Configuring LLMs

Connect your own LLM subscriptions or custom models to Automation Suite through the AI Trust Layer LLM configurations tab, using Integration Service connections to supported providers.

Note:

LLM configurations is available on the following licensing plans:

• Flex: Advanced Platform, Flex Standard Platform.
• Unified Pricing: Enterprise Platform, Standard Platform, Basic Platform

The LLM configurations tab allows you to integrate your existing AI subscriptions while maintaining the governance framework provided by UiPath. You can:

• Replace UiPath LLM subscriptions: Replace UiPath-managed subscriptions with your own, provided they match the same model family and version already supported by the UiPath product. This allows for seamless swapping of UiPath-managed models with your subscribed models.
• Add your own LLM: Use any LLM that meets the product's compatibility criteria. To ensure smooth integration, your chosen LLM must pass a series of tests initiated through a probe call before it can be used within the UiPath ecosystem.

Configuring LLMs preserves most of the governance benefits of the AI Trust Layer, including policy enforcement via Automation Ops and detailed audit logs.

When leveraging the option to use your own LLM or subscription, keep the following points in mind:

• Compatibility requirements: Your chosen LLM or subscription must align with the model family and version currently supported by the UiPath product.
• Setup: Make sure you properly configure and maintain all required LLMs in the custom setup. If any component is missing, outdated, or incorrectly configured, your custom setup may cease to function.
• Cost-saving: If your custom LLM setup is complete, correct, and meets all necessary requirements, you may be eligible for a Reduced Consumption Rate.

Setting up an LLM connection

LLM connections rely on Integration Service to establish the connection to your own models. You can create connections to the following providers:

• Amazon Web Services
• Azure Open AI
• Google Vertex
• Open AI
• Open AI V1 Compliant LLM – Use this option to connect to any LLM provider whose API follows the OpenAI V1 standard. For details, refer to the OpenAI V1 Compliant LLM connector documentation.

Note:

To configure Anthropic Claude models, use the Amazon Web Services connector in Integration Service. A direct Anthropic connector is not supported in Automation Suite.

To set up a new connection, follow these steps:

1. Create the Integration Service connection

1. In Integration Service, create a connection to your LLM provider.
2. Choose the folder where the connection will be stored.
3. Complete the authentication as required by the selected connector.
   Note:

   The folder you choose controls both security and visibility. To prevent unauthorized access, create the Integration Service connection in a private, non-shared folder. However, note that model visibility is determined by access to this folder. If an admin does not have access to it, the associated model configuration will not appear in the list.

2. Add a new LLM configuration

1. Navigate to Admin > AI Trust Layer > LLM configurations.
2. Select the Tenant.
3. Select Add configuration.
4. Choose the Product (for example, Agents) and Feature (for example, Design, Evaluate & Deploy).
5. Select the Connections Folder.

3. Configure the model

In the Model Configuration section, fill in the following fields:

• LLM Name – This field supports two configuration options, depending on your use case:
  • Select a model from the list – Choosing a model from the predefined list replaces the UiPath-managed LLM subscription with your own subscription for that same model. This scenario is referred to as Bring Your Own Subscription (BYOS).
  • Add custom alias – Entering a custom name allows you to configure a model that is not included in the predefined list of recommended models for that product. This scenario is referred to as Bring Your Own Model (BYOM). Refer to the table in Configuring LLMs for your product to learn which models are required for each product and feature set.
    Note:

    The Add a custom alias option is available only for products that support custom models. To learn which products support custom models, refer to the table below.

• API Type – The API endpoint supported by the LLM (for example, Open AI Chat Completions). This must match the endpoint exposed by your provider.
• Connector – The Integration Service connector (for example, Microsoft Azure OpenAI, Amazon Web Services).
  • If you enabled custom AI gateways during installation, you can also select Create custom connector to use a predefined template through Connector Builder. For details, refer to Using connector templates.
• Connection – The specific Integration Service connection created earlier. If no connection is available, create one in Integration Service.
• LLM identifier – The model identifier exactly as it appears in your LLM subscription.
  • For Azure-hosted models: enter the model deployment name/identifier.
  • For AWS Bedrock cross-region inference: enter the inference profile ID. You must prepend the model ID with your region code, for example: eu.anthropic.claude-3-5-sonnet-20240620-v1:0.
  • For other providers: use the model name as defined in your subscription.

4. Validate and save

1. Select Test configuration to verify that the endpoint is reachable.
   • The platform validates the connectivity.
   • Ensuring the correct model is configured remains your responsibility.
2. If the validation is successful, select Save to activate the configuration.

Managing existing LLM connections

You can perform the following actions on your existing connections:

• Check status – Verify the status of your Integration Service connection. This action ensures that the connection is active and functioning correctly.
• Edit – Modify any parameters of your existing connection.
• Disable – Temporarily suspend the connection. When disabled, the connection remains visible in your list but doesn't route any calls. You can re-enable the connection when needed.
• Delete – Permanently remove the connection from your system. This action disables the connection and removes it from your list.

Configuring LLMs for your product

Each product supports specific large language models (LLMs) and versions. Use the table below to identify the supported models and versions for your product.

