Topical Authority Map
Run ID: 69c955dfa17964d77e86e17f•2026-03-29SEO
PantheraHive BOS
BOS Dashboard

Build a comprehensive topical authority content map with pillar pages, clusters, and publishing schedule.

Topical Authority Map: AI Workflow Automation

This document outlines a comprehensive topical authority content map for "AI Workflow Automation." The goal is to establish your brand as a leading expert in this domain by creating a robust network of interlinked content, designed to capture diverse search intent and drive organic traffic.

1. Core Topic Definition

Primary Topic: AI Workflow Automation

Description: This topic encompasses the application of Artificial Intelligence (AI) technologies (such as Machine Learning, Natural Language Processing, Computer Vision, and Predictive Analytics) to automate, optimize, and enhance business processes and workflows across various industries. It moves beyond traditional Robotic Process Automation (RPA) by adding intelligence, adaptability, and decision-making capabilities to automated tasks.

2. Pillar Pages Strategy

Pillar pages are comprehensive, long-form content pieces that cover a broad aspect of the core topic. They serve as the central hub for related, more specific content clusters, signaling topical depth and authority to search engines.

Pillar Page 1: The Ultimate Guide to AI Workflow Automation

  • Objective: To provide a foundational, all-encompassing resource on what AI Workflow Automation is, its benefits, underlying technologies, and general applications.
  • Target Audience: Beginners, business leaders exploring AI adoption, decision-makers seeking an overview.
  • Key Sections/Sub-topics:

* What is AI Workflow Automation? (Definition, distinction from RPA)

* Why AI is the Future of Workflow Automation (Key benefits: efficiency, accuracy, scalability, cost reduction)

* Core AI Technologies Powering Automation (ML, NLP, Computer Vision, Predictive Analytics, Generative AI)

* Common Use Cases Across Industries (Finance, Healthcare, HR, Marketing, Manufacturing, Customer Service)

* The Journey to AI Workflow Automation: A Phased Approach

* Challenges and Best Practices for Implementation

* Future Trends in AI-Driven Workflows

Pillar Page 2: AI Workflow Automation Tools & Platforms: A Comprehensive Review

  • Objective: To guide users through the landscape of available AI workflow automation solutions, helping them understand different types of tools and how to choose the right one.
  • Target Audience: IT managers, project leads, technical decision-makers, procurement teams.
  • Key Sections/Sub-topics:

* Categorization of AI Automation Tools (Low-code/No-code, enterprise suites, specialized AI services, custom solutions)

* Deep Dive: Leading AI Workflow Automation Platforms (e.g., Microsoft Power Automate, UiPath AI, Google Cloud AI, AWS AI Services, Zapier AI)

* Key Features to Evaluate in an AI Automation Solution (Integration capabilities, scalability, security, analytics, ease of use)

* Integrating AI into Existing Systems (ERP, CRM, Legacy Systems)

* Open Source vs. Commercial AI Automation Solutions

* Case Studies: Successful Tool Implementations

* Pricing Models and ROI Considerations for Tool Selection

Pillar Page 3: Strategizing & Measuring ROI for AI Workflow Automation

  • Objective: To equip organizations with the knowledge to strategically plan, implement, and measure the success of their AI workflow automation initiatives.
  • Target Audience: C-suite executives, strategy planners, project managers, finance departments.
  • Key Sections/Sub-topics:

* Developing a Robust AI Workflow Automation Strategy (Identifying opportunities, prioritization, pilot programs)

* Defining Clear Objectives and Key Performance Indicators (KPIs) for AI Automation

* Calculating Return on Investment (ROI): Methodologies and Metrics (Time savings, error reduction, cost savings, revenue impact, employee satisfaction)

* Risk Management and Ethical Considerations in AI Automation (Bias, data privacy, compliance)

* Change Management and Workforce Transformation (Upskilling, reskilling, human-in-the-loop)

* Building an AI-Ready Culture and Governance Framework

* Continuous Improvement and Scaling AI Automation Programs

3. Content Clusters (Supporting Articles)

For each pillar page, specific content clusters will be developed. These articles delve deeper into niche aspects, link back to their respective pillar page, and establish granular authority.

