Data Flows

Using generative AI in a business environment requires not just powerful tools, but above all trust. At Intric, transparency about how your data is handled is a cornerstone. We make it easy for your organization to ensure compliance and understand exactly where information goes.

This article provides an overview of how the Intric platform handles data, which actors are involved, and the principles we follow.

Our core principles for data handling

Our security work rests on four main principles designed to protect business secrets and personal data:

1. No training on your data: Intric never uses customer data (prompts, uploaded files, or chats) to train our own models. We also ensure through agreements that the sub-processors we offer do not use your data for model training.

2. Data minimization: We share only the information that is absolutely necessary to perform a specific task. If a tool or sub-processor is used, only relevant context is sent — never your entire database.

3. Data retention control: You control how long history in your assistants is stored, using dynamic data retention policies at the assistant level. Intric has agreements that guarantee zero data retention on all communication with sub-processors that deliver language models.

4. Your data, your control: As a customer, you own all data you create and upload to the platform. You control which AI models and external tools are available to your users.

The articles below clearly describe how data flows between Intric’s infrastructure and the tools and sub-processors you choose to use for your organization.