Model selection and management | WRITER Knowledge Base

Model selection and management

Last updated 5 days ago

Who can use this feature

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:

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

Group by use case

Managing team access

Start restrictive, expand as needed

Align access with capability

Regular audits

Credential management

Security best practices

Credential reuse

Troubleshooting

Model shows as unhealthy

If your model shows an unhealthy status:

Potential causes to check:

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:

Credential errors

Error: "Invalid credentials" or "Authentication failed"

Solutions:

  1. Verify credentials are copied correctly with no extra spaces
  2. Check that credentials are still valid in your provider account
  3. Confirm the AWS region matches your model deployment region
  4. For Role ARN access, verify the role has necessary permissions
  5. Try creating new credentials from your provider

Still having issues?

FAQs

What providers are supported?

Currently supported providers:

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:

How do I know which model to choose for my use case?

Consider these factors:

💡 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:

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:

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.