The template reflects the steps set out in the PRINCE2 Method and is designed to prompt the Project Manag­er and help in the creation of the Project Brief.

PROJECT DOCUMENTATION

PROJECT BRIEF

This document is only valid on the day it was printed.

The source of the document will be found at this location – [insert folder structure]

Date of this revision:           

Date of next revision:          

This document requires the following approvals.

Signed approval forms should be filed appropriately in the project filing system.

This document has been distributed to:

  Page

1.Project Brief History                                                                                            

        1.1  Document Location                                                                         

        1.2  Revision History

        1.3  Approvals

        1.4  Distribution

2  Table of Contents

3  Project Definition

4  Outline Business Case

5  Project Product Description

6  Project Approach

7  Project Management Team Structure

8  Role Descriptions

9  References

3.1 Background

Social media platforms have strict content policies that users must adhere to. Violating these policies can lead to content takedowns, account suspensions, or even permanent bans. Many users and businesses struggle to ensure their media like images, videos, and text complies with platform-specific guidelines before posting. Media Report AI aims to provide a pre-check system to prevent policy violations.

3.2 Objectives

• Deliver a functional MVP within six months, with iterative improvements based on user feedback.
• Optimize infrastructure to minimize operational costs, leveraging cloud-based AI models where necessary.
• Ensure high detection accuracy using AI models trained on diverse datasets.
• Develop an AI-driven application that analyses media uploads against predefined social media policies.
• Potential false positives/negatives in content classification, evolving platform policies requiring frequent updates.
• Reduce the risk of content takedowns, increase compliance confidence for users, and save time for businesses managing multiple accounts.

3.3 Expected Outcomes

• Users can upload text, images, and videos for real-time compliance verification.
• The system provides a confidence score and detailed feedback report on potential violations.
• A dashboard tracks past verifications and allows users to refine their content.

3.4 Project Scope

AI-based content analysis, integration with major social media policies, and user-friendly reporting. Excluding Automated content modification or legal compliance guarantees.

3.5 Constraints and Assumptions

Social media platforms will continue providing publicly available content policies. The AI model can be updated regularly to keep up with policy changes. Users will manually adjust content based on recommendations.

3.6 Project Tolerances

A tolerance of ±10% in accuracy rate for content detection in the MVP phase. A delay of up to one month is acceptable for major feature rollouts if required.

3.7 User(s) and Interested Parties:

Content creators, social media managers, businesses, and influencers. Social media compliance officers and digital marketing agencies would be our stakeholders.

3.8 Interfaces:

• Web-based interface for uploads and analysis.
• API integrations for third-party tools (e.g., social media scheduling apps).
• Admin dashboard for system monitoring and updates.

Reasons why the project is needed:

Increasing scrutiny and regulation of online content necessitate better compliance tools. Businesses and influencers risk penalties for unintentional policy violations. Current compliance checks are often manual, time-consuming, and prone to errors.

Business Option Selected:

Developing an AI-driven compliance verification tool is the most effective option, as it offers real-time feedback, scalability, and ease of use. Other options, such as manual review or third-party moderation services, are less efficient and more costly over time.

Customer’s Quality Expectations:

High accuracy in identifying potential policy violations. Fast processing times for uploaded content. User-friendly interface for seamless interaction.

User Acceptance Criteria:

Users can successfully upload and analyse their content. The system provides clear and actionable feedback. Compliance reports are easy to understand and export.

Operations and Maintenance Acceptance Criteria:

Regular updates to align with evolving social media policies. Minimal downtime and high system availability. Scalable infrastructure to accommodate user growth. 

The project will leverage AI-driven natural language processing (NLP) and computer vision models to analyse content. Built using a cloud-based, scalable architecture with a microservices approach.

• Technology Stack:
  • Backend: Node.js/Python for AI model integration.
  • Frontend: React.js for a responsive UI.
  • AI Models: Pre-trained and fine-tuned models for text and image analysis.
  • Database: PostgreSQL for structured data, NoSQL for AI-driven insights.
  • Deployment: AWS/GCP cloud infrastructure with auto-scaling capabilities.

The solution must integrate with existing social media platforms through APIs, providing seamless content verification before posting. Ensure data privacy by implementing secure authentication and encryption measures. The system must handle high user traffic efficiently, with load balancing and caching mechanisms.

• Project Sponsor: Responsible for overall project approval and funding.
• Project Manager: Oversees project execution, timelines, and risk management.
• AI Development Team: Builds and trains machine learning models for content verification.
• Backend Development Team: Develops the server-side logic and API integrations.
• Frontend Development Team: Designs and implements the user interface.
• QA & Testing Team: Ensures system accuracy and compliance with social media policies.
• DevOps Team: Manages cloud infrastructure, deployment, and system scaling.
• Compliance & Policy Experts: Monitors and updates AI models to align with evolving social media regulations.
• Customer Support Team: Assists users with queries and troubleshooting.
• Product Owner – Defines the product vision, prioritizes features, and ensures alignment with user needs.
• UI/UX Designer – Designs intuitive and accessible user interfaces and improves user experience.
• Data Engineer – Manages data pipelines, storage, and optimization for AI models.
• Business Analyst – Analyses market needs, gathers requirements, and refines product strategy.
• Marketing & Communications Team – Handles branding, outreach, and product positioning.
• Legal & Compliance Advisor – Ensures regulatory compliance and advises on data protection laws.
• Technical Support Engineer – Provides advanced troubleshooting beyond customer support.
• Community Manager – Engages with users, collects feedback, and helps improve product adoption.

9.References

Social media platforms’ official policy documentation (e.g., Facebook, Instagram, Twitter, YouTube, TikTok). AI ethics and compliance guidelines for content moderation. API documentation of integrated third-party services. Internal project roadmap and milestone documents. Testing and evaluation reports for AI model accuracy and performance. Security and data privacy compliance frameworks (e.g., GDPR, CCPA).