Supporting Articles for Pillar Page 1: The Ultimate Guide to AI Workflow Automation

  • 1.1: RPA vs. AI: Understanding the Key Differences and Synergies in Automation
  • 1.2: How Machine Learning Optimizes Predictive Maintenance Workflows
  • 1.3: Leveraging Natural Language Processing (NLP) for Document Classification and Data Extraction
  • 1.4: Computer Vision Applications in Quality Control and Inventory Management Automation
  • 1.5: The Role of Generative AI in Automating Content Creation and Customer Responses
  • 1.6: Overcoming Data Silos: The Foundation for Successful AI Workflow Automation
  • 1.7: Real-World Examples: AI Workflow Automation in Financial Services
  • 1.8: Streamlining Healthcare Operations with AI-Powered Workflow Automation
  • 1.9: Enhancing Customer Experience through AI-Driven Service Automation

Supporting Articles for Pillar Page 2: AI Workflow Automation Tools & Platforms: A Comprehensive Review

  • 2.1: Top 5 Low-Code/No-Code Platforms for Rapid AI Workflow Deployment
  • 2.2: Integrating AI into Existing Enterprise Resource Planning (ERP) Systems
  • 2.3: Choosing the Right AI Workflow Automation Tool for Small to Medium Businesses
  • 2.4: Deep Dive: Features and Use Cases of [Specific Enterprise AI Automation Platform, e.g., Microsoft Power Automate with AI Builder]
  • 2.5: Leveraging Cloud-Based AI Services (AWS, Azure, GCP) for Custom Automation Solutions
  • 2.6: API-First Strategies: Connecting Disparate Systems with AI for Seamless Workflows
  • 2.7: Data Security and Compliance in AI Workflow Automation Platforms
  • 2.8: The Benefits of Hybrid Cloud Architectures for AI Workflow Scalability

Supporting Articles for Pillar Page 3: Strategizing & Measuring ROI for AI Workflow Automation

  • 3.1: Developing a Compelling Business Case for AI Workflow Automation Projects
  • 3.2: Key Performance Indicators (KPIs) to Track for AI Automation Success
  • 3.3: Calculating the Tangible and Intangible ROI of AI in HR Workflows
  • 3.4: Mitigating Algorithmic Bias and Ensuring Ethical AI in Automated Decision-Making
  • 3.5: Upskilling Your Workforce: Training Strategies for the AI Automation Era
  • 3.6: The Future of Work: How AI Automation is Reshaping Job Roles and Organizational Structures
  • 3.7: Implementing a Continuous Improvement Framework for AI Automation Initiatives
  • 3.8: Predictive Analytics for Proactive Workflow Management and Optimization

4. Interlinking Strategy

  • Pillar to Cluster: Each pillar page will prominently link to all its supporting cluster articles.
  • Cluster to Pillar: Every cluster article will contain at least one internal link back to its primary pillar page, typically in the introduction or a "learn more" section.
  • Cluster to Cluster: Relevant cluster articles within the same or even different clusters can link to each other where appropriate, enhancing the user journey and topical depth.
  • Contextual Linking: Links will be embedded naturally within the content, providing additional value and context rather than just a list of links.
  • Anchor Text Optimization: Use descriptive and keyword-rich anchor text for internal links to clearly indicate the linked content's topic.

5. High-Level Publishing Schedule (Phased Approach)

This schedule is designed to build authority systematically, starting with broad foundational content and then drilling down into specifics.

  • Phase 1: Foundation (Month 1)

* Publish Pillar Page 1: The Ultimate Guide to AI Workflow Automation.

* Begin drafting Cluster 1.1, 1.2, 1.3, and outline Pillar Page 2.

