They say that a watched pot never boils. That’s not really true, but in legal technology a lot of people spend time waiting with their finger over a button. The wait is over.
I was recently introduced to Toronto-based Rampiva Automate, a business process automation solution that integrates with Nuix’s well-known e-discovery processing engine to automate processing on e-discovery projects. I spent time talking with Rampiva founder Daniel Boteanu recently. Below is a distillation of that conversation.
Mike Quartararo: What is Rampiva Automate and what problem does it solve?
Daniel Boteanu: No one really likes processing data. People like discovering facts and patterns, but extracting metadata and running the next OCR job is a grind. Configuring the next report, picking processing settings, checking output to make sure it was executed correctly, and processing ESI is full of manual activities that have to be executed exactly right every time, as soon as possible, and probably a little different from the last task. Rampiva Automate integrates with Nuix’s data processing engine to automate processing using preset processing templates designed for your project. A processing technician can build expert-level workflows and save them to template library so the rest of us can pick the right workflow for our project, schedule it, and get an alert when the job is done.
MQ: What led to the development of Rampiva Automate?
DB: Like most things worth building, necessity. We realized that the manual workload is just unsustainable. There aren’t enough people who can do the work, the opportunity for user-error is too high, and the administrative layer is too burdensome. If we want to take the lessons we’ve learned from e-discovery and apply them to problems relating to data, we need to automate the processes.
MQ: Describe a use case for Rampiva Automate.
DB: The reason people use Rampiva Automate is so that they can build a job queue that will seamlessly execute data processing tasks in Nuix based on priority. This reduces user error, accelerates speed to results, and frees up analysts and project managers to focus on case strategy or other more important tactical tasks. At the end of the day, there’s really only one reason that people use Rampiva Automate — there’s too much data, too many projects, and not enough people to do it right every single time.
MQ: What is Rampiva Automate doing behind the scenes? What technology does it leverage?
DB: Using the Nuix processing engine, Rampiva Automate provides an alternative platform for executing data processing tasks. Like Nuix’s workstation product, Rampiva Automate uses the Java API to manage task execution with the Nuix engine. This provides more granular control of processing events than platforms built using the Nuix RestAPI. Rampiva Automate provides a job queuing system, called Scheduler, that accesses a customizable library of predefined workflows containing a list of tasks to run in Nuix.
MQ: I can imagine other uses for Rampiva Automate. What might they be?
DB: A client might want to monitor a department’s file share to alert business stakeholders of any items that have aged past the appropriate retention period or any new items that potentially contain sensitive data. That client would set up a trigger in Scheduler so that every fourth Saturday, a low-priority job is created in the job queue to execute a metadata scan of that file share using the next available set of Nuix workers, and then filter out any items that do not meet the defined date criteria — say, last accessed more than seven years ago or created in the past 30 days. Items that meet the first [criterion] would be written to a Nuix case as a lightweight metadata profile, and items that meet the second [criterion] would be completely indexed, and a search for known indicators of sensitive information would be executed. When these tasks are complete, an email notification is sent to the business stakeholder providing a link to Nuix case where the stakeholder can review and tag items with instructions.
When that review is completed, the team can then schedule a second job in Scheduler that creates an XML file with move, encrypt, or delete instructions based on policy and the stakeholder’s input. And after each task is executed, Rampiva Automate logs operational and case metrics in a built-in or a SQL database, so that users have a real-time database of all processing activity.
MQ: How else are organizations leveraging Rampiva Automate?
DB: Rampiva Automate can help a regulatory agency to capture their subject matter experts’ knowledge and standardize their internal methodology, including:
- Defining the special processing settings for specific types of forensic files
- Customizing the method for recovering deleted files
- Building custom dictionaries for decryption based on the data in each case, leveraging external brute-force decryption tools and loading the decrypted items back in the case
- Identifying indicators of date tampering and file manipulation
- Identifying known malicious files
These are all technologically feasible steps to execute in any data processing project but can require advanced-user knowledge to execute properly. Rampiva Automate becomes a force multiplier for those experts — allowing the client to support substantially more caseload without overburdening their existing team.
And on an operational level, teams are leveraging Rampiva Automate’s improved metrics tracking capabilities to better integrate their data processing with their Legal Operations objectives. This can be process testing and workflow optimization and billing, but it can also include cross-case analytics, data reuse, and detecting potential risk vectors by flagging unexpected domains and named entities.
Data is data — but, the goals, budgets, complexity, and urgency of processing data projects varies wildly between use cases. Rampiva Automate allows teams to expand their resources in a reliable, scalable, and cost-effective manner.
Mike Quartararo
Mike Quartararo is the President of the Association of Certified E-Discovery Specialists (ACEDS), a professional member association providing training and certification in e-discovery. He is also the author of the 2016 book Project Management in Electronic Discovery and a consultant providing e-discovery, project management and legal technology advisory and training services to law firms and Fortune 500 corporations across the globe. You can reach him via email at mquartararo@aceds.org. Follow him on Twitter @mikequartararo.