Oracle API Processing

Initially, your teams would work together to integrate your API with Oracle's systems. This involves setting up secure authentication mechanisms (e.g., API keys, OAuth) to ensure that all data exchanges are secure and authorized.

Oracle's Role: Oracle collects text and media (images/videos) related to a brand from various online sources based on predefined keywords. When Oracle's system identifies content with potentially negative sentiment or requires image/video analysis, it packages the content (or references to it) and metadata into a structured format.
Submission to Your API: Oracle sends this data to your service through an API call. The data could include direct media files, URLs to media, accompanying text, and any relevant metadata that could aid in the analysis.

Content Receipt: Your system acknowledges receipt of the data and begins processing. This may involve extracting media from URLs, validating file types, and other pre-processing steps.
Image/Video Recognition: Using machine learning models, your service analyzes the content to identify specific patterns, objects, or other indicators of malicious or harmful content.
Analysis Results: Your system compiles the findings, which may include the presence of malicious content, confidence scores, types of issues detected (e.g., inappropriate content, fake images), and relevant metadata.

Result Transmission: Your system packages the analysis results into a structured response format and sends this back to Oracle via the API.
Oracle's Use of Results: Oracle receives the analysis results and incorporates this data into their broader contextual intelligence dashboard or reports. This could trigger alerts, inform content moderation decisions, or feed into Oracle’s recommendations for brand protection strategies.

Optionally, a feedback mechanism can be established where Oracle can report the accuracy of the detections back to your system. This information can be used to continually train and improve your machine learning models, enhancing the service's effectiveness over time.

Scalability: The system must be designed to handle high volumes of requests and data efficiently, ensuring timely processing and response.
Security: All data exchanges should be conducted over secure connections (e.g., HTTPS), with strict data handling and privacy protocols to protect sensitive information.
API Rate Limiting and Management: Implement rate limiting and efficient request management to optimize resource use while staying within operational limits.