# Helvia.ai Release 5.88.0

## 1. Live Chat Agent Name Masking for Zendesk and Cisco

Enhance privacy in customer interactions with the new **Agent Name Masking** feature for Zendesk and Cisco Live Chat integrations. Admins can now define a **regex rule** to automatically mask agent names according to a custom format—such as converting “John White” into “John W.” This ensures a consistent, privacy-compliant presentation of agent information across all chat channels.

If you want to activate this, speak to the Helvia team.

## 2. Live Chat Agent Notification When User Closes the Chat Window for Genesys

Stay informed and respond proactively with the new **User Closure Notification** feature for LiveChat. When a user closes the chat window—on desktop or mobile—agents now receive a discreet English message (e.g., “The user has closed the chat window.”) visible only to them.

This improvement helps agents manage conversations more effectively by knowing when a user has exited. 

Speak to the Helvia team if you would like to enable this feature.

## 3. “LiveChat Cancelled” System Message in Chat Sessions

Gain clearer visibility into chat activity with the new **“LiveChat Cancelled”** system message in Chat Sessions. When a live chat request is canceled, a system message now appears automatically, matching the format of existing system events.

<figure><img src="https://604830754-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FBM1xs3i59ajeTgi4uVfN%2Fuploads%2FfF1CxJe2j5Dcko1WDZW9%2Fimage.png?alt=media&#x26;token=02a7a4b2-3529-42a3-b827-0a45239b25ed" alt="" width="364"><figcaption></figcaption></figure>

This enhancement helps chat reviewers and support teams easily track when users or systems terminate chat requests, improving transparency in conversation audits and operational reporting.

## 4. Language Selection using Viber and Messenger Links

Deliver a more personalized experience with automatic **language selection** for users accessing your service via Viber deeplinks or Messenger referral links. When a user joins a session through one of these channels, the platform now detects and applies the **language specified in the link**, overriding the default deployment language.

This ensures users immediately interact with your AI agent in their preferred language—without manual adjustments—improving accessibility and engagement across multilingual audiences.

**Example use case:**\
A marketing campaign targeting Spanish-speaking customers can include a Messenger referral link with lang:es, ensuring the conversation begins directly in Spanish when users click through. The same could be achieved for Viber with a deep linκ.

## 5. Automated Agent Testing

Streamline and simplify agent validation with the new **Automated Agent Testing** LLM plugin. This feature enables organizations to ensure agent responses are consistent, accurate, and reliable without manual testing, reducing errors and saving operational time.&#x20;

Platform admins can activate or deactivate the plugin directly from the console, enabling automated testing of AI agent flows currently via OpenAI integrations.

<figure><img src="https://604830754-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FBM1xs3i59ajeTgi4uVfN%2Fuploads%2FboJv55ojo85yd9gphCmG%2Fimage.png?alt=media&#x26;token=ae6fd7a1-5df7-4ca4-97ca-4c8b55d1fb9f" alt="" width="480"><figcaption></figcaption></figure>

All automated agent tests are managed in a **centralized Testing screen**, displaying all tests in a comprehensive table independent of date filters. Users can **create new tests** or **edit existing ones** using intuitive forms.&#x20;

<figure><img src="https://604830754-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FBM1xs3i59ajeTgi4uVfN%2Fuploads%2FVmcBOgJiRQQWakUjRc2V%2Fimage.png?alt=media&#x26;token=a0426605-c1c5-4c04-b01a-2b1f748f2f43" alt="" width="563"><figcaption></figcaption></figure>

After running tests, a dedicated **Results view** provides pass/fail outcomes, detailed logs, and flow performance insights.

<figure><img src="https://604830754-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FBM1xs3i59ajeTgi4uVfN%2Fuploads%2FiKAuEiqp4OGJso5XmGb9%2Fimage.png?alt=media&#x26;token=c37c059d-8155-41f4-975f-e92f6f057352" alt="" width="563"><figcaption></figcaption></figure>

This end-to-end workflow ensures agent responses are consistent, accurate, and reliable, reduces manual testing effort, and helps teams quickly identify and fix issues before release.