AI Replies and Data Processing: Model Overview, Security, and Compliance

Model Overview

For our AI-powered replies and summaries, we rely on OpenAI's GPT-4o-mini model. This model excels in natural language understanding and contextual response generation, making it ideal for handling diverse customer inquiries.

You can explore more about this model here: OpenAI GPT-4o-mini Documentation.

Processing Data

Only publicly available data, like app store reviews, and manually tagged data is processed by our AI models. These tags allow us to categorize and analyze feedback more effectively. Importantly, we use only the title and content of reviews for AI purposes.

Safeguards and Data Usage

All processing and analysis are conducted within the customer's AppFollow account, without external data sources. Manually tagged reviews are used as input to ensure that our models perform accurately and stay within their intended function. Automatic tagging is applied based on these inputs to provide a consistent categorization of user feedback.

Accuracy and Quality Assurance

The AI models are trained on manually tagged reviews to maintain high accuracy and quality. We use a feedback loop where incorrect tags can be reported, allowing for continuous improvement. Our QA processes include a trial period to validate tagging accuracy and coverage, precision, and recall metrics to monitor performance.

Handling Personal Data

We process two types of personal data:

1. Authorized Users of AppFollow Platform: This includes contact, usage, location, technical and transactional data, processed per user rights such as access, deletion, and correction.
2. Public App Store Reviewers: For users who post reviews, we process name/nickname, review content, location, language, and device details, based on platform-specific data-sharing capabilities.

For a detailed overview of our data handling practices and privacy commitments, visit our privacy policy: AppFollow Privacy Policy.