Defensive Publication Outline

The Future Has Arrived

Title:
System and Method for Context-Aware, User-Governed AI Email Reply Generation

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This invention relates to systems and methods that allow artificial intelligence (AI) to generate email replies in response to inbound messages—specifically unsolicited or repetitive messages—based on user-defined parameters for tone, legality, and context. The system ensures no unsolicited communication is initiated by the AI and that messages are generated only in response to actual incoming email.

Introduction

Background

Traditional spam filters block or quarantine unsolicited emails but fail to proactively communicate rejection or customize replies. Meanwhile, current autoresponders often send generic replies without context, tone control, or legal awareness. There's a growing need for AI-enhanced communication tools that intelligently respond, rather than initiate, with customizable safeguards and purpose-built use cases across administrative, procurement, customer service, and personal inbox management.

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Summary of Innovation

The disclosed system includes:

• A classification engine that distinguishes between spam, vendor, customer, official, and unknown message types.

• An AI-based email reply generator trained to understand message context, sender category, legal implications, and user-selected tone preferences.

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• A legal compliance layer that appends region-appropriate disclaimers or opt-out notices depending on the classification confidence score.

• A user-controlled reply policy module that allows for:

  • Default tone per sender type

  • Opt-in for disclaimers

  • Multilingual support

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System Components

Email Input Parser

• Parses incoming messages and extracts metadata.

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Sender Classifier

• Identifies sender category (e.g., known contact, vendor, government, spam).

Reply Generator (AI Mode)

• Creates a custom message based on templates and learned responses.

Tone Selector Module

• Adjusts response tone (formal, polite, assertive, soft, legal).

Legal Disclaimer Module

• Injects pre-built region-aware legal disclaimers where applicable.

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User Control Panel

• Lets the user adjust tone profiles, sender rules, reply approval settings.

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Key Functional Flow

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A. Spam Rejection Flow (QWITBOX)

1. Spam detected.

2. Reply generated stating no interest, legal rights reserved.

3. Disclaimers added in case of sender misclassification.

4. No further reply generated for repeat senders unless manually overridden

B. Routine Vendor Response Flow (ROUTINERESPONDER)

1. Recognizes routine vendor order or check-in.

2. Fetches prior history.

3. Replies with confirmation or update based on admin-defined preferences.

1. Email categorized as general admin request.

2. Replies crafted for scheduling, redirection, or confirmation.

3. User can pre-approve templates or opt-in to review before send.

C. Administrative Assistant Flow (AI-ADMIN)

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Examples of Use Cases

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Rejecting Spam With a Custom Response

• “This email was flagged as unsolicited...”

Responding to a Vendor's Monthly Invoice

• “We’ve received your invoice and will process it by…”

• “Thank you for reaching out...”

Reply to a Customer's Inquiry Using Tone Match to Brand Voice

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• The system never initiates outbound communication.

• Provides region-aware disclaimers (e.g., GDPR, CAN-SPAM).

• Offers user-tunable tone and legal thresholds.

• Works across international inboxes and supports multilingual replies.

Unique Attributes

• Modular engine (BOXTRAP-AI) powers different branded products.

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Diagrams

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Flowchart: Spam Reply

Shows the decision-making flow when an email is flagged as spam — including detection, reply generation, disclaimer injection, and response suppression for repeat offenders.

Flowchart: Vendor Message Response

Outlines the steps for handling routine vendor communications — such as order confirmations or invoice replies — using predefined admin preferences and message history.

System Architecture Diagram

Illustrates the overall structure of the QWITBOX system — how its components (e.g. email parser, classifier, AI generator, tone selector, legal module) interact from email intake to response delivery.

Visual preview of the user-facing control panel where users configure tone, disclaimer use, sender categories, approval workflows, and language preferences.

UI Mock Up of Settings Panel

Samples of actual AI-generated email responses across use cases (e.g. spam rejection, vendor communication, customer service), demonstrating tone, structure, and legal phrasing.

Example AI-Generated Message

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Prior Art & Differentiation

Unlike existing spam filters (e.g., Gmail, Outlook), this system:

• Is user-governed for full control.

• Responds intelligently, not just blocks.

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• Designed for productivity workflow, not merely defense.

• Embeds legal and tone intelligence per message type.

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This document is intended to serve as a defensive publication. It publicly discloses the invention to establish prior art under patent law and preclude others from claiming identical or substantially similar inventions.

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DRIDON, LLC

11a. Author

• DRIDON, LLC

11b. Affiliation

• QWITBOX / BOXTRAP-AI

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11c. Date of Disclosure

• August 21, 2025

Note on Intellectual Property: While this publication serves to establish prior art and prevent unauthorized patent claims, all written content, system descriptions, and branded elements (e.g., QWITBOX, BOXTRAP-AI) remain the exclusive intellectual property of DRIIDON, LLC.

This disclosure does not grant permission to reuse, reproduce, or commercially exploit any part of the material without express written authorization.

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