Add Pro Demo Links to Documentation

README.md

@@ -61,11 +61,13 @@ You can explore the strategic reasoning flow directly online:
 
 👉 [Explore Omen on Streamlit Cloud](https://omen-demo.streamlit.app/)
 
+👉 [Explore Omen Pro on Streamlit Cloud](https://omen-pro.streamlit.app/)
+
 ---
 
 ## 🚀 Quick Start
 
-If you are:
+If you are a:
 
 - Data Scientist
 - AI Researcher
@@ -85,7 +87,7 @@ pip install --upgrade pip setuptools wheel
 pip install -e .
 ```
 
-### 🌰 View Demo
+### 🌰 Run Demo
 
 If you want to quickly see Omen in action, a visualized sample case and its results are available in the `demo` directory. Run:
 
@@ -95,17 +97,29 @@ streamlit run demo/app/scenario_planning.py
 
 Then open `http://localhost:8501` in your browser to explore the full strategic reasoning flow.
 
-### 🎵 Run Built-in Case
+#### End-to-End Flow
+
+![End-to-End Flow](docs/assets/images/streamlit-strategic-reason-flow.png)
+
+#### More details
+
+You can click on each panel on the page to inspect the full chain of outputs from source document to situation artifact, scenario artifact, simulation result, and explanation artifact.
+
+![Scenario Planning](docs/assets/images/streamlit-scenario-planning.png)
+
+---
+
+## 🎵 Run Built-in Case
 
 If you want to run a complete **Analyze - Simulate - Explain** workflow, we have prepared a built-in case simulating SAP's acquisition of Reltio in March 2026. 
 
 The case document is `cases/situations/sap_reltio_acquisition.md`, and it can be run end-to-end with the following commands:
 
-#### Step 1. Analyze
+### Step 1. Analyze
 
 Omen's Analyze module combines strategy methodology and the data pipeline, allowing you to generate strategic insights and machine input artifacts from the source document with a single command.
 
-##### Situation Analysis
+#### Situation Analysis
 
 ```bash
 # analyze the built-in case and pack it as "sap" alias
@@ -114,7 +128,7 @@ omen analyze situation --doc sap_reltio_acquisition --pack-id sap
 
 This step generates the Situation Artifact and creates a package named `sap` for consistent use in subsequent steps.
 
-##### Scenario Planning
+#### Scenario Planning
 
 Omen `v0.1.9` provides deterministic A/B/C scenario planning capabilities.
 
@@ -130,7 +144,7 @@ omen scenario --situation sap
 
 This step generates the scenario pack artifact under `data/scenarios/sap/` for simulation.
 
-#### Step 2. Simulate
+### Step 2. Simulate
 
 Omen's simulation engine can reason across different scenarios. Use the scenario pack generated in the previous step to run simulation:
 
@@ -140,7 +154,7 @@ omen simulate --scenario data/scenarios/sap/scenario_pack.json
 
 This step generates reasoning traces and writes the deterministic result to `output/sap/result.json`.
 
-#### Step 3. Explain
+### Step 3. Explain
 
 Omen's explanation module interprets simulation outcomes and traces back key decision points and risk items (known unknowns) from the situation artifact to generate decision-ready insights and recommendations:
 
@@ -152,41 +166,32 @@ This step generates a structured explanation artifact at `output/sap/explanation
 
 ### Launch UI
 
-Omen also provides a Streamlit-based UI application for visualizing the full strategic reasoning flow.
+Run the Streamlit application for visualizing the full strategic reasoning flow.
 
 ```bash
 streamlit run app/scenario_planning.py
 ```
 
-#### End-to-End Flow
-
-![End-to-End Flow](docs/assets/images/streamlit-strategic-reason-flow.png)
-
-#### More details
-
-You can click on each panel on the page to inspect the full chain of outputs from source document to situation artifact, scenario artifact, simulation result, and explanation artifact.
-
-![Scenario Planning](docs/assets/images/streamlit-scenario-planning.png)
-
-## 👥 Target Audience
-
-Omen is built for the following roles:
-*   Technology Strategy Teams
-*   Product & Platform Leads
-*   AI Infrastructure Researchers
-*   Open Source Ecosystem Observers
-*   Investors & Industry Analysts
+Then open `http://localhost:8501` in your browser to explore the results.
 
 ## 🎬 Showcase
 
 ### Strategic Actor Analyze
 
+We have built-in samples of five strategic actors:
+
 *  👤 [Elon Musk](cases/actors/elon-musk.md)
 *  👤 [Jeff Bezos](cases/actors/jeff-bezos.md)
 *  👤 [Steve Jobs](cases/actors/steve-jobs.md)
 *  👤 [Jack Ma](cases/actors/jack-ma.md)
 *  👤 [Chen Jiaxing (me)](cases/actors/chen-jiaxing.md)
 
+Run the following command to build strategic actors and gain insights into their profiles, behavior patterns, and influence relationship graphs:
+
+```bash
+streamlit run app/strategic_actor.py
+```
+
 ### Strategic Reasoning Cases
 
 *  🧩 [Acquisition: SAP vs Reltio](cases/situations/sap_reltio_acquisition.md)

