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Overview

Last updated Aug 12, 2025

Use of customer data with Context Grounding

Purposes

We process the information used with our services for the following purposes:

  • Provide our services
  • Machine learning and product enhancement and development
  • Personalization of services and content

Provide our services

We process the indicated search, indexing instructions and data format specified by the user at design time to deliver our services: ingesting those data and querying over them to provide R.A.G. (retrieval-augmented generation) for Generative AI features at UiPath.

The purpose of using Context Grounding is to retrieve relevant information and use it as context to prompts that are executed by the models selected by the customer. For details regarding Context Grounding functionalities, refer to the Context Grounding documentation in the Automation Cloud user guide.

We process telemetry data such as document data, index data, and cloud account to make sure our platforms operate smoothly and to optimize the user experience based on the feedback and usage patterns we observe.

We use data analytics to measure and evaluate the performance of our services. We process account information such as cloud organization, tenant, and user IDs (emails) to provide you with access to the services and to secure your account. We may process data that you send to us for support or as necessary for troubleshooting issues in accordance with our Support teams.

Data storage

Ingested data and queries are stored when using this product as selected by you and in accordance with our Data Residency page, available in the Automation Cloud admin guide.

Integration with generative AI services

  1. Context Grounding passes relevant information as context to the models selected and used by the customers.
  2. All Context Grounding traffic to third party models goes through the AI Trust Layer if the models used are UiPath managed models.
  3. Context Grounding interacts with embedded models to create vector representation of supported data formats. It stores these data and vectors in a vector database.
  4. Through Autopilot for Everyone, UiPath Agents, and the UiPath GenAI activities, you can query these documents/vectors to find relevant information and pass it to an LLM of your choice.

Safeguards

We follow the standard policies for the AI Trust Layer:

  1. Customer data is deleted at contract termination or upon request.
  2. Customer data is encrypted. Access is strictly limited, and any access is logged and audited.
  3. We apply the following retention policy.
  4. You can export data from the AI Trust Layer Audit tab.

Opt-out mechanism

You can disable the input and output prompts saving mechanism using the AI Trust Layer policy, as described in the Managing AI Trust Layer documentation.

  • Use of customer data with Context Grounding
  • Purposes
  • Provide our services
  • Data storage
  • Integration with generative AI services
  • Safeguards
  • Opt-out mechanism

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