Goal:* Establish initial broad authority and capture high-level search queries.

  • Phase 2: Expansion & Depth (Month 2)

* Publish Cluster 1.1, 1.2, 1.3.

* Publish Pillar Page 2: AI Workflow Automation Tools & Platforms: A Comprehensive Review.

* Begin drafting Cluster 1.4, 1.5, 1.6, and Cluster 2.1, 2.2, 2.3, and outline Pillar Page 3.

Goal:* Deepen authority in foundational aspects and introduce the tools landscape.

  • Phase 3: Strategic & Measurement Focus (Month 3)

* Publish Cluster 1.4, 1.5, 1.6.

* Publish Cluster 2.1, 2.2, 2.3.

* Publish Pillar Page 3: Strategizing & Measuring ROI for AI Workflow Automation.

* Begin drafting remaining cluster articles (1.7-1.9, 2.4-2.8, 3.1-3.8).

Goal:* Cover strategic implementation and ROI, completing the core pillar structure.

  • Phase 4: Granular Authority & Maintenance (Month 4 onwards)

* Continue publishing the remaining cluster articles (approximately 4-6 articles per month).

* Regularly review and update existing content for accuracy, freshness, and new developments.

* Actively monitor search performance and identify new content opportunities.

Goal:* Solidify granular authority, maintain content freshness, and capture long-tail search queries.

6. Next Steps

This topical authority map provides a robust framework. The next steps will involve:

  1. Keyword Research Deep Dive: Conduct in-depth keyword research for each pillar and cluster topic to refine titles and content outlines, ensuring alignment with search intent.
  2. Content Outlining: Develop detailed outlines for each pillar page and cluster article, including H2/H3 headings, target keywords, and key talking points.
  3. Content Creation: Begin the writing and editing process for the identified content pieces according to the publishing schedule.
  4. Performance Tracking: Implement analytics to monitor the performance of each content piece, including organic traffic, rankings, engagement metrics, and conversion rates.
gemini Output

This document outlines a comprehensive Topical Authority Map for "AI Workflow Automation," designed to establish your brand as a leading expert in this critical domain. It details the foundational pillar pages, supporting content clusters, a proposed publishing schedule, and strategic considerations for maximizing organic search visibility and audience engagement.

Executive Summary

This Topical Authority Map for "AI Workflow Automation" is strategically designed to capture a significant share of organic search traffic and establish your brand as a definitive resource. By creating a robust network of interlinked, high-quality content, we will cover the topic exhaustively, addressing various user intents from high-level understanding to detailed implementation guides and industry-specific applications.

The map is structured around three core pillar pages, each supported by numerous content clusters. This architecture ensures comprehensive coverage, strong internal linking, and a clear user journey, ultimately boosting SEO performance and demonstrating deep expertise. A phased publishing schedule is provided to guide content creation and deployment.

1. Target Audience & SEO Considerations

1.1 Target Audience

Our primary target audience includes:

  • Business Leaders & Executives (C-suite, VPs): Seeking strategic insights, ROI justification, and high-level understanding of AI workflow automation's impact on business growth and efficiency.
  • IT Decision Makers & Department Heads: Looking for practical implementation strategies, technology comparisons, integration challenges, and best practices.
  • Process Improvement Specialists & Business Analysts: Interested in how AI can optimize specific workflows, methodologies, and measurement.
  • Developers & Technical Teams: Seeking deeper dives into specific tools, APIs, and technical aspects of building and deploying AI-powered workflows.
  • Small & Medium Business (SMB) Owners: Exploring accessible and scalable AI automation solutions to improve operational efficiency.