You can connect your own LLM using one of the following providers: Amazon Web Services, Google Vertex, Microsoft Azure OpenAI, or OpenAI V1 Compliant. Follow the steps outlined in the previous section to create a connection.

Note:

File support: Some product features rely on the configured LLM endpoint to process uploaded files. When using custom LLM configurations, support for file formats depends on the provider, model family, model version, and API Type. Verify that the selected model supports the required file formats before enabling file-based features. For product-specific requirements, refer to the relevant product documentation — for example, Analyze Files for Agents.

The number of models you must configure depends on the product and feature:

• For features with a selectable model — where you choose which model to use — you can configure one or more models; unconfigured models continue to use UiPath-managed subscriptions.
• For features with a fixed model set — where the feature uses a predetermined set of models — all models must be configured for the feature to work; partial configuration is not valid.

Product	Supports custom models	Feature	LLM provider	Version
Agents 1	Yes	Design, Evaluate & Deploy	Anthropic	anthropic.claude-3.5-sonnet-20240620-v1:0 anthropic.claude-3.5-sonnet-20241022-v2:0 anthropic.claude-3.7-sonnet-20250219-v1:0 anthropic.claude-3-haiku-20240307-v1:0
			Google	gemini-2.5-pro
				gemini-2.5-flash
			OpenAI	gpt-4o-2024-05-13 gpt-4o-2024-08-06 gpt-4o-2024-11-20 gpt-4o-mini-2025-04-14 gpt-4o-mini-2024-07-18
Autopilot	No	Generation	Google	gemini-2.5-flash-lite gemini-2.5-flash gemini-2.5-pro gemini-embedding-001
		Chat	Anthropic	anthropic.claude-haiku-4-5-20251001-v1:0 anthropic.claude-sonnet-4-6 anthropic.claude-opus-4-6-v1
			Google	gemini-2.5-pro gemini-2.5-flash gemini-3-flash-preview gemini-3-pro-preview gemini-3.1-pro-preview
Autopilot for everyone	No	Chat	Anthropic	anthropic.claude-3.5-sonnet-20240620-v1:0 anthropic.claude-3.7-sonnet-20250219-v1:0
			OpenAI	gpt-4o-mini-2024-07-18
Coded agents	Yes	Call LLM	Anthropic	anthropic.claude-3.5-sonnet-20240620-v1:0 anthropic.claude-3.5-sonnet-20241022-v2:0 anthropic.claude-3.7-sonnet-20250219-v1:0 anthropic.claude-3-haiku-20240307-v1:0
			Gemini	gemini-1.5-pro-001 gemini-2.0-flash-001
			OpenAI	gpt-4o-2024-05-13 gpt-4o-2024-08-06 gpt-4o-2024-11-20 gpt-4o-mini-2024-07-18 o3-mini-2025-01-31
Context Grounding	No	Embeddings	Gemini	gemini-embedding-001
			OpenAI	text-embedding-3-large
		Advanced ingestion	Gemini	gemini-2.5-flash
		DeepRAG	Gemini	gemini-2.5-flash
		Batch Transform	Gemini	gemini-2.5-flash gemini-2.5-flash-lite
		Batch Transform with Web Search	Gemini	gemini-2.5-flash gemini-2.5-flash-lite
GenAI Activities	Yes	Build, Test & Deploy	Anthropic	anthropic.claude-3.5-sonnet-20241022-v2:0 anthropic.claude-3.7-sonnet-20250219-v1:0
			Gemini	gemini-2.5-pro gemini-2.5-flash
			OpenAI	gpt-5-2025-08-07 gpt-5-mini-2025-08-07 gpt-5-nano-2025-0807
Healing Agent	No	Workflow Recovery
			Google	gemini-2.5-pro gemini-2.5-flash
			OpenAI	gpt-4o-2024-08-06
UI Automation	No	ScreenPlay	Anthropic	anthropic.claude-sonnet-4-5-20250929-v1:0
			Google	gemini-2.5-flash
			OpenAI	gpt-4.1-mini-2025-04-14 gpt-4.1-2025-04-14 gpt-5-2025-08-07 gpt-5-mini-2025-08-07 computer-use-preview-2025-03-11
		Semantic selectors	Google	gemini-2.5-flash
Test Manager	No	Autopilot Autopilot Search Find Obsolete Tests Generate Test Cases Import Test Cases Generate Reports Requirement Evaluation	Anthropic	anthropic.claude-3.7-sonnet-20250219-v1:0 (to be replaced with anthropic.claude-4.5-sonnet in March 2026)
			Google	gemini-2.5-pro gemini-2.5-flash
			OpenAI	gpt-4o-2024-11-20

¹ Agents requirements:

• Ensure your LLM supports:
  • Tool (function) calling – The model must be able to call tools or functions during execution.
  • Disabling parallel tool calls – If supported by your provider, the model should offer the option to disable parallel tool calls.
• When using custom models, Agents default to a 4096 token limit regardless of the model's true capacity, since UiPath cannot infer token limits for customer-defined deployments.