AI Data Security: How youleap Protects Your Business Information

Last updated: November 2026

Your price lists, agreements and order history are sensitive commercial information. When connecting this information to AI tools, it is important to understand who can access it, which services process it and the boundaries of each connection. These are questions that need answers before introducing a new service into your business.

What we did

youleap is built on Amazon Web Services cloud infrastructure and uses Kubernetes to run and manage service components. The system includes separation between customer environments and data, and access controls for resources.

Amazon Bedrock is an AWS service for running AI models. Each AI service, transcription service or integration requires consideration of its specific processing path and providers.

Access to protected business information takes place through the service interfaces, after user authentication and in accordance with the permissions active in the relevant service. The scope of access controls depends on the product, capability and configuration deployed for the customer.

Access permissions also apply to AI

In youleap, each sales representative accesses information according to their assigned customers and the permissions set by the system administrator. AI tools use only information the representative is authorized to see and do not extend their access to additional information.

Why we did it

Business information is more than a collection of files. It includes price lists, agreements, customers and order histories built up over time. Using this information for sales, service or AI processing requires clear boundaries: which business it belongs to, who may see it and which process uses it.

Separation between customer environments and data, together with the access controls active in the service, addresses this need. The rationale is to enable work with information within a defined framework, according to the product and configuration deployed for the customer.

When using models, it is also important to distinguish processing a business request from using information for training. According to AWS, Amazon Bedrock inputs and outputs are not used to train foundation models and are not shared with model providers. This policy applies to Bedrock only, not automatically to transcription or additional services. It is not a promise of zero data retention. AWS documentation

How this helps your business

Separation between customer environments and data helps reduce the risk of exposure between customers. Active access controls add boundaries to work with protected business information, according to the product, capability and configuration deployed for you.

For sales and service teams, the value is being able to work with business information through the service interfaces and in accordance with the permissions active in the service. For example, when preparing a representative for a meeting or handling a customer inquiry, information should support the task without turning the user into an infrastructure administrator.

For business management, this architecture provides a clear basis for assessing the service: separation between customer environments and data, authenticated access to protected business information, and the access controls active in the relevant service. It does not guarantee complete protection or mean that the entire system is disconnected from the internet. Security depends on the full set of safeguards and their suitability for your service, alongside the agreement and data processing addendum.

Questions about data security