At ZyLAB we develop innovative solutions that always go beyond what our competitors do, using new technology to seek higher levels of automation, completeness, speed and ease of use. This originates from the DNA of our founders. Today we work closely together with Universities around the world and have their researchers work in our R&D department.
And go even further in combining the various dimensions? No matter the type of case or investigation you need to ask the obvious questions: What, Why, Where, When, Who, etc.
What: Topic modeling
Who: Community detection
Where: Geo mapping
Why: Sentiment and emotion mining
When: Time lines
but also the:
What–when Topic Rivers
Who-Why Sentiment mining per person
ZyLAB Assisted Review (ZAR) – also known as Computer Assisted Review (CAR) or Predictive Coding – uses a series of algorithms to search and sort documents relevant for data investigation or eDiscovery.
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Based on large data sets train the machines, this way we can support automation of the best practice use cases.
Different types of unstructured data can surface during case, which means different means of extraction are required. ZyLAB ONE is compatible with almost every type of data, and can extract meaningful information easily.
eDiscovery is a global and often multilingual practice, which is why ZyLAB is built to support and accomodate a vast amount of languages.
Based on our extensive experience we can translate your need for automation to the use of AI, making your processes both faster and more consistent.