Craft
  • Craft AI Whitepaper Overview
  • 1. Executive Summary
    • 1.1 Overview
    • 1.2 Mission & Vision
    • 1.3 Key Problems Craft Solves
    • 1.4 Highlight of Features and Capabilities
    • 1.5 Target Users & Industries
    • 1.6 Strategic Roadmap
  • 2. Introduction
    • 2.1 The AI Revolution in Content Creation
  • 2.2 Market Fragmentation and Tool Overload
  • 2.3 The Need for a Unified, Intelligent Platform
  • 2.4 One Platform. Endless Possibilities.
  • 3. Market Analysis
    • 3.1 Current Landscape
    • 3.2 User Personas
    • 3.3 Competitor Landscape
  • 4. The Problem
    • 4.1 Content Overload and Burnout
  • 4.2 Platform Switching Inefficiencies
  • 4.3 Inconsistency in Brand Tone and Style
  • 4.4 Cost and Learning Curve of Using Multiple Tools
  • 4.5 Lack of Customization and Prompt Memory in Most AI Platforms
  • 5. The Solution: Craft
    • 5.1 What is Craft?
    • 5.2 Why Craft is Different
  • 6. Platform Architecture
    • 6.1 Technical Overview
    • 6.2 AI Layer
    • 6.3 Modular Tools Framework
    • 6.4 Security and Privacy
  • 7. Key Features
    • 7.1 AI Writer Suite
    • 7.2 AI Image & Video
    • 7.3 AI Voice & Audio Tools
    • 7.4 AI Chat & Agents
    • 7.5 Developer Tools
    • 7.6 Business Tools
    • 7.7 Productivity Tools
    • 7.8 Advanced Features
  • 8. User Experience (UX)
    • 8.1 Unified Dashboard
    • 8.2 Prompt UX Innovation
  • 9. Use Cases
    • 9.1 Solopreneurs Building a Brand
    • 9.2 Agencies Scaling Content Production
    • 9.3 Developers Building Agents
    • 9.4 Students Writing Thesis or Reports
    • 9.5 Businesses Automating Documentation
  • 10. Monetization Model
    • 10.1 Freemium Model
    • 10.2 Premium Monthly and Yearly Plans
    • 10.3 Enterprise and Team Plans
    • 10.4 Affiliate Program
    • 10.5 API-Based Metered Pricing
  • 11. Tokenomics
    • 11.1 Design Philosophy
    • 11.2 Allocation Rationale
  • 12. Roadmap
    • 12.1 Past Milestones
    • 12.2 Current Focus
    • 12.3 Future Vision
  • 13. Community & Ecosystem
    • 13.1 Affiliate and Ambassador Programs
    • 13.2 Feedback Loops and Feature Voting
    • 13.3 Content Challenges & Partnerships
    • 13.4 Integration with Creative Communities
  • 14. Technical Challenges & Solutions
    • 14.1 Model Latency and Response Quality
    • 14.2 Prompt Fatigue and Hallucinations
    • 14.3 Cost Management at Scale
    • 14.4 Audio and Video Output Quality
    • 14.5 File Parsing for Large Documents
  • 15. Legal, Ethics & Compliance
    • 15.1 Responsible AI Usage Policies
    • 15.2 Data Handling and Content Ownership
    • 15.3 Fair Use of Generated Media
    • 15.4 Transparency in Model Attribution
  • 16. CONCLUSION
    • 16.1 Recap of Craft’s Mission
    • 16.2 Call to Action for Creators and Partners
    • 16.3 Vision for the Future of AI Creation
  • 17. APPENDIX
    • 17.1 Glossary of Terms
    • 17.2 Tool Descriptions
    • 17.3 Supported File Types
    • 17.4 Model Attribution
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  1. 15. Legal, Ethics & Compliance

15.4 Transparency in Model Attribution

Transparency is a non-negotiable pillar of trust in artificial intelligence. Craft provides full disclosure of the models powering its features, including third-party LLMs (such as OpenAI’s GPT-4, Anthropic’s Claude, or Mistral) and generative tools (such as Stability AI for images or ElevenLabs for voice synthesis). For each AI tool, the platform clearly identifies the source model or engine used, either through tooltips, interface notes, or documentation. Additionally, Craft tags generated outputs with metadata that optionally allows users to credit the AI origin. In the case of enterprise deployments, Craft provides detailed model documentation, model changelogs, and API-level transparency to ensure complete visibility into what powers the end-user experience. This enables regulatory alignment and ethical accountability at both the user and organizational level.

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