TABLE OF CONTENTS

• ACE:AI Overview
  • Data Transmission
    • In-house Applications
• Main Functions
  • Application Normalisation
  • Application Categorisation and Description
  • Application Vendor & Name Translation
  • Application Accept/Reject/Rationalise
  • Operating System End of Life Reports
• Further Support

ACE:AI Overview

ACE:AI (Asset Confidence Engine: Artificial Intelligence) is designed to minimise the time and expertise required to manage large-scale application estates in ManagementStudio. Enterprises typically have thousands of applications, including many discovered through Inventory Connectors such as the MECM/SCCM Connector. 

Traditionally, application specialists spend significant time reviewing pending applications, determining which are business-relevant, which versions require rationalisation, and which should be excluded as non-business applications. This process is further complicated by gaps in application knowledge.

ACE:AI streamlines these tasks by collecting and analysing accept/reject decisions submitted by ManagementStudio customers. This collective decision data is securely stored in the cloud and used to recommend actions with confidence ratings. For example, if 90% of customers have accepted a particular application, ACE:AI will recommend acceptance at that confidence level to other customers. These recommendations are updated as new customer decisions are added, ensuring the system continually improves.

When multiple versions of an application are detected, ACE:AI suggests rationalisation in line with version thresholds defined in Administration settings. This approach enables rapid, accurate assessment and rationalisation of applications, forming a solid foundation for transformation projects and business-as-usual operations.

Data Transmission

In-house Applications

During onboarding, each customer’s application list is manually reviewed. Exclusion filters are applied to ensure in-house applications are not added to the global ACE:AI catalogue or transmitted to the OpenAI API. For example, applications developed by a fictional customer, MyCorp, using the vendor name 'MyCorp', would be excluded.

Main Functions

Application Normalisation

Software vendors often use inconsistent naming and versioning for their products. Application normalisation resolves these inconsistencies, creating a unified, manageable set of application names and versions. ACE:AI supports both automatic and manual normalisation using a pre-defined ruleset.

Example:
Vendor applications might be listed as "Adobe", "Adobe Corp.", or "Adobe Inc." ACE:AI recommends standardising all such entries to "Adobe".

Usage Instructions

Application Categorisation and Description

ACE:AI retrieves categories and descriptions for recognised applications via the ChatGPT API. These can be applied manually or scheduled to run automatically. Categorisation settings can be found in the Application Normalisation section within ACE:AI.

Usage Instructions

Application Vendor & Name Translation

ACE:AI uses the OpenAI API for accurate vendor and application name translation, particularly when non-alphanumeric characters are detected in the original data. This translation is performed automatically.

Application Accept/Reject/Rationalise

ACE:AI aggregates past customer application decisions to generate confidence-rated recommendations for accepting, rejecting, or rationalising applications. This process can be manual or automated.

In-scope Application Example:

• 91 out of 100 customers mark Bloomberg as a valid business application.
• A new customer using ManagementStudio detects Bloomberg.
• ACE:AI recommends "Accept" for Bloomberg as an in-scope application with a confidence rating of 91%, with optional auto-rejection. 
• Multiple Bloomberg versions can be rationalised to the accepted version.

Out-of-scope Application Example:

• 9 out 12 customers mark Spotify as a non-business application (Reject).
• A new customer using ManagementStudio detects Spotify.
• ACE:AI recommends "Reject" for Spotify as out-of-scope with a confidence rating of 75%, with optional auto-rejection.

Rationalisation Example:

• When different versions of one application are found, ACE:AI can auto-rationalise them to the accepted version.

Usage Instructions

Operating System End of Life Reports

ACE:AI provides reporting on operating system end-of-life dates using the ManagementStudio algorithm. These reports are available in the built-in device report ACE - OS End of Life Report. End-of-life dates can be manually added to a Device Datamining Report by enabling Add OS End of Life Days in the Device Reporting Tier.

Further Support

For additional assistance, visit the ManagementStudio Service Desk to search the knowledge base or to submit a support ticket.