An Introduction to MaxAI
MaxAI is an AI-driven offering introduced in 25.1.0 version of HCL Unica+. It is a part of the HCL Unica+ marketing platform.
Overview
MaxAI is an advanced AI-powered platform designed to streamline data analysis, documentation search, and report interpretation within the HCL Unica+ offering. It integrates Natural Language Processing (NLP), document embeddings, and advanced LLM (Learning Language Model) capabilities to deliver precise and actionable insights.
Key Features
The key features of MaxAI are as follows:
| Feature Name | Description |
|---|---|
| MaxAI Assistant | Helps in real-time decisions and optimizations. Ask any query
related to Unica product suite and the Assistant provides quick and
accurate answers. The supported queries are:
|
| MaxAI Content Generation | Enables a Marketer to effortlessly optimize the content of their
emails. With intelligent AI-driven suggestions, marketers can
instantly refine their messaging for better clarity, tone, and
impact ensuring that the core message resonates with their audience.
Content Generation includes:
|
| MaxAI Email Scoring and Insights | Enables a Marketer to improve their email content by scoring it based on various marketing-related parameters. With intelligent AI-driven suggestions, marketers can refine their email communication to make it a professional and high-impact marketing communication. |
| MaxAI Journey Insights | Access actionable insights for Unica Journey and Unica Deliver. In just a few clicks, marketers can move from observation to action. |
| MaxAI Reporting Insights | AI-driven insights provides contextual and actionable-analysis based on the selected chart or report. With the analysis, you can continue to the chat with the AI in MaxAI assistant, ask follow-up questions to receive appropriate responses enabling seamless exploration of trends, detection of anomalies, and data-driven recommendations. |
| MaxAI Session Insights | AI-driven insights provides contextual and actionable-analysis based on the selected session. |
Points to Remember when using an AI-driven component
- Iterative Learning and Improvement: MaxAI leverages iterative improvements. Initial responses may vary in accuracy and relevance; both prompts and responses can refine over time based on user feedback and improved system tuning. Expect continuous enhancement, not day-one perfection.
- Non-deterministic Outputs: MaxAI utilizes large language models (LLMs), which are inherently non-deterministic, identical queries may yield different responses across sessions or users.
- Context-dependent Results: For analytical queries, MaxAI tries for accurate computation based on available data. However, how results are summarized or explained may vary depending on the retained context for the session.
- Handling of Vague or Incomplete Queries: Ambiguous or incomplete questions may trigger clarification prompts from MaxAI, or result in less precise answers. Providing context-rich and specific queries improves outcomes.
- Session Context and Continuity: Cross-context or unrelated queries within the same session may lead to confusion or errors in responses. For best results, keep queries within a logical context thread or start new sessions for unrelated topics.
- Data Dependency and Accuracy: MaxAI relies on access to up-to-date, accurate, and complete data sources. If the underlying data or documentation is outdated, incomplete, or inconsistent, the AI’s responses and analytical outputs may be impacted even if the logic or query syntax is correct.
- Explainability: MaxAIs documentation related responses sometimes include links to underlying documentation or data. That helps to review supporting details when available.
MaxAI Workbench
- AutoML
Enable business user-generated ML models with no code approach
- MLOPs
Model Versioning, Deployment & Drift Monitoring
- MLac
Machine Learning as Code for automatic pipeline code generation
- Explainability
Higher accuracy predictions with supported explanations and model confidence
Although. MaxAI Workbench is part of MaxAI, it has a separate set of documentation. For more information, see MaxAI Workbench documentation.