Our Technology

Removing the Barriers to Sharing Sensitive Data;
Applying Zero-Trust to Self-Service Analytics and ML.

Self-Governing Data Security

Simplifies Sharing, Using, Analyzing and Monetizing Raw Sensitive Data

Using Myngl Concordance, data owners control how and by whom their data can be used with “Need-to-Know” policies. 

Using simple web services, owners easily embed their “Need-to-Know” policies into every data element. 

Every cell of data becomes “Self-Governing” exclusively controlled by its owner.

Conventional Systems Assume Trust;
Myngl Assumes: With Data, Trust No One

Capabilities Needed by Business Teams Myngl Secure Analytic Containers Conventional Big Data Platforms Data Management Services
Aggregates raw data from multiple owners?
Decentralizes cell-level controls to data owners?
Securely commingles data for self-service analytics, ML?
Commingles raw sensitive data with Zero-Trust?
Simplifies direct data partnership, ecosystem formation?
Embeds owners Zero-Trust rules into every data cell?
Admins can override owner's security and governance policies?
Admins or users can directly extract raw data?

Myngl Uses a Simple 5-Step Workflow

Looking for Technical Documents?

The Zero-Trust sandbox makes it easy to analyze sensitive data without exposing it.

Analyzing commingled raw data in the sandbox is made easy with open source Zeppelin Notebooks, SQL, Python, TensorFlow and other powerful tools.

Data owners must agree and grant permission before analytic “apps” can operate against commingled raw data in the secure core within the Secure Analytic Container.

Myngl Concordance has a Hybrid Architecture

Combining cloud containers, microservices, Hadoop and Zero-Trust.


Highly Scalable

Open Source Analytics

Zero-Trust End-to-End

Easy to Pilot – Let’s Chat!