1.2 SEO Considerations

  • Search Intent Alignment: Each piece of content will be crafted to address specific search intents (informational, commercial investigation, transactional).
  • Keyword Research: Integration of primary, secondary, and long-tail keywords relevant to each topic to capture diverse search queries.
  • Internal Linking: A robust internal linking structure will connect cluster pages to their respective pillar pages and other relevant content, signaling topical authority to search engines and guiding users through related content.
  • Schema Markup: Implementation of relevant schema (e.g., Article, FAQ, HowTo) to enhance visibility in SERPs.
  • Content Quality & Depth: Prioritizing comprehensive, well-researched, and actionable content that provides genuine value to the reader.
  • Mobile Responsiveness & Page Speed: Ensuring all content is optimized for mobile devices and loads quickly.

2. Topical Authority Map: AI Workflow Automation

This map is organized into a primary pillar and two secondary pillars, each with dedicated content clusters.

2.1 Primary Pillar Page: The Definitive Guide to AI Workflow Automation: Transforming Business Operations & Driving Efficiency

This foundational pillar serves as the ultimate resource, covering the breadth and depth of AI Workflow Automation. It will be a comprehensive, long-form guide designed to rank for broad, high-volume keywords.

  • Proposed Word Count: 5,000 - 8,000 words
  • Target Keywords: "AI workflow automation," "intelligent process automation," "AI for business processes," "workflow automation strategy," "AI business transformation," "operational efficiency AI"
  • Content Outline (Key Sections):

1. Introduction: What is AI Workflow Automation? Definition, evolution from traditional automation, core benefits.

2. Why AI Workflow Automation Now? Market trends, competitive advantages, addressing modern business challenges.

3. Key Components & Technologies: Machine Learning, NLP, Computer Vision, RPA, BPM, Integration Platforms.

4. Strategic Planning & Implementation Framework: From identifying opportunities to scaling solutions.

5. Measuring ROI & Business Impact: Key metrics, efficiency gains, cost reduction, enhanced customer experience.

6. Common Use Cases Across Industries: High-level overview (detailed in Secondary Pillar 1).

7. Challenges & Best Practices: Data privacy, ethical AI, change management, overcoming integration hurdles.

8. The Future of AI Workflow Automation: Hyperautomation, Generative AI, human-in-the-loop.

9. Getting Started: A roadmap for organizations.

2.1.1 Content Clusters for Primary Pillar

These articles will delve into specific aspects of the primary pillar, linking back to it as the central hub.

  • Cluster 1: Understanding AI Workflow Automation Fundamentals

* Article 1.1: What's the Difference: AI vs. RPA vs. Traditional Automation?

Description:* Clarifies the distinctions and synergies between various automation technologies.

Target Keywords:* "AI vs RPA," "traditional automation limitations," "intelligent automation explained"

* Article 1.2: The Evolution of Automation: From Rules-Based to Intelligent Processes

Description:* Traces the history of automation and highlights the paradigm shift brought by AI.

Target Keywords:* "history of automation," "intelligent process evolution," "AI in business process management"

* Article 1.3: How AI Enhances Business Process Management (BPM)

Description:* Explores the specific ways AI supercharges BPM, from analysis to execution.

Target Keywords:* "AI BPM," "business process optimization AI," "intelligent BPM"

  • Cluster 2: Strategy & Planning for AI Workflow Automation

* Article 2.1: Developing an AI Workflow Automation Strategy: A Step-by-Step Framework

Description:* Provides a practical guide for building a comprehensive strategy, from vision to roadmap.

Target Keywords:* "AI automation strategy," "workflow automation roadmap," "enterprise AI strategy"

* Article 2.2: Identifying High-Impact Workflows for AI Automation: A Prioritization Guide

Description:* Helps businesses pinpoint which processes are ripe for AI automation for maximum ROI.

Target Keywords:* "identify AI automation opportunities," "workflow prioritization AI," "AI automation assessment"

* Article 2.3: Building a Business Case for AI Workflow Automation: Proving ROI

Description:* Guides stakeholders on how to quantify benefits and secure buy-in for AI initiatives.

