AI Agent Studio v.36 release
- Updated: 2025/04/02
What's new
AI Guardrails
This release introduces AI Guardrails, a new feature protecting sensitive data and promoting responsible AI usage. AI Guardrails protect sensitive data by masking PII, PHI, and PCI within prompts sent to LLMs. Additionally, they monitor prompts and responses for potentially harmful language. Administrators can configure data masking rules and assign them to specific folders, ensuring consistent data protection across automations. Important: The AI Guardrails offering is available on
Automation 360
Cloud, and will be available for
use with AI Guardrail (Number of LLM Prompts) license along
with the Enterprise Platform license. For
details about this license, see Enterprise
Platform. |
System prompt in AI Skills
Within AI Skills, a new feature called System Prompt will be introduced. This optional field, visible to anyone with access to view or edit the AI Skill, allows you to provide initial instructions or context to the underlying model. The System prompt helps to orient or ground the model, influencing its responses to user prompts and ensuring more relevant and accurate outputs. The System prompt field is displayed for all models. For models that support System prompt, the provided text will be sent as a System prompt. For models that do not support System prompts, the text provided in the System prompt field will be placed before the User prompt. |
Enable or disable
AI Guardrails policies globally within
the Control Room
Administrators can now enable the AI Guardrails in the Control Room with a cloud license by navigating to . When this setting is enabled, Professional Developers can create AI Guardrails to enforce rules for protecting sensitive information and promote responsible AI usage. |
Support for RAG
capability in AI Agent Studio to create grounded
Model connections using Azure OpenAI
Grounded by AI Search Create Grounded by AI Search Model connections using the native RAG (retrieval-augmented generation) capability from Azure OpenAI to retrieve information from Azure AI Search indexes for more accurate and relevant responses. Create Grounded Model connections with Azure OpenAI RAG capability |
Test with AI guardrail in AI Skills Enhance the reliability and safety of your AI Skills by testing them against AI Guardrails before deployment. This new feature allows you to simulate the effects of your chosen guardrails on prompts and model responses. This update provides toxicity and data masking results. You can click the view data masking execution option to reveal the tokenized masked values of sensitive data. Gain valuable insights into how your AI Skill will perform in a production environment with guardrails enabled. Access this functionality within the AI Skills editor and review the AI Governance logs for a detailed record of each test. |
Custom model definitions - Authenticate
with AWS Signature authentication This release
introduces support for AWS Signature authentication when
defining custom models in AI Agent Studio. This
enhancement allows you to seamlessly integrate with a wider
range of AWS-based AI/ML services that use this
authentication method. You can now set the
For
example:
|
Custom model definitions - Update existing model This release introduces the ability to modify existing custom model definitions using the newly introduced PUT and PATCH methods. Previously, modifications to an existing custom model were not supported. PUT (Replace/Update
entire model): Use the PUT endpoint to completely
replace or update an existing custom model definition. This
method is used when you need to update multiple properties
of the model.
Note: This action is restricted to
custom models that have no associated Model connections.
PATCH (Partial update - Name and
Description): Use the PATCH endpoint to update only
the name and description of an existing custom model
definition.
Both endpoints require the |
Custom model definitions - List custom
models API, can be filtered by vendor name This release introduces the ability to filter the list of custom models by vendor name and sort the results based on specific criteria.
