AI providers list view that we can use for the workflow.

Enter API Key.

Create workflow with AI.

AI will auto execute workflow.

Select the LLM Provider in settings and choose the skill option as per the requirement.

You can manage 'Skill Types' in the recruitment configuration.

Set All Skill Types.

Click Digitize Document AI and then process Resume/CV to extract structured data.

View AI-generated Resume/CV analysis and then review skills, experience, and summary. Note tab with data.

Details tab with data.

Skills tab with data.

Now we select 'Skills from Job Position'.

Set Expected Skills in Job Position and then compare with applicant Resume/CV match.

View AI-generated Resume/CV analysis and then review skills, experience, and summary. Note tab with data.

Details tab with data.

Skills tab with data.

Go to the 'AI MCP'.

Create a new MCP server.

Method 1: Connect with the token URL.

Click on 'Regenerate URL Token'.

Copy URL.

Go to the 'Claude' -> Customization.

Go to the connectors, click add custom connector.

Add the MCP name, URL, and click 'Add'.

After connected it shows all details.

Method 2: Connect with OAuth.

Go to the connectors, click custom connector, add all details, and click 'Add'.

Click to connect.

After connected it shows all the details.

You can remove or disconnect as per requirements.

Technical details are shown in these tabs.

Generate instructions as per the requirement.

Define controlled access by specifying which models, operations (read, create, update, delete), and fields users or AI can interact with—ensuring data security and precise permission management.

You can restrict access for either all fields or only selected fields for a given model.

You can control which actions are permitted on a model, such as confirm, cancel etc ensuring users or AI can only perform specific operations as needed.

Click 'Generate Dashboard'.

Generate Dashboard form with options.

Chart tab with generate charts.

Dashboard view.

Click 'Generate Charts.'

Generate Charts form with options.

The AI Chat menu allows users to manage conversations with AI models.

Users can create a new AI chat session, assign or edit a session name, and select from multiple AI models. Previous chat histories are listed on the sidebar for easy reference.

Users can switch between multiple AI models directly from the chat interface. Available options include Google’s Gemini series and OpenAI’s ChatGPT series (from 4o to 5 nano).

Users can easily rename a chat session by clicking the session title, editing it, and saving the new name. Based on the user’s query, AI-generated outputs are displayed in multiple formats — List View, Kanban View, Graph View, or Pivot View.

Users can manage their chat history effortlessly by deleting unwanted chat sessions with a single click.

A confirmation popup appears when deleting a chat session, ensuring that users don’t accidentally remove important conversations.

The Chat Session List View provides a centralized overview of all AI chat sessions in Odoo. Each record displays key details such as session name, selected AI model (LLM provider), message count, chat status, timestamps for the last message, and creation date.

The Chat Session Form View displays detailed insights of an individual AI chat session. Admins can also access Debug Info for each message to review technical details, making this view ideal for analysis, troubleshooting, and audit purposes.

Create new projects.

You can drag and drop as per the requirement.

You can perform actions on the folder as needed.

When you delete a folder, it will remove the subfolder data along with it.

Chat session list with project hierarchy.

Chat project list view with project structure.

Project form view with sessions and child project.

Click the AI icon to open the mini chatbot popup window.

Click the chat dropdown to select an existing conversation or create a new chat.

Select your preferred AI model from the dropdown to switch between available models.

Click the expand icon to enlarge the chatbot window for a better view.

Click on the Odoo main menu and select AI Assistance to open the configuration settings.

Navigate to the Configuration menu and select LLM Providers to manage your AI models.

Select an LLM provider from the list to configure its reasoning effort level details.

Choose the desired Reasoning Effort level from the dropdown list to adjust the AI's cognitive depth.

View the active reasoning effort indicator in the AI chat response.

Open the Chat Sessions menu to view a list of all logged AI conversations and settings.

Click on Debug Info in the chat session form to review reasoning tokens and details.

AI response debug popup showing reasoning tokens and selected reasoning effort level.

Enable debug mode and click Show Query to view reasoning details in the chat response.

View the usage statistics including reasoning tokens and reasoning level in the debug query section.

Click the microphone icon to record your query.

Speak your query naturally, and the system instantly transcribes it for processing.

View the AI response within the mini popup window for quick interaction.

AI Chat requests to show all confirmed sale orders from the admin role.

Sales orders total count at the backend for the admin role.

AI gives the sales order list in the conversation.

Now we change access rights to users.

AI Chat requests to show all confirm sale orders.

AI gives the sales order list in the conversation as per the assigned role.

Sales orders total count at the backend as per the assigned role.

Now we change access rights to none.

AI Chat requests to show all confirmed sale orders, so AI will not give a list and display a message like below.

Odoo users, along with their login names and roles.

We have a custom-developed app, named the knowledge base system.

Articles list view with all articles.

The Marc Demo user is set up with access to view their own and public documents only.

AI Chat requests to view all available articles, so AI gives articles as per the assigned roles in a conversation.

Now we change access to the manager role.

AI Chat requests to view all available articles.

AI gives articles as per the assigned roles in a conversation.

You can enable Debug Mode from the configuration to view detailed AI response logs. From the chat session form view, clicking on Debug Info opens the AI Response Debug window, showing both Response Content and Debug Information (JSON) tabs.

Once Debug Mode is enabled, admins can access the Debug Information (JSON) tab showing detailed technical logs for LLM processing.

This screen displays details of the configured LLM provider, including model name, response style, and API key settings. Admin can define the provider API key, activate or set the default LLM, and manage the system prompt that guides AI behavior and accuracy.

This list view displays all available LLM models configured in Odoo, such as ChatGPT and Gemini versions. It is accessible only to admins and shows details like provider name, model code, default LLM status, and activation toggle for each AI model.

This view shows the AI Chat interface visible to users, featuring dark mode based on user preferences.

Click on the "Share" button to share the chat.

After that, the share link is generated. Copy the link.

Paste the copied link to open chat.

Click on the "Export Chat" button to export the chat.

You can import the exported chat using the "Import Chat" button.

Select chat from the wizard, and click "open".

Your chat is imported; you can continue the chat.

Click on pause icon to stop AI response.

It shows notification for it.

You can see cancelled chat in chat history also.

'Is cancelled' ticked in that chat.

Go to the 'AI Assistance'.

Click 'Let's do it'.

Select the model and click 'Continue'.

Enter your API key, and click 'Verify & Continue'.

It shows a success message after the verification.

Select the agent and click 'Continue'.

Select response style and complete setup.

You can start chatting now.

Select Always, Never, or Auto to control AI model view visibility.

Select OpenRouter and enter your OpenRouter API key to enable OpenRouter integration.

Browse and select from the wide range of AI models available through OpenRouter.

Configure your preferred OpenRouter model as the default provider for AI interactions.

Start chatting using your selected OpenRouter model seamlessly within the AI Chat interface.

Connect multiple AI providers, choose your preferred models, and control how AI interacts with your Odoo data. Define access rules to ensure AI only creates, updates, or archives records within permitted boundaries — keeping your system secure and compliant.

Fill in the required details to configure a new AI provider record.

Start conversation.

Set action views, add requirements, and select an AI model provider.

When attempting to update a record and update action is restricted in the system settings, the AI assistant does not perform the action. Instead, it displays a message similar to the example shown below.

If you attempt to update a record that is not restricted by system settings, the update will proceed. The system will present you with an option to review the change and either approve or reject it before it is finalized.

On approval, it will make changes.

Chatter history that was recorded with AI.

AI Write Request menu and list view.