Identify collect and review in 15 minutes
The problems with E-Discovery
According to Gartner, corporate data has been growing just over sixty percent on average per year. At this growth rate, antiquated collection tools have not been able to keep pace with the data volume and have shown few signs of innovative evolution. Technology Assisted Review addresses tagging and identification of data at the end of the process, not the beginning.
Traditional E-Discovery collections do not provide users with true Early Data Assessment or data analytics and have forced users into a workflow by which they must over-collect information before having a true understanding of the content. This traditional process has driven up the overall cost of E-Discovery by forcing users to collect, process and review a high percentage of non-responsive documents and if processing in-house forced the purchasing of expensive processing tools, people and data storage.
Heureka has changed the outdated collection model by harnessing the power of individual endpoints. Heureka installs a lightweight endpoint service which creates a full text and metadata index for laptops, desktops and file shares running Windows, macOS or Linux. Each index remains on the local machine whereby a central command console is used to perform actions on the endpoints including search, collect, delete or quarantining of files.
Heureka users can analyze search results at the point of creation without moving a single file until needed. Any initiated endpoint action takes a minute or less to run across hundreds or thousands of endpoints. Searches can be edited according to returned results without collecting a single file. Search results can be exported for further analysis in BI platforms such as Tableau.
If file collection is required, a collect action is created in the Heureka interface using one of Heureka’s Express Export options. Files may be collected for review platforms such as Relativity, Zapproved, Logikcull or iCONECT, or if a custom export style is needed it can be selected with an advanced selection. Specific platform templates are in place in order to make exporting data as simple as possible. Heureka helps clients significantly reduce non-responsive data collection by allowing clients to perform surgically targeted collections based on search results. This type of data collection drastically reduces all downstream E-Discovery costs by helping eliminate non-response document processing and review.
Heureka’s Express Export module speeds up the process from collection to review. Collected documents are automatically formatted for a desired review platform taking the guesswork out of what settings to use. Zapproved and Logikcull users will find compressed folders sorted by endpoint (custodian) with full file paths contained within the compressed data structure. Relativity and iCONECT users can take advantage of advanced functions like file renaming, compression and individual native files along with extracted text exporting which saves even more time and money by not requiring downstream file processing.
Once imported into a review platform, a normal document review can occur. If additional custodian data is required, a user may log back into Heureka, select any number of custodians and perform their search and collections. Also, if new or modified keywords or queries need to be added to searches, it’s possible to create new searches identifying additional information.
Heureka has a standard, built-in classification engine which runs daily across new or modified endpoint data. Heureka enables users to quickly identify risky information such as social security or bank routing numbers along with credit card information or offensive words. Heureka’s classification tags provide additional context to the information on each endpoint allowing users to make more intelligent choices on files and file content. Additionally, Heureka’s platform supports “shared intelligence” by allowing Heureka-specific classification tags to be exported into review platforms thus providing additional file context during the review process. New development will streamline the entire process and offer even greater file intelligence and classification information.