README.zh.md

@@ -59,11 +59,13 @@ Omen **不预测**单一未来，它是**为复杂性而生**的推演引擎。
 
 希望快速体验 Omen 而勿须本地安装，请访问我们部署在 Streamlit Cloud 的演示应用。点击下面的链接，直接探索战略推演流程：
 
-👉 [在线体验 Omen](https://omen-demo.streamlit.app)
+👉 [开源版本 omen-demo.streamlit.app](https://omen-demo.streamlit.app)
+
+👉 [商业版本 omen-pro.streamlit.app](https://omen-pro.streamlit.app)
 
 ---
 
-## 🚀 快速上手
+## 🚀 快速开始
 
 如果你是：
 
@@ -85,7 +87,7 @@ pip install --upgrade pip setuptools wheel
 pip install -e .
 ```
 
-### 🌰 看例子
+### 🌰 演示
 
 如果你希望快速查看 Omen 的运行效果，`demo` 目录中提供了可视化案例及其结果。运行：
 
@@ -95,25 +97,37 @@ streamlit run demo/app/scenario_planning.py
 
 在浏览器中打开 `http://localhost:8501`，即可查看完整的战略推演流程。
 
-### 🎵 跑流程
+**战略推演全流程视图**
+
+![全流程视图](docs/assets/images/streamlit-strategic-reason-flow.png)
+
+#### 更多细节
+
+你可以点击页面上各个面板，查看从源文档到情势工件、情景工件、推演结果，再到解释工件的完整链路产出。
+
+![Scenario Planning](docs/assets/images/streamlit-scenario-planning.png)
+
+---
+
+## 🎵 开始运行
 
 如果你希望亲自跑一遍完整的**分析——模拟——解释**流程，请使用我们准备的内置案例，用于模拟 2026 年 3 月 SAP 收购 Reltio 的情境。
 
 案例文档位于 `cases/situations/sap_reltio_acquisition.md`，可以通过以下步骤端到端运行。
 
-#### 第一步：分析
+### 第一步：分析
 
 Omen 分析模块融合战略方法与数据工程管道，你仅需一行命令，即可从源文档中自动生成战略洞察与机器可消费的工件。
 
-##### 情势分析
+#### 情势分析
 ```bash
 # 分析内置案例，并打包为 "sap" 别名
 omen analyze situation --doc sap_reltio_acquisition --pack-id sap
 ```
 
 此步骤会生成情势工件（Situation Artifact），并创建别名为 `sap` 的包，供后续步骤一致使用。
 
-##### 情景规划
+#### 情景规划
 
 Omen 当前版本提供了确定性的 A/B/C 情景规划能力：
 
@@ -129,7 +143,7 @@ omen scenario --situation sap
 
 此步骤会在 `data/scenarios/sap/` 下生成用于模拟的情景包工件（Scenario Pack Artifact）。
 
-#### 第二步：模拟
+### 第二步：模拟
 
 Omen 提供的模拟引擎可针对不同的情景进行推演。下面使用上一步生成的情景包工件，运行模拟：
 
@@ -139,7 +153,7 @@ omen simulate --scenario data/scenarios/sap/scenario_pack.json
 
 此步骤将生成推演轨迹以及结果文件 `output/sap/result.json`。
 
-#### 第三步：解释
+### 第三步：解释
 
 Omen 解释模块会对模拟结果进行解读，并回溯情势工件中的关键决策点、风险项（已知的未知），生成面向决策者的洞察与建议：
 
@@ -151,40 +165,32 @@ omen explain --pack-id sap
 
 ### 启动 UI 应用
 
-Omen 还提供了一个基于 Streamlit 的 UI 应用，用于可视化完整的战略推演流程。
+Omen 提供了基于 Streamlit 的应用，用于可视化完整的战略推演流程。
 
 ```bash
 streamlit run app/scenario_planning.py
 ```
-**战略推演全流程视图**
 
-![全流程视图](docs/assets/images/streamlit-strategic-reason-flow.png)
-
-#### 更多细节
-
-你可以点击页面上各个面板，查看从源文档到情势工件、情景工件、推演结果，再到解释工件的完整链路产出。
-
-![Scenario Planning](docs/assets/images/streamlit-scenario-planning.png)
-
-## 👥 适用人群
-
-Omen 专为以下角色打造：
-*   技术战略团队
-*   产品与平台负责人
-*   AI 基础设施研究者
-*   开源生态观察者
-*   投资与行业分析师
+然后在浏览器中打开 `http://localhost:8501`，即可探索结果。
 
 ## 🎬 案例展示
 
 ### 战略主体分析
 
+我们内置了五位战略主体的样本：
+
 *  👤 [Elon Musk](cases/actors/elon-musk.md)
 *  👤 [Jeff Bezos](cases/actors/jeff-bezos.md)
 *  👤 [Steve Jobs](cases/actors/steve-jobs.md)
 *  👤 [Jack Ma](cases/actors/jack-ma.md)
 *  👤 [Chen Jiaxing (me)](cases/actors/chen-jiaxing.md)
 
+运行以下命令，构建战略主体并洞察其画像、行为模式及影响关系图谱：
+
+```bash
+streamlit run app/strategic_actor.py
+```
+
 ### 战略推演案例
 
 *   🧩 [SAP 收购 Reltio：主数据迷雾](cases/situations/sap_reltio_acquisition.md)