Data retention policy
At the end of the Contract, the Client may choose to retain its Client Data with Rydoo in accordance with the retention schedule set out in Rydoo’s Privacy Notice available on its website. If the Client does not wish to retain the data, it must notify Rydoo about such a decision either in the Termination Notice or at any time during the applicable retention period.
Data archiving and removal policy
At any time during the Contract term, upon Contract termination or during the applicable retention period, the Client may request erasure of all or part of the Client Data. The timeframe for completing the data erasure typically does not exceed thirty (30) days, provided that the Client supplies Rydoo with all necessary information regarding the scope of the requested export, whether the Client wishes to receive a copy of its data and confirmation on exporting such copy to Client’s own system. Any delay caused by incomplete or unclear instructions from the Client may extend this timeframe.
The Client acknowledges and agrees that, in any event, all Client Data will be deleted by Rydoo upon expiry of the applicable retention period. Following deletion of Client Data from the active systems, residual copies may remain in Rydoo’s backup systems for a period of up to six (6) months. Such backup copies shall not be accessible or used in the ordinary course of business. Any such data shall remain subject to the confidentiality and data protection obligations set out in the Contract until permanently deleted in accordance with Rydoo’s backup deletion cycle.
Data storage policy
Data is stored within the EU with ISO 27001 and ISO 9001 certified storage partners in accordance with the EU GDPR regulation. All data entered into our application is securely stored within Microsoft Azure data centres located in the EU and meets strict security requirements.
Data center location(s)
France, Sweden
Data hosting details
Cloud hosted
Data hosting company
Azure
App/service has sub-processors
yes
Guidelines for sub-processors
App/service uses large language models (LLM)
no