Sixgill Reveals Blockchain-Enforced Data Authenticity Platform

Sixgill, LLC, a provider of data automation and authenticity products and services, is offering Sixgill Integrity 1.0 for blockchain-enforced data authenticity.

Sixgill Integrity fulfills the critical enterprise need for end-to-end, real-time data authenticity assurance with robust capabilities to monitor and guarantee the veracity of any data stream, including today’s sensors emitting time-series data in any form.

Integrity provides organizations with absolute assurance that the data they create, transmit, process, act on, and store remains unchanged and tamperproof throughout its lifecycle.

In short, Integrity ensures that organizations – including their stakeholders, regulators, clients and others – can truly trust their data, particularly for high-stakes data automation applications.

Integrity ensures that organizations will benefit from the unparalleled security, transparency and immutability of private and public blockchain networks, while using off-chain capabilities for storing, processing, verifying, and safely operationalizing vast amounts of data.

Use cases for Sixgill’s new blockchain-secured data authenticity solution span a wide range of industries and needs, including:

  • Healthcare: Permanent auditability, traceability and certainty required for regulatory-grade medical and clinical trial data records
  • Supply Chain: Immutable data evidence of authenticity of goods origin and permanent traceability to originating data source(s)
  • FinTech: Unalterable transaction records for permanent audit trails
  • Utilities: Backbone data integrity for widely distributed infrastructures enabling centrally managed, system-wide programmatic actions triggered by device, data, and contextual rules for operating on data truth
  • Insurance: Verified data lifecycle authenticity from smart devices, smart homes, sensor-intensive vehicles, smart buildings, etc. for rate setting and claim settling
  • Video Surveillance: Permanent data immutability and auditability for…

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