowledge Base Operational Data Analytics Inventory Risk Control AI Customer Service GEO Traffic Optimization
3000万+ Single Project GMV
5亿+ Business Volume Covered
8 Production Agents
6周 Typical Delivery Timeline
Delivery Standard: Seamless HCI + Industrial-grade Business Flow Closure
From top-level user experience and middle-layer business logic to the underlying automation hub seamlessly integrated with daily office tools. No patchwork, no paying twice for fragmented systems that can't talk to each other.

02 / Why Enterprise AI

AI technology is advancing far faster than enterprises can adopt it.

Many companies already run ERP, CRM, Feishu, and other systems — yet data silos, process fragmentation, and manual repetitive tasks persist. The real challenge isn't calling an AI model; it's embedding AI into the daily business workflows that run your enterprise.

That's why I chose to become an FDE (AI Forward Deployed Engineer) — responsible for the full closed loop from business analysis and architecture design to system development, deployment, and go-live. Making AI a long-term digital asset for your business, not just a demo.

I bring system-level architectural thinking, breaking down complex business problems into clean, structured solutions. In practice, I follow technical pragmatism and results-driven delivery — handling requirements analysis, architecture design, full-stack development, deployment, and go-live as a single point of accountability.

I specialize in cross-system resource integration — building end-to-end business closures from automated data collection and intelligent analysis to proactive alerts. Replacing uncertain business problems with deterministic automation for long-term cost reduction and efficiency gains.

Solo Full-Chain Result-Driven Delivery RPA Fault Tolerance 100% Private Deployment Long-term Maintenance

Workflow Automation

Repetitive manual ops · Data transfer · Multi-system switching

→ Lower Operating Costs

Data Intelligence

Scattered data · Untapped information · No real-time visibility

→ Better Decision-Making

AI Agent Execution

AI can answer but not act · Lacks automation tools

→ From Assistant to Digital Employee

03 / How Enterprise AI Works

Enterprise Data ERP/MES/CRM AI Understanding Data Governance + Ontology Intelligent Judgment Agent Orchestration Automation Execution RPA + Tool Human Review Feishu Card Continuous Improvement Feedback Loop Continuous iteration · Each improvement feeds back into the evaluation set

04 / AI Delivery Methodology

Behind every case study lies the same reusable closed-loop methodology — whether the scenario is ad bidding or inventory clearance, every delivered system follows the same four-stage structure:

FDE AI Forward Deployed Engineer Data collection → Agent decision → Business execution. Anomalies or high-risk cases go through a human review loop to form a closed circuit. 01 · Data CollectionPlaywright +Fingerprint Browser / ERP API 02 · Agent DecisionPrivate Enterprise AI HubSOP-based Decision Making 03 · Business ExecutionPricing / Start-Stop / SettlementWrite Back to Business Systems 04 · Human LoopFeishu Interactive CardOne-click Approval Dashed line: anomalous/high-risk decisions don't auto-execute, returned for human confirmation — forming a closed loop

The collection layer ensures data fidelity. The decision layer applies explainable rules/models. The execution layer writes directly back to existing enterprise systems instead of building new silos. The review loop gives the final say to the business owner — this is the fundamental difference between "full-stack delivery" and "calling a single API."

Complete Layered Architecture (Technical)

Behind every delivery is a complete layered architecture:

① Data Governance Layer
Integrates 8+ business systems (MES/ERP/CRM/PLM/WMS), API/database direct connect/ETL
② Knowledge Layer (RAG)
Structured data via SQL, documents via RAG retrieval, routed by business type
③ Ontology Layer
Entity-relationship modeling giving AI true understanding of your data world, eliminating inconsistent naming across systems
④ Tool / MCP Layer
Business capabilities wrapped as auditable, permission-controlled tools with MCP protocol standardization
⑤ Agent Orchestration Layer
LangGraph-driven stateful workflows designed by business nodes + branches + human intervention points — no black-box reasoning

05 / Enterprise AI Architecture

From data ingestion to Agent orchestration — a complete layered architecture for enterprise AI deployment.

Enterprise AI Complete Architecture Seven-layer architecture: Data Sources → Data Governance → Tool/MCP Layer → Knowledge Layer → Governance Layer → Agent Orchestration → User Interfaces Enterprise AI Complete Architecture Agent Orchestration LayerMulti-Agent Orchestration · Task Routing · State Management Tool / MCP LayerTool Registration · MCP Protocol · API Gateway Knowledge Layer (RAG · Vector DB · Knowledge Graph) Tool / APIERP · CRM · Feishu · E-commerce Platforms Knowledge BaseRAG · Vector DB · Business Documents External DataScraping · Third-party APIs · Competitor Monitoring Data Governance Layer (Cleansing · Standardization · Update Strategy) Data Source LayerERP · CRM · E-commerce Backend · Logs · Files · Databases User InterfaceWeb Dashboard · Feishu Interactive Cards · Telegram Bot

The architecture spans seven layers from data ingestion to user interface — covering the full pipeline from data to decision.

06 / Case Studies

Real project deliveries from cross-border e-commerce and brand sellers.

Real-time Competitor Price Monitoring
Outdoor Gear · GMV ~50M
Amazon AdsPower Feishu 2 周
Business Pain Point

Competitors would adjust prices aggressively at midnight without detection. Operations spent hours on manual price checks, and missing a pricing window meant real profit loss.

AI Solution

Fingerprint browser + Playwright captured real front-end prices, ±5% filter eliminated noise, Feishu cards pushed in real-time.

