That title might seem like I’m Captain Obvious, but it’s true. There’s nothing “artificial” about this approach to next-generation discovery! HaystackID® has defined an approach to discovery intelligence that synergistically harnesses the potential of artificial intelligence, the precision of data science, the power of machine learning, and the practicality of expertly trained and managed reviewers.
In their website page (HaystackID® Discovery Intelligence: Powering Next-Generation Discovery), HaystackID provides a detailed description of what next-generation discovery looks like, with four synergistic elements of discovery intelligence, as follows:
- Potential – The Potential of Artificial Intelligence: Proprietary artificial intelligence technologies and processes to deliver on the potential of AI.
- Precision – The Precision of Data Science: Proprietary data science approaches and algorithms to extract knowledge and insight, which includes the five stages of the data science lifecycle.
- Power – The Power of Machine Learning: Proven application of propriety machine learning workflows and analytics to maximize results, typically using the Continuous Active Learning® (CAL®) predictive coding protocol developed, used, and advocated by Maura R. Grossman and Gordon V. Cormack.
- Practicality – The Practicality of Expertly Trained and Managed Reviewers: Proprietary review sourcing, selection, and support systems that power next-generation reviews with the Discovery Intelligence synergy.
Discussion of the elements includes a comprehensive list of links to numerous resources and case studies. And the page also includes one example of how the HaystackID Discovery Intelligence approach is manifested, which is in HaystackID’s Protect Analytics™ offering. Protect Analytics is an exclusive set of technologies and processes that allows client data set analysis for sensitive information ranging from PII and PHI to data breach code anomalies. It’s enabled by a collection of proprietary workflows and proven tools and can proactively or reactively help determine sensitive data concentrations, locations, and relationships to inform notification lists, exposure assessments, and discovery targeting.
It’s a great detailed discussion of what next-generation discovery looks like and a great representation of HaystackID’s Discovery Intelligence approach! Check it out here!
By the way, I missed this earlier, but earlier this month HaystackID announced a partnership with Intelligent Voice, a leading specialist in voice and audio analysis solutions. Intelligent Voice provides a full end-to-end audio discovery process in the Relativity surveillance application, with proprietary GPU-based algorithms minimizing any gap between data loading and data review, redaction, and production. Here is more info on the announcement. Congrats to the HaystackID and Intelligent Voice teams on the partnership announcement!
So, what do you think the next-generation of discovery looks like? Please share any comments you might have or if you’d like to know more about a particular topic.
Disclosure: HaystackID is an Educational Partner and sponsor of eDiscovery Today
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