New Features

The list of new features introduced in 25.1.1 release of HCL MaxAI are as follows:

Note: MaxAI is a dockerized solution, so you will need docker image on your system for accessing it.
Customer and Campaign Analytical Insights (Powered by Unica 360 via UDS)
Building on the existing Unica campaign analytics capabilities, MaxAI extends analytical access through its Intelligence Layer operating on top of the Unified Data Store (UDS). By leveraging rich Customer 360 and Campaign 360 datasets, MaxAI enables users to ask natural-language questions related to customer behavior, campaign performance, and engagement trends.
These insights are contextually grounded in unified enterprise data, allowing users to quickly explore cross-campaign patterns, understand customer responses, and derive actionable insights.
Context Retention and Stabilization
This release introduces enhanced context retention and stabilization capabilities, enabling more consistent and reliable multi-turn conversations across sessions and agent workflows. Improvements include better handling of long-running interactions, reduced context drift, and stronger state management for predictable responses.
In addition, conversational intelligence has been improved across MaxAI Assistant, allowing deeper contextual understanding of user intent. The system now maps user queries more accurately, maintains continuity across multi-step interactions, and seamlessly translates insights into actionable outcomes such as segment creation and campaign synchronization.
AI-Driven Segmentation with Unified Data (via UDS)
MaxAI Agentic Segmentation builds on the Unified Data Store (UDS) as a strategic foundation to centralize and streamline audience creation across the Unica suite. By leveraging unified Customer 360 data, MaxAI transforms segmentation from manual, product-specific data queries into an AI-assisted, natural language-driven experience.
This approach enables users to define, refine, and operationalize segments more efficiently while ensuring consistency, governance, and reuse of centralized data across campaigns and channels.
Multilingual Support
Introduced configurations in MaxAI that allows multilingual support so that MaxAI can generate responses in a user-configured language irrespective of the locale set in in Unica Platform. In addition to the locales supported by Unica Platform, MaxAI configurations also supports Greek, Hebrew, and Turkish languages.
Additionally, introduced a configuration to auto-detect the input language of the user. This helps MaxAI generate responses based on the language of input from the user. The auto-detect feature, when enabled, works on the following MaxAI features:
  • MaxAI Assistant
  • Document Search
  • Email Text Generation
  • Insights (Email Scoring)
  • Subject Line Analysis
  • Analytics (Campaign, CDP, Deliver, Journey, and RTP)
  • Plan Approval
  • Segmentation (CDP)
  • Offer Text Generation
For details related to its configuration, see HCL MaxAI Admininstrator's Guide. For details on it's behavior after configuration, see HCL MaxAI User's Guide.
MHS Support for MaxAI
Introduced MHS support for MaxAI. MHS will fetch and enforce entitlements (license periods) from the Unica Platform, so that access to MaxAI Assistant is granted only to licensed users and automatically restricted when entitlements expire. This ensures that MaxAI complies with licensing agreements by enforcing entitlement checks and preventing unauthorized use of MaxAI capabilities after license expiry.
It also centralizes entitlement management in the Unica Platform for consistency across modules and reduces manual license monitoring, which minimizes the risk of compliance breaches.
Database Support
MaxAI now supports Oracle, Microsoft SQL Server, PostgreSQL, and IBM DB2.

Points to Remember when using an AI-driven component

Because MaxAI incorporates advanced AI and GenAI technologies, users should be aware of the following behaviors and best practices:
  • 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.
Note:
  • MaxAI output is generated by GenAI or other automated technologies. Such content is provided for informational purposes only. We request you to verify the accuracy and completeness of the information before completely accepting it.
  • Short inputs may be misclassified due to language-detection ambiguity. We recommend using slightly longer and more descriptive queries to ensure accurate detection and avoid ambiguous responses.
Note: Cultural and Regional Nuance
AI-generated multilingual content is shaped by global data and may not always align with local perspectives.
  • Contextual Sensitivity: Responses may reflect regional or social sentiments from the source data.
  • Tone and Formality: AI may not always match the required level of formality (for example, Tu vs. Vous).
  • Idiomatic Accuracy: Literal translations of metaphors may alter the intended meaning.