HaloPSA 2.152 (Latest Stable) and AI Changes

Introduction

Welcome back again to my YouTube channel! If you were here yesterday for my video and documentation, thank you, I appreciate it.

In this video, we'll be exploring the latest stable version of HaloPSA (2.152) and discussing the hottest topic of the day: artificial intelligence (AI). I'll share my screen and guide you through my training instance of HaloPSA, focusing on new AI features and their configurations.

Getting Started with HaloPSA 2.152

We are currently running on version 2.152.34. Let's dive into the release notes and explore the new AI features:

• AI suggestions: Article suggestions are now available.
• Article suggestions: Readily accessible to provide more efficient solutions.

Important Warnings

1. Demo Environments: The demo instances come configured with HaloPSA's Azure OpenAI instance. You can use this out of the box, but be cautious about data sovereignty and ownership. You also have the ability to configure your own OpenAI connection.
2. AI Modules Separation: With the recent update, AI Integrations are now separated. This update allows you to choose between OpenAI and Azure OpenAI ChatGPT.

Configuration

Testing AI Integration

1. OpenAI Setup:

   • Access the Integration settings.
   • Verify configurations.
   • Test ticket creation to ensure proper AI responses.

2. Embeddings Deployment:

   • Embeddings require specific models. Ensure correct models are chosen and updated.

AI Insights

AI Insights can evaluate ticket data:

• Sentiment Analysis: Evaluate and categorize the tonality of tickets.
• Ticket Summarization: Generate summaries and recommendations based on ticket content.

Knowledge Base Search

HaloPSA enhances Knowledge Base searches using AI embeddings. This can be done using built-in functionality or Azure AI Search.

Knowledge Base Creation

A significant feature of the new update is AI-assisted Knowledge Base creation. The system automatically generates articles based on ticket data, offering a streamlined workflow. However, ensure customization and validation to meet specific standards and settings.

Emotion Detection and Reporting

Emotion detection analyzes user interactions to evaluate emotional states. Configure the system to detect user emotions upon closing tickets or triggering specific events.

Challenges and Workarounds

During configurations and testing, you might face some challenges such as broken run books or incorrect settings. Debugging involves:

• Fixing methods and variables.
• Understanding and adjusting API expectations.
• Reviewing and updating run book configurations.

Conclusion

HaloPSA 2.152 introduces many AI-driven functionalities, from sentiment analysis, knowledge base article generation, to emotion detection. While some features might require debugging to work out-of-the-box, the addition of these enhanced AI tools signifies a step forward in automating and optimizing service management workflows.

Keywords

• HaloPSA 2.152
• AI Integration
• Azure OpenAI
• Knowledge Base Creation
• Sentiment Analysis
• Emotion Detection
• Embeddings Deployment

FAQ

What is the latest stable version of HaloPSA discussed in the video?

The latest stable version discussed is HaloPSA 2.152.34.

Can I use HaloPSA's Azure OpenAI instance in the demo environment?

Yes, demo environments come configured with HaloPSA's Azure OpenAI instance, but you can also configure your own OpenAI connection.

Are AI integrations separated in the latest update?

Yes, AI integrations are now separated, allowing you to choose between OpenAI and Azure OpenAI ChatGPT.

How does AI Insights help in ticket management?

AI Insights help by evaluating the sentiment of tickets, generating ticket summaries, and providing recommendations.

How does HaloPSA enhance Knowledge Base searches?

HaloPSA enhances Knowledge Base searches using AI embeddings and can integrate with Azure AI Search for improved article and ticket identification.

Can AI generate Knowledge Base articles automatically?

Yes, HaloPSA can automatically generate Knowledge Base articles from ticket data using AI, but customization and validation are recommended.

What is Emotion Detection in HaloPSA?

Emotion Detection analyzes user interactions to determine their emotional states, which helps in understanding customer satisfaction and sentiment trends.

What should I do if I face issues with AI run books and configurations?

Debugging may involve fixing methods and variables, adjusting API expectations, and updating run book configurations to align with your specific system settings.