Target Keywords:* "AI automation ROI," "business case AI," "justify AI investment"

  • Cluster 3: Implementation & Best Practices

* Article 3.1: Step-by-Step Guide to Implementing AI Workflow Automation

Description:* A practical walkthrough of the deployment process, from pilot to full rollout.

Target Keywords:* "implement AI automation," "AI workflow deployment guide," "AI integration steps"

* Article 3.2: Data Preparation & Management for AI Automation Success

Description:* Focuses on the critical role of data quality, governance, and access for effective AI workflows.

Target Keywords:* "AI data preparation," "data governance AI," "data quality for automation"

* Article 3.3: Change Management & Employee Adoption for AI Automation Initiatives

Description:* Addresses the human element, ensuring smooth transitions and maximizing user acceptance.

Target Keywords:* "AI change management," "employee adoption AI," "human-AI collaboration"

  • Cluster 4: Future Trends & Innovations

* Article 4.1: The Rise of Hyperautomation: Orchestrating AI, RPA, and More

Description:* Explores the convergence of multiple technologies to achieve end-to-end automation.

Target Keywords:* "hyperautomation explained," "future of automation," "orchestrated automation"

* Article 4.2: How Generative AI is Reshaping Workflow Automation

Description:* Details the impact of large language models and generative AI on content creation, customer service, and more.

Target Keywords:* "generative AI automation," "LLM workflow automation," "AI content generation workflow"

* Article 4.3: Ethical AI & Responsible Automation: Navigating Bias, Transparency, and Governance

Description:* Discusses the critical ethical considerations and best practices for building fair and transparent AI workflows.

Target Keywords:* "ethical AI automation," "AI bias in workflows," "responsible AI governance"

2.2 Secondary Pillar Page 1: AI Workflow Automation Use Cases: Industry-Specific Applications & Real-World Examples

This pillar focuses on demonstrating the practical application of AI workflow automation across various industries, providing tangible examples and case studies.

