Migrate from legacy Ravenna AI to Agents and unlock new capabilities including rules-based automation, explicit resource control, and enhanced customization
Agents have been released to all organizations, replacing the legacy Ravenna AI system. Migrate to Agents to unlock new features including rules-based behavior, explicit resource access, and customizable personalities. Once you assign an agent to a , the legacy AI system for that channel automatically deactivates.
What changed
Agents replace legacy Ravenna AI with explicit rules-based configuration. Request Types renamed to Forms. Categories released as workspace-wide ticket classification.
Why migrate
Agents provide rules-based behavior control, explicit resource access via @ mentions, customizable personality, and advanced capabilities like escalation instructions and tool integrations.
What happens to legacy system
Legacy Ravenna AI remains active on existing channels until you assign an agent. Once migrated, the legacy system for that channel deactivates. New channels must use Agents.
A dedicated Agents tab now appears in the left sidebar for workspace configuration. Configure AI assistants with rules-based behavior, explicit resource access, customizable personality, and tool integrations. Each can have one agent assigned.
Request types renamed to forms
Throughout the platform, “Request types” have been renamed to . This better reflects their purpose as structured intake forms for capturing ticket information with .
Categories
now apply to all tickets as a workspace-wide classification system, accessible via workspace settings. Previously, categorization was embedded within Request Types. This separation makes Forms and Categories distinct, independent systems for ticket organization.
Slack file attachments in agent conversations
Agents can now read files that users share in Slack as part of a conversation. The agent extracts text from PDFs, images, and other supported documents, and uses the contents to answer questions, prefill forms, and route tickets. The agent briefly defers its response while Slack finishes processing the upload so the file contents are available when it replies. See file handling in agents.
Tool execution policies for agent rules
Tools referenced in a rule can now be gated with a per-rule execution policy: Auto-execute, Requires confirmation, or Requires approval. Approval-gated tools route through an approval template, or workspace admins by default, before the agent executes them. When the agent plans multiple gated calls in the same run, they open as a single batch of parallel approval rounds. Write and delete tools default to confirmation; read tools default to auto-execute. See tool execution policies.
Your existing legacy Ravenna AI settings remain active on configured channels until you assign an agent to those channels. This allows seamless migration without disrupting current operations.
Newly created channels cannot use the legacy Ravenna AI system. You must configure an agent for any new channels.
Once you assign an agent to a channel, the legacy Ravenna AI system for that channel automatically deactivates and is removed from the channel settings.
Agents unlock new capabilities that legacy Ravenna AI cannot provide. Migrate to gain explicit control over AI behavior, resource access, and customization.
Follow these steps to migrate from legacy Ravenna AI to Agents. Once you assign an agent to a , the legacy system for that channel automatically deactivates.
1
Review current configuration
Before migrating, review and understand your existing legacy Ravenna AI setup:
Which have AI enabled
What are connected
Which (previously Request Types) are available for automatic selection
Any custom personality or tone settings
2
Create an agent
Navigate to the Agents tab in your workspace settings and create a new agent. Start with basic settings and gradually add complexity as you understand the rules-based system.
You can create multiple agents with different configurations for different teams or use cases. Each channel can have one agent assigned.
3
Configure agent rules
Agents require explicit to know which to use. For each form you want the agent to access:
Create a new rule in the agent’s configuration
Describe when this form should be used
Use @Form Name to reference the specific form
Add any context-specific instructions
Example rule for a password reset form:
When a user requests a password reset or reports being locked out, use @Password Reset to create a ticket. Inform the user that IT will process their request within 2 hours.
Select which your agent should access. Unlike legacy Ravenna AI, agents only have access to knowledge you explicitly grant.You can also reference specific knowledge bases in using @Knowledge Base Name for targeted retrieval.
Navigate to the Connections section in your agent’s settings and select which should use this agent.
Once you assign an agent to a channel, the legacy Ravenna AI system for that channel automatically deactivates and is removed from the channel settings.
7
Test and refine
Send test messages to your channels to verify:
Agent responds appropriately to different request types
Correct are selected and populated
retrieval returns relevant information
behavior works as expected
Iterate on your based on test results. Review conversation logs to identify improvements.
Once you assign an agent to a , the legacy Ravenna AI system for that channel automatically deactivates and is removed from the channel settings. You cannot revert to the legacy system.
Legacy system removal
The legacy Ravenna AI configuration disappears from channel settings once an agent is assigned. All AI functionality for that channel now operates through the agent’s rules-based system.
Multiple agents
You can create multiple agents with different configurations for different teams, use cases, or channels. Each channel can have one agent assigned, but agents can be deployed to multiple channels.
Ongoing refinement
Monitor agent performance through conversation logs and feedback tracking. Continuously refine , , and based on actual usage patterns.
Agents do not automatically have access to all resources in your workspace. You must explicitly grant access to:
via @ mentions in
via the knowledge configuration
for ticket classification
and integrations via @ mentions in rules
Rules-based power
The system allows you to define sophisticated behavior patterns. Each rule can:
Reference multiple resources using @ mentions
Include conditional logic using natural language
Specify exact workflows for different scenarios
Define escalation criteria and processes
One agent per channel
Each can have one agent assigned, but you can create multiple agents for different teams or use cases. Deploy the same agent to multiple channels or use different agents for specialized teams.