Global-Ready System Development for EC–ERP Integration with AI & Workflow

Why Enterprises Worldwide Need Reliable Automation Now

Across global enterprises, e-commerce platforms, ERP systems, internal tools, and legacy applications have evolved independently over many years. The result is a complex operational landscape where:

APIs exist but are limited, unstable, or inconsistent
File-based integration (CSV, batch jobs, SFTP) is still mission-critical
Business changes require costly, risky system modifications

As a result, many organizations say:

“We want automation, but failures are unacceptable.”
“AI is promising, but we can’t let it directly control business operations.”

We address these challenges with a clear separation of AI intelligence, workflow responsibility, and execution, designed for real-world enterprise operations.

Our Core Philosophy: AI Decides, Workflows Take Responsibility

Many AI chatbot solutions attempt to:

understand requests
execute actions
recover from failures

all at once.

This approach is risky for enterprise systems.

Our Design Principle

Responsibility	Component	Why It Matters
Understanding & judgment	AI / LLM	Flexible, language-aware decision making
State, retries, approvals	Workflow engine	Deterministic, auditable, failure-resistant
Execution	Business systems / RPA	Precise, repeatable, controlled

This separation enables automation that is explainable, auditable, and safe—critical for enterprises operating across regions and regulatory environments.

Reference Architecture (EC × ERP × AI)

E-commerce platforms (orders, customers, payments)
ERP systems (inventory, invoicing, procurement)
AI layer (intent understanding, structured extraction)
Workflow orchestration (state, approval, retry, compensation)

All components are loosely coupled for long-term maintainability.

System Architecture Overview

flowchart LR
  U["Customer / Internal User"] --> UI["Chat UI / Web / Mobile / Messaging"]
  UI --> AG["Agent API"]

  AG --> LLM["AI / LLM\n(Intent & Data Extraction)"]
  AG --> WF["Workflow Engine\n(Temporal)"]

  WF --> ECW["E-commerce Worker"]
  WF --> ERPW["ERP Worker"]

  ERPW -. "When no API is available" .-> RPA["Robot Framework\n(UI Automation)"]

  ECW --> EC["E-commerce System"]
  ERPW --> ERP["ERP / Core Systems"]
  RPA --> ERPUI["Legacy ERP UI"]

  WF --> LOG["Audit Logs & Execution History"]

Key points

AI never directly mutates business data
All state, retries, and approvals are managed by workflows
Even legacy UI automation is fully auditable and controlled

Recommended Software Stack (Example)

Below is a representative stack we frequently adopt. Each layer can be adapted to on‑premise, cloud, or hybrid environments.

1) AI & Interaction Layer

LLM: Local LLMs (e.g., Ollama) or cloud LLMs, depending on data policy
RAG / Knowledge Search: pgvector, OpenSearch, Qdrant
Tool & prompt control: Strict application-side enforcement (AI cannot write to DBs directly)

2) Workflow Orchestration

Workflow Engine: Temporal
Workers / Activities: EC integration, ERP integration, notifications, approvals

3) Application & APIs

Backend: Django or FastAPI
Authentication: SSO (OIDC / SAML), enterprise IAM, step-up authentication (OTP)
Notifications: Email, Slack, LINE, SMS (depending on region)