Private and compliant
use and training
monetization
deployment
of all data types, AI and ML models.
THE CHALLENGE
Exchanging raw data exposes all parties to a variety of compromises, making privacy and monetization of information assets, like data and algorithms, a complex balancing act.
Company A encrypts and sends data to Company B
Company A allows data to be decrypted for use.
Company B decrypts data for use.
Company B negligently allows stray data to remain on servers against Terms of Use.
PROBLEMS ASSOCIATED WITH DECRYPTION:
Data exchange and use relies on good faith adherence to Legal Terms.
The data economy requires costly IT and security infrastructure.
Stray Data can be left behind after use, unsecured and vulnerable to counter-parties.
Aggregating data from various providers is expensive and complex.
Data de-identification reduces the value and training accuracy of data.
INGEST HISTORICALLY INACCESSIBLE DATA
Previously inaccessible data is easily licensed to make your models more accurate and less biased.
Easily gain insights from the data sets you need without time-consuming legal contracts.
GRANT INSIGHTS FROM DORMANT DATA
Monetize your data and bring new sources of profits straight to your bottom line
Collaborate freely without having to rely on good faith adherence to your terms of use.
ACCESS OUR WHITE PAPER
ACCESS OUR WHITE PAPER
UNLOCK NEW OPPORTUNITIES
Company A Encrypts data related to customer purchase histories. Company A wants to share only those data related to ice cream purchases.
Company B tries to run an algorithm that will calculate the pizza spend of customers represented in Company A’s data set, and is rejected.
Company B is allowed to run other algorithms related to ice cream, per Company A’s DRM.
Company A can allow another vendor to train against its customer data.
TripleBlind’s Third Party digital rights management offers control of your data while it’s being used by third parties.
This means both parties must provide cryptographic consent to every operation, effectively eliminating all counter-party data leak or abuse risk!
Privophy
Secure Search Encryption
Homomorphic Encryption
Private Set Interaction
Private Training
Model Fingerprinting
SMPC VS FHE
SMPC | FHE |
---|---|
Fast | Slow |
Future proof | May be cracked in the future |
Privophy™ supports non-linear operations, including comparisons | Only supports basic algebraic operations |
Requires all parties online | Operates offline |
All parties consent to each use | Doesn’t require consent of all parties for other uses |
Mathematical Digital Rights Management | No Digital Rights Management |
Interested in a product demo? We’d love to hear from you.