iDenfy to Enable Biometric Onboarding for Medical Research Startup

iDenfy will be providing identity verification services for a blockchain start-up that specializes in medical research. Triall was founded in 2018, and is attempting to use blockchain technology to enable collaboration while making sure that clinical trials and data remain secure.

To that end, Triall is building an entire blockchain ecosystem to support clinical interactions. The tokenized system guarantees the integrity (and the auditability) of clinical data, and makes it easier to share that data with partners all over the world. In that regard, Triall’s ecosystem provides a secure and interoperable connection for scientists who are working remotely.

iDenfy, meanwhile, will be confirming the identities of those who register with the platform. The company offers an ID verification service that uses document recognition to make sure that an ID is authentic, and facial recognition to match the image on that document to its owner. The solution is compliant with all of the relevant Know Your Customer and Anti-Money Laundering regulations, which is crucial in a heavily regulated field like clinical research.

“Triall accelerate medical research by making clinical trials smarter, safer, and more efficient. It is an honor to be working with them, especially in the context of a global pandemic, which proved how important medical research is,” said iDenfy CEO Domantas Ciulde. “We look forward to the digital Triall ecosystem and will clear the obstacles they would face without us on the team.”

Triall is also creating its own utility token to facilitate transactions through its platform. The TRL token will essentially function as a virtual currency, and could be used for payment and as incentives for stakeholders in the platform.

iDenfy has picked up several new customers in the past few months, with Monneo, Paymento, and the sports betting site Sparlay standing as some of the recent additions to the client roster.

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(Originally posted on Mobile ID World)