Privacy is a fundamental component of Moore Development’s practices, and this Privacy Policy is reflective of such. This Privacy Policy explains how your information (i.e. data) is collected, used, disclosed, transferred, and stored. Moore Development recommends that all users of any and/or all services provided by Moore Development are familiar with this Privacy Policy.
Personal information is defined as data that may be used to identify or contact a single entity (i.e. a person).
In the event where personal information is collected by Moore Development, the information collected will never be intentionally disclosed and/or shared with parties other than that of Moore Development and/or its affiliates. You shall never be required to provide personal information, if requested, but, in the event of denial, the products or services requesting the information may not be able to function properly, or at all.
Personal information shall never be the subject or target of any irresponsible activities. Such activities include, but are not limited to, selling for profit, trivial analysis, and advertising purposes. Moore Development wants to assure the protection of your privacy, and does not want to consume your personal information for any purposes other than to provide a satisfactory service.
Moore Development takes multiple measures to ensure the security of your personal information. Online services protect this personal information during transit using encryption technology such as TLS, and/or encryption. When your personal information is directly stored by Moore Development, albeit rare, as data is usually stored by Apple Inc., we employ encryption throughout.
While Moore Development takes a number of steps to ensure security of your personal data, there may be certain cases where such measures do not perform as expected. In such an event (breach), Moore Development does not assume responsibility for any lost and/or stolen personal data, but will attempt to recover the lost/stolen data and continue to protect your personal information.
There are many cases where Moore Development uses TestFlight to test new and/or existing products. In such cases, a discrete amount of personal information must be gathered to begin testing the product, namely, a user’s email address. Any personal information will remain private and is only to be used for testing-related purposes.
Pre-release products, and the testing of such products, should be inclusive of acknowledgement that the product in testing may not perform as expected. The behavior of pre-release products is subject to change at any time, and the product should not be relied upon. Collection of information related to the testing of prerelease products will never be shared or used for purposes other than that of internal development.
While many precautions are taken to ensure the security and privacy of your personal information/data, prerelease products pose potential implications which may infringe on the privacy policy of Moore Development. Such is to say that, without limitation (as permitted by the Laws of the Province of Ontario and the Laws of Canada applicable therein, excluding its conflicts of law provisions), Moore Development is not responsible for any damage(s) related to prerelease products. This case shall only apply for the testing of Moore Development’s prerelease products and/or services.
Couplet is a service which is both completely private, and fully dependent on the user’s iCloud account. Moore Development does not have access to any records, data, assets, private information, etc (collectively referred to as “Content”), aside from usage statistics. To remain in-line with Moore Development’s overall policy with respect to privacy, privacy shall never be infringed upon while interacting with, using, storing data with, or other operations related to Couplet.
Sensibility is an iMessage app which enables a user to communicate sentiment for text-based messages. The application performs local, on-device machine learning in order to make personalized sentiment inferences that have a high degree of accuracy. All machine learning data remains on-device at all times, and is never sent, received, or transmitted. Personal information is not collected, but instead used to train a local high-speed accuracy model. Connections between lemmatized sets of vocabulary preserve model fluency and stability, while maintaining user-privacy.