What are the benefits of using Port's managed AI infrastructure?

Zero setup: Works immediately with no configuration required. Automatic updates: Always access to the latest model versions. Enterprise security: Your data is processed securely and not stored. No data training: We never train models on your data. Reliable performance: Optimized for Port's AI features. This is the recommended approach for most organizations as it provides the best balance of security, performance, and ease of use.

When should I consider bringing my own LLM provider?

Consider bringing your own LLM provider when you need: Enhanced data privacy: Keep AI processing within your own infrastructure. Compliance requirements: Meet specific regulatory or organizational requirements. Custom models: Define custom configuration on models not available through Port's managed infrastructure. Integration requirements: Connect with existing AI infrastructure.

How does data handling differ between Port's managed infrastructure and bring your own LLM?

Port's Managed Infrastructure: Data is processed within Port's secure cloud infrastructure. Your data is not used for model training. Complete logical separation between different customers' data. Data processing occurs within Port's controlled environment. Bring Your Own LLM: Data is processed by your chosen LLM provider. You control where and how your data is processed. Must comply with your provider's data handling policies. Port still retain interaction data for operational purposes. Detailed Information: How is my data processed by LLM providers? - How your data is processed by AI models. Does Port still retain AI interaction data when using bring-your-own LLM? - Data handling with custom LLM providers. Data privacy and retention - What data we store and why.

What security controls apply when using my own LLM provider?

When using your own LLM provider, you maintain the same security controls as Port's managed infrastructure: RBAC compliance: Port AI still respects your organization's access controls. Data governance: All interactions respect your configured data access policies. Audit trail: AI interactions are still logged and trackable. Permission inheritance: Port AI cannot access data you don't have permission to view. Additional considerations: You're responsible for your LLM provider's security measures. Ensure your provider meets your compliance requirements. Monitor your provider's data handling practices. Detailed Information: Data access and permissions - How AI respects your organization's access controls. Compliance and security standards - Integration with compliance requirements.

Can I opt out of data storage when using my own LLM provider?

Yes, you can opt out of data storage even when using your own LLM provider. However, there are important considerations: What you can opt out of: 30-day interaction data storage by Port. Port's operational data retention. Impact of opting out: May impact Port's ability to provide support and troubleshoot issues. Could affect AI feature performance and reliability. Detailed Information: Can I opt out of data storage? - How to opt out of data storage. Does Port still retain AI interaction data when using bring-your-own LLM? - Data handling with custom LLM providers.

How do I configure my own LLM providers?

To configure your own LLM providers: Configure your providers - Set up your preferred LLM providers using the Create or connect an LLM provider API endpoint. Select defaults - Once providers are configured, you can view and select default providers and models through the UI ( Builder → Organization Settings → AI tab) or via the Change default LLM provider and model API. Viewing and selecting defaults: Available in both UI and API. Adding new custom providers: Requires the API. This feature is designed for organizations with specific compliance, privacy, or integration requirements that cannot be met by Port's managed infrastructure.

What happens to my existing AI interactions when I switch LLM providers?

When you switch LLM providers: Existing AI invocations: All previous interactions remain accessible and unchanged. New interactions: Will use your newly configured provider. Data continuity: No data is lost during the transition. Performance: Response times and capabilities may change based on your new provider. Important considerations: Test your new provider configuration thoroughly. Monitor performance and adjust settings as needed. Ensure your new provider meets your security and compliance requirements.

LLM provider management

Manage and configure the Large Language Model (LLM) providers that power all AI interactions in Port. This feature gives you control over which AI models are used across Port AI Assistant, AI Agents, and other AI-powered features.

LLM approach overview

Port offers two approaches for AI model usage:

Port's managed AI infrastructure (default)

Port provides state-of-the-art LLMs through our secured cloud infrastructure by default:

No data training: We never train models on your data
Enterprise security: Your data is processed securely and not stored
Automatic updates: Always access to the latest model versions
Zero setup: Works immediately with no configuration required

Learn more about our data controls and security measures.

Bring your own LLM

For organizations requiring additional control, Port also supports configuring your own LLM providers:

Data privacy: Keep AI processing within your own infrastructure
Compliance: Meet specific regulatory or organizational requirements

Supported LLMs and providers

Port supports the following LLM providers and models:

Provider	Supported models
OpenAI	`gpt-5`
Anthropic	`claude-haiku-4-5-20251001`, `claude-sonnet-4-20250514`, `claude-sonnet-4-5-20250929`, `claude-sonnet-4-6`, `claude-sonnet-5`, `claude-opus-4-5-20251101`, `claude-opus-4-6`
Azure OpenAI	`gpt-5`
Azure Anthropic	`claude-haiku-4-5-20251001`, `claude-sonnet-4-20250514`, `claude-sonnet-4-5-20250929`, `claude-sonnet-4-6`, `claude-sonnet-5`, `claude-opus-4-5-20251101`, `claude-opus-4-6`
AWS Bedrock	`claude-haiku-4-5-20251001`, `claude-sonnet-4-20250514`, `claude-sonnet-4-5-20250929`, `claude-sonnet-4-6`, `claude-sonnet-5`, `claude-opus-4-5-20251101`, `claude-opus-4-6`
Vertex Gemini (`vertex-gemini`)	You choose the model names. See the Vertex Gemini setup guide.
Vertex Anthropic (`vertex-anthropic`)	You choose the model names. See the Vertex Anthropic setup guide.
OpenAI compatible (`openai-compatible`)	You choose the model names. See the OpenAI compatible setup guide for a full walkthrough using LiteLLM as the example gateway, or use the Create or connect an LLM provider API for the exact JSON schema.

Default models

Port AI leverages gpt-5 and claude-sonnet-4-20250514 by default when no custom provider is configured.

How this affects Port AI features

All Port AI features rely on the configured default providers. When working directly with the API, you can even select which provider and model to use for specific requests.

LLM approach overview​

Port's managed AI infrastructure (default)​

Bring your own LLM​

Supported LLMs and providers​

How this affects Port AI features​

FAQ​

LLM approach overview

Port's managed AI infrastructure (default)

Bring your own LLM

Supported LLMs and providers

How this affects Port AI features

FAQ