Skip to main content

STRM Privacy

STRM Privacy is a privacy-focused data processing platform, that ensures that collected data from a source is of a strictly defined shape and content (the Data Contract), and that it is compliant with all well known privacy regulations, such as GDPR. We strive to help you collect customer data in real-time or process data in batch with privacy and usability built-in.

You can consume data through multiple channels and use it for analytics, data science, machine learning, or store it in your data lake. If you'd like to jump right in:

Common use cases

As STRM Privacy supports both streaming and batch data pipelines, any use case can be enabled with our data processing platform. Some examples of use cases:

  • E-Commerce platform customer journey tracking. Decrease the time needed for your customers to find the product they are looking for by collecting data, respecting the customer's consent regarding data usage and still have the possibility to train Machine Learning models to assist the customer in their product journey.
  • App usage data. Smartphone applications collecting data might contain sensitive identifiers that can be traced back to individuals. The app data can still be collected, only if the consent that is often an opt-out approach is provided. With STRM Privacy you can collect data, ensure that the sensitive data is protected while respecting the consent of the user.
  • Medical data. With e-Health arising, data privacy becomes even more important than it already was in healthcare. For data analytics purposes, our platform can assist in ensuring that patient data stays secure, and that only specific employees get access to specific data.
  • Structure data privacy throughout your organization and enforce ownership, by purpose binding data throughout your ecosystem. Privacy is hard. What STRM Privacy is all about, is making it as easy as possible to put privacy policies in operation. With STRM Privacy, you use a clear and scalable process that uses the privacy policies you already have, and make sure the agreements made there, are enforced on all data flowing through data pipelines.
  • Safe data transfer with third parties. When you transfer your data to third parties the data moves, but the liability does not. Because of this, there is great reluctance around sharing your sensitive data. This is a shame, as there is a lot of value in collaboration, e.g. in research and in product development. STRM Privacy allows you to set clear conditions between the parties involved in the data sharing, and allows you to perform audits, if you need to show the correct measures are put in place.
  • Privacy-transformed data as base for machine learning models and analytics. In the end, machine learning is statistics on large scale data systems. Hence, often personal data is not required for good result, what matters is the underlying distribution of the data. Using STRM Privacy streams as the basis for your models, you keep the links within your data intact while discarding the personal aspect of it.
  • Your use case? Reach out to us and discuss your use case and see how STRM Privacy could help you streamline your the challenge of processing privacy-sensitive data.

Support

Require assistance? Reach out to us! We’re happy to help you, and are always looking for ways to improve our documentation.

Please see our contact page for ways to reach out to us, whenever you’re facing an issue.