  • Proposed Word Count:
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\n"); zip.file(folder+"src/app/app.component.css",".app-header{display:flex;flex-direction:column;align-items:center;justify-content:center;min-height:60vh;gap:16px}h1{font-size:2.5rem;font-weight:700;color:#6366f1}\n"); } zip.file(folder+"src/app/app.config.ts","import { ApplicationConfig, provideZoneChangeDetection } from '@angular/core';\nimport { provideRouter } from '@angular/router';\nimport { routes } from './app.routes';\n\nexport const appConfig: ApplicationConfig = {\n providers: [\n provideZoneChangeDetection({ eventCoalescing: true }),\n provideRouter(routes)\n ]\n};\n"); zip.file(folder+"src/app/app.routes.ts","import { Routes } from '@angular/router';\n\nexport const routes: Routes = [];\n"); Object.keys(extracted).forEach(function(p){ var fp=p.startsWith("src/")?p:"src/"+p; zip.file(folder+fp,extracted[p]); }); zip.file(folder+"README.md","# "+slugTitle(pn)+"\n\nGenerated by PantheraHive BOS.\n\n## Setup\n\`\`\`bash\nnpm install\nng serve\n# or: npm start\n\`\`\`\n\n## Build\n\`\`\`bash\nng build\n\`\`\`\n\nOpen in VS Code with Angular Language Service extension.\n"); zip.file(folder+".gitignore","node_modules/\ndist/\n.env\n.DS_Store\n*.local\n.angular/\n"); } /* --- Python --- */ function buildPython(zip,folder,app,code){ var title=slugTitle(app); var pn=pkgName(app); var src=code.replace(/^\`\`\`[\w]*\n?/m,"").replace(/\n?\`\`\`$/m,"").trim(); var reqMap={"numpy":"numpy","pandas":"pandas","sklearn":"scikit-learn","tensorflow":"tensorflow","torch":"torch","flask":"flask","fastapi":"fastapi","uvicorn":"uvicorn","requests":"requests","sqlalchemy":"sqlalchemy","pydantic":"pydantic","dotenv":"python-dotenv","PIL":"Pillow","cv2":"opencv-python","matplotlib":"matplotlib","seaborn":"seaborn","scipy":"scipy"}; var reqs=[]; Object.keys(reqMap).forEach(function(k){if(src.indexOf("import "+k)>=0||src.indexOf("from "+k)>=0)reqs.push(reqMap[k]);}); var reqsTxt=reqs.length?reqs.join("\n"):"# add dependencies here\n"; zip.file(folder+"main.py",src||"# "+title+"\n# Generated by PantheraHive BOS\n\nprint(title+\" loaded\")\n"); zip.file(folder+"requirements.txt",reqsTxt); zip.file(folder+".env.example","# Environment variables\n"); zip.file(folder+"README.md","# "+title+"\n\nGenerated by PantheraHive BOS.\n\n## Setup\n\`\`\`bash\npython3 -m venv .venv\nsource .venv/bin/activate\npip install -r requirements.txt\n\`\`\`\n\n## Run\n\`\`\`bash\npython main.py\n\`\`\`\n"); zip.file(folder+".gitignore",".venv/\n__pycache__/\n*.pyc\n.env\n.DS_Store\n"); } /* --- Node.js --- */ function buildNode(zip,folder,app,code){ var title=slugTitle(app); var pn=pkgName(app); var src=code.replace(/^\`\`\`[\w]*\n?/m,"").replace(/\n?\`\`\`$/m,"").trim(); var depMap={"mongoose":"^8.0.0","dotenv":"^16.4.5","axios":"^1.7.9","cors":"^2.8.5","bcryptjs":"^2.4.3","jsonwebtoken":"^9.0.2","socket.io":"^4.7.4","uuid":"^9.0.1","zod":"^3.22.4","express":"^4.18.2"}; var deps={}; Object.keys(depMap).forEach(function(k){if(src.indexOf(k)>=0)deps[k]=depMap[k];}); if(!deps["express"])deps["express"]="^4.18.2"; var pkgJson=JSON.stringify({"name":pn,"version":"1.0.0","main":"src/index.js","scripts":{"start":"node src/index.js","dev":"nodemon src/index.js"},"dependencies":deps,"devDependencies":{"nodemon":"^3.0.3"}},null,2)+"\n"; zip.file(folder+"package.json",pkgJson); var fallback="const express=require(\"express\");\nconst app=express();\napp.use(express.json());\n\napp.get(\"/\",(req,res)=>{\n res.json({message:\""+title+" API\"});\n});\n\nconst PORT=process.env.PORT||3000;\napp.listen(PORT,()=>console.log(\"Server on port \"+PORT));\n"; zip.file(folder+"src/index.js",src||fallback); zip.file(folder+".env.example","PORT=3000\n"); zip.file(folder+".gitignore","node_modules/\n.env\n.DS_Store\n"); zip.file(folder+"README.md","# "+title+"\n\nGenerated by PantheraHive BOS.\n\n## Setup\n\`\`\`bash\nnpm install\n\`\`\`\n\n## Run\n\`\`\`bash\nnpm run dev\n\`\`\`\n"); } /* --- Vanilla HTML --- */ function buildVanillaHtml(zip,folder,app,code){ var title=slugTitle(app); var isFullDoc=code.trim().toLowerCase().indexOf("=0||code.trim().toLowerCase().indexOf("=0; var indexHtml=isFullDoc?code:"\n\n\n\n\n"+title+"\n\n\n\n"+code+"\n\n\n\n"; zip.file(folder+"index.html",indexHtml); zip.file(folder+"style.css","/* "+title+" — styles */\n*{margin:0;padding:0;box-sizing:border-box}\nbody{font-family:system-ui,-apple-system,sans-serif;background:#fff;color:#1a1a2e}\n"); zip.file(folder+"script.js","/* "+title+" — scripts */\n"); zip.file(folder+"assets/.gitkeep",""); zip.file(folder+"README.md","# "+title+"\n\nGenerated by PantheraHive BOS.\n\n## Open\nDouble-click \`index.html\` in your browser.\n\nOr serve locally:\n\`\`\`bash\nnpx serve .\n# or\npython3 -m http.server 3000\n\`\`\`\n"); zip.file(folder+".gitignore",".DS_Store\nnode_modules/\n.env\n"); } /* ===== MAIN ===== */ var sc=document.createElement("script"); sc.src="https://cdnjs.cloudflare.com/ajax/libs/jszip/3.10.1/jszip.min.js"; sc.onerror=function(){ if(lbl)lbl.textContent="Download ZIP"; alert("JSZip load failed — check connection."); }; sc.onload=function(){ var zip=new JSZip(); var base=(_phFname||"output").replace(/\.[^.]+$/,""); var app=base.toLowerCase().replace(/[^a-z0-9]+/g,"_").replace(/^_+|_+$/g,"")||"my_app"; var folder=app+"/"; var vc=document.getElementById("panel-content"); var panelTxt=vc?(vc.innerText||vc.textContent||""):""; var lang=detectLang(_phCode,panelTxt); if(_phIsHtml){ buildVanillaHtml(zip,folder,app,_phCode); } else if(lang==="flutter"){ buildFlutter(zip,folder,app,_phCode,panelTxt); } else if(lang==="react-native"){ buildReactNative(zip,folder,app,_phCode,panelTxt); } else if(lang==="swift"){ buildSwift(zip,folder,app,_phCode,panelTxt); } else if(lang==="kotlin"){ buildKotlin(zip,folder,app,_phCode,panelTxt); } else if(lang==="react"){ buildReact(zip,folder,app,_phCode,panelTxt); } else if(lang==="vue"){ buildVue(zip,folder,app,_phCode,panelTxt); } else if(lang==="angular"){ buildAngular(zip,folder,app,_phCode,panelTxt); } else if(lang==="python"){ buildPython(zip,folder,app,_phCode); } else if(lang==="node"){ buildNode(zip,folder,app,_phCode); } else { /* Document/content workflow */ var title=app.replace(/_/g," "); var md=_phAll||_phCode||panelTxt||"No content"; zip.file(folder+app+".md",md); var h=""+title+""; h+="

