Model selection and management
Last updated: July 20, 2026
Who can use this feature
Supported on Enterprise plans
Org admins and IT admins are able to select and manage models via AI Studio. .

Model selection overview
With model selection you can choose the right AI models for defined agent use cases across your org, while managing them through a unified governance layer — ensuring confidence in model choice, routing, and compliance enforcement. For technical configuration details, see our dev docs.
How to add external models

From AI Studio navigate to Models & Guardrails > Models > +Add model to get started.


Once you’ve launched the modal for adding a model you will be taken through various steps where you will need to add credentials from your model provider. Please take a look at our dev docs for more details here.
Once you’ve added your model provider information, you can select who has access to use this model when building agents. You can grant access to All teams which will give anyone with builder access the ability to leverage that model when building agents. To restrict access to specific groups, select Specific teams and then add the team(s) that should have access to this model.
Managing Models

Once you’ve added a model you’ll see it appear in the list on the page where you’ll be able to:
See the Model name and Provider of the models you have connected
See the Health of the model
Healthy - The model is responding correctly and credentials are valid
Unhealthy - The model is not responding. Check credentials and provider status
Select any model in the Models list to view detailed information:
Health status: Current health state (Healthy or Unhealthy)
Last checked: Timestamp of the most recent health check
Model details: Provider, model name, and model ID
See who added the model to AI Studio and when

Select the three dot icon to the right of a model to Delete the model which will automatically remove it from your agents. For full details about configuring external models please visit our dev docs.
Best practices
Organizing models
Use clear naming conventions
Include purpose in display name: "Palmyra X5 - Customer Support"
Add environment indicators: "Claude - Production" vs "Claude - Testing"
Indicate department if team-specific: "GPT-4 - Finance Team"
Group by use case
Assign cost-effective models for high-volume, routine tasks
Reserve advanced models for complex reasoning or specialized needs
Keep experimental/testing models restricted to specific teams
Managing team access
Start restrictive, expand as needed
Initially grant access to specific teams
Monitor usage and costs
Expand to "All Teams" once confident in the use case
Align access with capability
Give specialized models (e.g., financial, medical) only to relevant teams
Ensure teams have training on model capabilities before granting access
Regular audits
Review team access quarterly
Remove access for models no longer needed
Update access when team members change
Credential management
Security best practices
Use dedicated service accounts, not personal credentials
Rotate credentials on a regular schedule
Document credential ownership and renewal dates
Store backup credentials securely outside AI Studio
Credential reuse
Use the same credentials across multiple models from the same provider
Reduces management overhead
Easier to rotate when needed
Troubleshooting
Model shows as unhealthy
If your model shows an unhealthy status:
Need info here
Potential causes to check:
Credentials may have expired
Provider service may be experiencing downtime
Network connectivity issues
Model may have been deprecated by provider
Regional restrictions or availability issues
Model doesn't appear when building agents
If you can't see a model when building an agent, check:
1. Team access restriction
Check if the model is assigned to "Specific teams"
Verify you're a member of an assigned team
Contact your admin to request access if needed
2. Model health issue
Check if the model shows as "Unhealthy" in the models list
Contact your admin to resolve connection issues
3. Permissions
Verify you have builder access in AI Studio
Confirm your role permissions with your admin if needed
Permission errors when adding models
Error: "You don't have permission to add models"
Solution: Contact your org admin, IT admin, or user with AI Studio full access role to:
Grant you appropriate permissions, or
Add the model on your behalf
Credential errors
Error: "Invalid credentials" or "Authentication failed"
Solutions:
Verify credentials are copied correctly with no extra spaces
Check that credentials are still valid in your provider account
Confirm the AWS region matches your model deployment region
For Role ARN access, verify the role has necessary permissions
Try creating new credentials from your provider
Still having issues?
Check your provider's service status page
Review provider documentation for credential requirements
Contact WRITER support with error messages and model details
FAQs
What providers are supported?
Currently supported providers:
AWS Bedrock: Fully supported
Hugging Face: Coming soon
Nvidia: Coming soon
Can I use the same credentials for multiple models from the same provider?
Yes! When configuring a model, choose credentials you've already configured for that provider from the Credentials name list in the setup modal.
Benefits:
Simpler credential management
Easier credential rotation
Consistent access patterns
How do I know which model to choose for my use case?
Consider these factors:
For general tasks: Use balanced models like Palmyra X5
For complex reasoning: Use advanced models like Palmyra X5 Thinking
For cost efficiency: Start with smaller models and upgrade if needed
For specialized domains: Use industry-specific models (Palmyra Med, Palmyra Fin)
For vision tasks: Use multimodal models like Palmyra Vision
💡 Tip: Consult our dev docs for detailed model comparisons and recommendations.
Do I need to configure credentials for WRITER models?
No. WRITER models (Palmyra family) are pre-configured and immediately available. You only need to configure credentials for external provider models.
Do I need separate credentials for each team?
No. Credentials are configured at the model level, not the team level. One set of credentials can be:
Used by multiple models from the same provider
Accessed by all teams that have access to those models
Managed centrally by admins
Team access controls WHO can use the model, not the credentials themselves.
What happens if I'm not on a team with access to a specific model?
If a model is restricted to specific teams and you're not a member:
You won't see the model when building agents
You can request access from your admin
Your admin can either:
Add you to an allowed team, or
Add your team to the model's access list
Can team members see the credentials?
No. Credentials are encrypted and only visible to users who configure them (admins). Team members with access can use the models but never see the underlying credentials.