Request
body:
|
Support for RAG
capability in AI Agent Studio to create grounded
Model connections using Azure OpenAI
Grounded by AI Search Create Grounded by AI Search Model connections using the native RAG (retrieval-augmented generation) capability from Azure OpenAI to build rich search experiences that combine large language models with enterprise data from Azure AI Search. Create Grounded Model connections with Azure OpenAI RAG capability |
Introducing GenAI model calls widget The new GenAI model calls widget within the AI Governance dashboard in the home screen displays the top 5 GenAI models used in the automations. Clicking on a model name drills down to the AI Governance Event Log, pre-filtered for that model. |
What's changed
Custom Model Integration
Enhancements (Service Cloud Case ID: 02147228) AI Agent Studio now supports the integration of custom large language models (LLMs) that you have developed or deployed. This feature now includes APIs for full lifecycle management of these custom models, including defining, retrieving, modifying, and removing them, giving you the ability to use specialized AI models within the AI Agent Studio. |
Search and add roles in create Model connections wizard You can now search and add roles while creating Model connections. |
Enhanced AI Governance
Logging for Parent/Child Bot Execution AI Governance logs now provide enhanced visibility into bot execution by accurately reflecting parent bot details when initiating child bots, applicable to both Generative AI Command packages and automations leveraging AI Skills. Previously, logs displayed child bot information, creating inconsistency. This enhancement ensures logs now include the parent bot ID, name, and folder path for improved audit trails. For example, if parent bot ID 103 triggers a child bot, logs will correctly show 103, not the child bot's ID. This improvement impacts both prompt and event logs within AI Governance. |
AI Governance
AI prompt log and Event log
tabs: New AI guardrail column A new column, AI guardrail, has been added to the AI Governance AI prompt log and Event log screens. A new field AI guardrail is also included within the session details or events when you open individual prompt or event logs. This column provides information about the specific guardrails applied to each prompts and events. Monitor AI prompt log interactions | Monitor Event log interactions |
Enhancement to AI Governance
AI prompt log : New Toxicity analysis and System prompt/User prompt
|
Enhancement to AI Governance
Event log : New Toxicity analysis and System prompt/User prompt
|
Fixes
The Anthropic Claude 2.1 and Anthropic Claude 3.5 models, which are not supported on Amazon Bedrock as a fine-tuned models, have been removed from the available model options within the Amazon Bedrock fine-tuned types. Previously, these models were incorrectly displayed in the model selection when selecting Fine-tuned as the type under Amazon Bedrock. |
Fix for an issue where AI Governance logs were not supported for API Tasks run in real-time mode (attended automation). This limitation has been resolved in this release. |
Fix for the misleading error message that incorrectly states that the Bot Agent needs an update for accurate AI Governance logging. Previously, this error was observed within the AI Governance sections, specifically the AI prompt log and Event log for Bot Agent versions 22.100.xx or later. |
Fix for an issue where you will incorrectly receive a notification prompting a Bot Agent update for AI Governance audit logs. Previously, this notification incorrectly appeared in settings and AI Governance logs ( AI prompt log and Event log) even when using compatible Bot Agent versions (22.60.10 and later). |
Limitations
Assigning folders to AI Guardrails
|
When clicking on a model name containing
special characters (such as "*", "?", "+", "=", "&&",
"||", ">", "<", "!", "(", ")", "{", "}", "[", "]", "^",
"~", ":", or words enclosed within double quotes) within the AI Governance dashboard in the home screen of the
Most used models widget, an error
message is displayed similar to the following screen shot. This
occurs because the search functionality within the AI Governance dashboard does not currently
support these special characters. |
The Folder field within the File Properties of an AI Skill or an AI Skill template does not currently function as intended. Changing the folder location in this screen does not actually move the AI Skill or the AI Skill template to the specified location when the changes are saved. |
Test with AI guardrail is unavailable for System prompt in AI Skills Test with AI guardrail is currently not support for system prompts within the AI Skills editor. While guardrails will function correctly for system prompts when used within automations and executed at run time. This means that you cannot directly test the application of guardrails to system prompts during the AI Skill development phase. This limitation only affects the testing with AI guardrail. |
AI Skill
API Task logging issue AI Skill executions triggered via on-demand API Tasks do not log responses to the AI Governance Event log. Adding a Delay action of at least 1 second after the AI Skill: Execute action for all on-demand API Task executions is a current temporary solution to resolve this logging issue. ![]() |
Updates to the interface
AI Guardrails |
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A new navigation menu is introduced to access AI Guardrails: |