Tech Highlights: Playwright RPA + AdsPower Fingerprint Browser + Feishu Card Push

<5min Anomaly Response Latency
↓95% Manual Monitoring Reduced
Alerts only on anomalies instead of checking every price daily — this design eliminated so much noise.
Inventory & Logistics Risk Control
Home Furnishings · GMV ~80M
Feishu OpenClaw Winit 4 周
Business Pain Point

Long-cycle inventory holding and logistics delays were only discovered at month-end settlement. Warehousing, logistics, and operations data was scattered — anomalies drowned in a sea of data.

AI Solution

Auto-calculated delay days, TOP 5 high-risk orders pushed @ relevant person, 3/6-month dual-threshold inventory age alerts + weekly inventory value report.

Tech Highlights: OpenClaw Agent + Feishu @mention Push + Multi-source Data Fusion

TOP 5 Auto-Identified High Risk Orders
3/6mo Dual-Threshold Inventory Age Alerts
It covers weekly-level data like inventory age and value, not just short-term sales — long-term inventory health is well taken care of.
ERP Automation Emergency Monitoring
3C Digital · GMV ~200M
Playwright ERP Feishu 24h Emergency
Business Pain Point

The Jijia ERP official API authentication gateway failed, taking down the entire negative review monitoring system — third-party outages are a common reality in automation projects.

AI Solution

Instead of waiting for the official fix, switched the scraping layer to Playwright RPA within 24 hours — simulated login to scrape from the front end with zero changes to upstream logic.

Tech Highlights: Playwright RPA + Emergency Switch Mechanism + Feishu Notification Loop

<24h API Outage → RPA Switch
0 天 Business Monitoring Downtime
No waiting for the vendor fix — switched the scraping layer to RPA with zero changes to upstream logic. Business barely noticed. APIs go down, but business doesn't stop.
OpenClaw Private Automation Hub
Multi-category · GMV ~500M
OpenClaw Private Deployment Feishu 6 周
Business Pain Point

Core operational data flowing through public cloud posed trade secret leakage risks. Multiple isolated systems with no unified data view for management.

AI Solution

Full-stack OpenClaw private deployment, 7 types of daily/weekly reports pushed to Feishu, 100% physical isolation of core data.

Tech Highlights: OpenClaw Private Deployment + Feishu Integration + Multi-Agent Collaboration

100% Core Data Physically Isolated
↓80% Manual Repetitive Work Reduced
Opening Feishu every morning shows all operations — no more logging into 4-5 platforms. Zero learning curve, high team adoption.
View All Case Studies →

07 / Services

Flexible options based on enterprise needs. Each service includes deployment support and long-term maintenance.

AI Workflow Automation

Single Process Optimization
Timeline 2 - 4 周 Investment $3K - $7K

Ideal for enterprises needing fast resolution of specific pain points like daily report automation, competitor monitoring, or inventory alerts.

Enterprise Agent System

Multi-system Integration + Multi-Agent Collaboration
Timeline 4 - 8 周 Investment $15K - $45K

For enterprises needing to connect multiple business systems and build an enterprise-grade AI Agent ecosystem.

Private AI Deployment

Open-source Model On-premise + Customization
Timeline 2 - 6 周 Investment $7K - $30K

For organizations with high data security requirements needing on-premise LLM and knowledge base deployment.

08 / Workflow

From diagnosis to go-live, every step has clear deliverables.

01 Business Diagnosis 02 AI Opportunity Analysis 03 Solution Design 04 Development & Delivery 05 Continuous Optimization

09 / Core Technology

A systematic tech stack supporting industrial-grade delivery — not just theory, but proven in production.

LLM Engineering Integration

Integrated OpenAI / Claude / DeepSeek and 8+ mainstream model APIs. On-premise deployment experience with Ollama / vLLM.

Agent Workflow Design

Business capability modules wrapped around a private enterprise AI hub. Delivered 8 production-grade Agents for competitor monitoring, operations analysis, inventory health, and more.

RPA + Enterprise System Integration

Playwright browser automation + AdsPower / Purple Bird to penetrate API-less systems. Connected Feishu multi-dimensional tables, Interactive Cards, Kingdee ERP, and Shopify.

RAG Full-stack Knowledge Base

Document parsing → Chunking → Embedding → Vector search → Hybrid retrieval → Reranking → Knowledge-augmented generation — complete end-to-end production experience.

Business Ontology Modeling

Entity, attribute, relationship, and business rule models designed around real scenarios. With ontology, Agents understand the full chain of "customer→order→product→process→equipment" — traceable and explainable reasoning.

Full-stack Engineering Delivery

Next.js / Python Flask frontend and backend. From requirements research to documentation, single point of accountability — no cross-team communication overhead.

10 / FAQ

Do you support private deployment?

Yes. Can be deployed on enterprise servers, cloud servers, or local network environments. Business data never passes through third-party platforms.

Do I need to replace our ERP?

No. Priority is given to integrating with existing ERP, Feishu, WeCom, and other systems to minimize business transformation costs.

How long is the delivery cycle?

Typically 2 to 8 weeks depending on project complexity. A phased delivery plan is provided after requirements are confirmed.

Do you sign an NDA?

Yes. NDA can be signed for projects involving business data or processes.

Do you provide post-delivery support?

Yes. Deployment support, bug fixes, and agreed maintenance services are provided. Long-term technical support is available based on project needs.

How is pricing structured?

Pricing is based on requirement complexity, system scale, and delivery scope. You can schedule a free consultation to get a business AI application assessment report.

11 / Contact

Turn AI from a demo
into a long-term digital asset for your enterprise

Free 15-minute scenario feasibility assessment · Evaluate integration complexity and Agent roadmap
No hype, just solutions. First call evaluates whether AI transformation is right for you — no hard sell.

Free Enterprise AI Automation Opportunity Analysis

Or reach out directly: Telegram @GeekHeron