One of the highlights of the Heureka platform involves multi-layered intelligence gained from each installed endpoint. The first layer is a high-level dashboard tracking and displaying risk across all Heureka installed endpoints. The second layer reveals a deeper level of knowledge based on file-level details showing auto-classified risk or tags generated for regular expression searching on items such as intellectual property, GDPR privacy information, or unique patterns such as student id’s.
As beneficial as it is to be able to rapidly search and classify data enterprise-wide, our core philosophy revolves around the ability to share any gained intelligence with outside systems who may not only benefit but also potentially further enhance any shared knowledge. Heureka’s intelligence sharing takes on many forms from a simple, flat file CSV export for Tableau to an API with ServiceNow delivering Heureka’s automatic endpoint risk score. Deeper levels of intelligence sharing are achieved by exporting native files along with file-level tag information from Heureka to review platforms such as Relativity or iCONECT.
Below is an example of how Heureka’s shared intelligence can be interpreted using a visual analytics tool like Tableau. In this case, Heureka is providing file-level information for documents which can then be translated into file categories, counts, pii risk, overall risk cost, level of ROT (redundant/obsolete/trivial) as well as file volumes.
Another excellent example of shared intelligence can be seen in the Relativity dashboard shown below. In this example, early case assessment dashboards were built to help visualize information coming from Heureka’s imported documents. Custodian volume, file dates, file types, etc can easily be created for rapid visualization. Additionally, a Heureka Risk chart was added to show endpoint risk scores providing a quick view across all of the custodians.
Finally, taking this one step deeper, Heureka’s automatic classification tags were imported for each file. In Relativity’s review mode, a Heureka PII info pane (shown below) was built and added to the coding area giving a reviewer the ability to see if a document contains potentially sensitive information along with the type of information such as credit card, SSN, bank routing information or even GDPR related tags. Unique RegEx tags for privacy items such as student identification or intellectual property are also visible. Heureka’s “hit count” for each tag gives the reviewer an indication of how many instances are involved for more accurate document coding.
These are just a few examples demonstrating how Heureka’s shared intelligence can be consumed outside of the Heureka platform. We continue to work with new partners to push the platform into areas such as machine learning and text analytics while enhancing the ability of the system to find and classify even more data types. Additionally, Heureka is working on enhanced workflows while adding more seamless integration to outside systems. Keep your eye out for more news on the Heureka platform.