"+title+"

"; var hc=md.replace(/&/g,"&").replace(//g,">"); hc=hc.replace(/^### (.+)$/gm,"

$1

"); hc=hc.replace(/^## (.+)$/gm,"

$1

"); hc=hc.replace(/^# (.+)$/gm,"

$1

"); hc=hc.replace(/\*\*(.+?)\*\*/g,"$1"); hc=hc.replace(/\n{2,}/g,"

"); h+="

"+hc+"

Generated by PantheraHive BOS
"; zip.file(folder+app+".html",h); zip.file(folder+"README.md","# "+title+"\n\nGenerated by PantheraHive BOS.\n\nFiles:\n- "+app+".md (Markdown)\n- "+app+".html (styled HTML)\n"); } zip.generateAsync({type:"blob"}).then(function(blob){ var a=document.createElement("a"); a.href=URL.createObjectURL(blob); a.download=app+".zip"; a.click(); URL.revokeObjectURL(a.href); if(lbl)lbl.textContent="Download ZIP"; }); }; document.head.appendChild(sc); } function phShare(){navigator.clipboard.writeText(window.location.href).then(function(){var el=document.getElementById("ph-share-lbl");if(el){el.textContent="Link copied!";setTimeout(function(){el.textContent="Copy share link";},2500);}});}function phEmbed(){var runId=window.location.pathname.split("/").pop().replace(".html","");var embedUrl="https://pantherahive.com/embed/"+runId;var code='';navigator.clipboard.writeText(code).then(function(){var el=document.getElementById("ph-embed-lbl");if(el){el.textContent="Embed code copied!";setTimeout(function(){el.textContent="Get Embed Code";},2500);}});}

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