How can artificial intelligence assist Metastudio DRM users?


Some time ago in our company, we discussed the possibilities of using artificial intelligence in the Metastudio DRM solution. Often, installations at our clients help over 100 users manage hundreds of dictionaries with varying degrees of difficulty. Tracking logs becomes a challenge. No wonder one of the first ideas was to use AI to analyze application logs. Below are a few interesting ways that we think can help in analyzing Metastudio DRM logs:

Error Handling

An AI model can help identify and manage errors in application logs. Through machine learning algorithms, the model can learn to recognize patterns in logs and detect potential problems. For example, the model can identify errors related to connecting to a database and generate notifications for the relevant teams.

Application Optimization

Analyzing application logs can help optimize the application. An artificial intelligence model can be trained to identify repetitive patterns in logs that suggest performance issues with the application. For example, the model can detect that the database response time is too long, indicating the need to optimize database queries.

Creating New Structures

An AI model can also be used to create new data structures based on application logs. For example, the model can be trained to recognize data patterns in logs and create new structures that facilitate the processing of that data. This is particularly useful when the application generates a large amount of logs and manual processing is impossible.

Data Quality Management

An artificial intelligence model can also help ensure data quality in application logs. For example, the model can be trained to recognize data patterns that suggest data quality problems. Automatically generated notifications for the development team will help solve these problems.

Data Validation

An AI model can be used to validate data in application logs. It can be trained to recognize data patterns that are incorrect or may indicate issues with the application. For example, the model can detect that login data is incorrect and generate notifications to secure the application against potential attacks.

Soon we plan to release a new version of the software, and the next step will be to use artificial intelligence models not only for log analysis but also in other aspects. It is possible that a dedicated model supporting reference data management in organizations will be created. By using artificial intelligence in log analysis and other processes related to reference data, our Metastudio DRM solution will be even more efficient and user-friendly.

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