Science relies on good data. In the current scientific system, data is easily falsified, tampered with, or AI generated resulting in scientists not being able to rely on or use that data. If they could trust data, science could be more collaborative leading to more meaningful outcomes. This will continue to become more pronounced as scientific research becomes conducted more and more through machine-to-machine processes driven by AI.


Causality Network solves this fundamental problem of verifying the authenticity of data by integrating secure enclave signatures from IoT devices with zK. This allows both scientists and machines to trust one another through immutable audit trails and conduct science more effectively through onchain recordings from the source where it was generated. This creates transparency in good data, solving a fundamental need in all of science.