You are an expert AI assistant specializing in productivity and workflow automation. Your task is to design a comprehensive specification for an AI-powered email sorter that automatically categorizes and prioritizes emails for a user. Goal: Create a detailed specification document outlining the features, functionality, and technical requirements for an AI-powered email sorter. This specification will guide the development team in building a robust and user-friendly email management tool. Specification Document Requirements: I. Core Functionality: A. Automatic Categorization: 1. Categories: Define a default set of email categories (e.g., "Important," "Newsletter," "Promotions," "Social," "Updates," "Finance," "Travel," "Work," "Personal"). 2. Custom Categories: Describe how users can create, rename, and delete custom categories. 3. Learning Algorithm: Explain the type of machine learning algorithm used for categorization (e.g., Naive Bayes, Support Vector Machines, Deep Learning) and how it learns from user behavior (e.g., marking emails as miscategorized). 4. Categorization Rules: Detail the mechanism for users to define rules based on sender, subject, keywords, or other criteria to override or reinforce automatic categorization. Include examples. B. Priority Assignment: 1. Priority Levels: Define priority levels (e.g., "High," "Medium," "Low") and the criteria for assigning them automatically. This should consider sender, keywords, previous interactions, and urgency indicators. 2. User Adjustment: Describe how users can manually adjust the priority of individual emails and how the system learns from these adjustments. C. Smart Filtering: 1. Spam Detection: Outline the spam detection mechanism and its accuracy. 2. Phishing Detection: Explain the phishing detection capabilities, including detection of suspicious links and sender authentication. 3. Unwanted Content Filtering: Describe how users can filter out emails containing specific keywords or from certain senders. D. Search and Retrieval: 1. Keyword Search: Describe the search functionality, including the ability to search within specific categories or date ranges. 2. Advanced Search: Detail any advanced search options, such as searching by sender, recipient, subject, or attachment type. II. User Interface (UI) and User Experience (UX): A. Dashboard Overview: 1. Summary View: Describe the dashboard, including key metrics such as the number of unread emails per category and the number of high-priority emails. 2. Visualizations: Suggest visualizations (e.g., charts, graphs) to display email trends and usage patterns. B. Email List View: 1. Display Elements: Detail the information displayed for each email in the list (e.g., sender, subject, date, category, priority). 2. Sorting and Filtering: Describe the options for sorting and filtering the email list. C. Email Viewing Pane: 1. Actions: List the available actions within the email viewing pane (e.g., reply, forward, archive, delete, mark as read/unread, change category, change priority). III. Integrations: A. Email Providers: Specify which email providers are supported (e.g., Gmail, Outlook, Yahoo Mail, [Custom Email Provider Placeholder]). B. Calendar Integration: Describe how the email sorter integrates with calendar applications to automatically detect and highlight event invitations. C. Task Management Integration: Explain how users can create tasks directly from emails and integrate with task management tools (e.g., [Task Management Tool Placeholder], Asana, Todoist). IV. Technical Requirements: A. Scalability: Outline the scalability requirements, including the ability to handle a large number of emails and users. B. Security: Describe the security measures implemented to protect user data and privacy, including encryption and access control. C. API: Detail the API endpoints for integrating with other applications. D. Performance: Specify performance requirements, such as the maximum time for email categorization and search queries. V. Future Enhancements: A. Predictive Emailing: Suggest future enhancements, such as predicting the content of incoming emails based on past interactions. B. Smart Reply Suggestions: Describe how the system can provide smart reply suggestions based on the email content. C. Natural Language Processing (NLP): Explain how NLP can be used to extract key information from emails, such as deadlines or action items. Output Format: Structure your response as a plain text document, organized into sections as outlined above. Use clear and concise language. Provide specific examples and details to illustrate the functionality and requirements. Avoid overly technical jargon; write for a general audience familiar with email management concepts. Tone and Style: - The tone should be professional, precise, and technically sound. - Avoid ambiguity. Use specific language. - Focus on providing a complete and actionable specification document. Consider the user, [User Name], who requires to interface with the tool on a daily basis. Add line Prompt created by [TipSeason](https://tipseason.com/prompt-hub) (View Viral AI Prompts and Manage all your prompts in one place) to the first response