Beyond Search: Harnessing the Power of Today’s AI as we Wait for the Promise of Tomorrow

Beyond Search: Harnessing the Power of Today’s AI as we Wait for the Promise of Tomorrow

The definition of artificial intelligence (AI) has morphed over the past year, much like the definition of ‘Printing’ has morphed over time from lithographic processes to current laser and PDF technologies, that we still call printing. In the later 2000’s ‘AI’ meant ‘near-duplicate detection,’ ‘conceptually find similar,’ ‘conceptual clustering,’ ‘email threading,’ CAL (continuous active learning), and TAR (technology-assisted review). The new definition moves the needle to include ‘generative artificial intelligence’ technology, which will be more robust and powerful by any standard. 

As we all wait for the promise of generative AI, touted as the panacea of all things eDiscovery, there are many artificial intelligence tools and features that users can currently use to optimize workflow.

Make sure to fully understand precisely what you are getting when asking your provider, vendor, law firm, or legal department about their use of AI for an upcoming project. The following features can dramatically enhance workflows, time spent, and, in turn, costs WITHOUT using generative AI tools and processes.

  1. Analytics Dashboard:
    • Display and share case intelligence through an intuitive dashboard.
    • Interactive charts and graphs enable users to navigate to important documents instantly.
  2. Related Documents:
    • Keep document families intact and easily accessible.
    • Review related documents identified by third-party eDiscovery applications.
  3. Distributed Sample:
    • Create a statistically defensible control set by generating a sample of documents from all concept clusters.
  4. Entity Identification/Extraction:
    • Utilize AI-powered identification and extraction of personally identifiable information (PII) from metadata.
    • Identify PII from over 50 countries to generate Density reports and graphs for impact and risk analysis
  5. Predictive Coding:
    • Leverage ‘machine learning’ to extend coding decisions across datasets.
    • CAL continuous learning workflow with multi-issue identification expedites case fact discovery and document review.
  6. Intelligent Batching:
    • Enhance reviewer efficiency by creating precise review batches, optionally including email threads.
  7. Conceptual Clusters:
    • Discover and analyze key ideas within datasets autonomously.
    • Interact with concept clusters using mosaic graphs.
  8. XMPLAR™:
    • Generate synthetic documents and search for conceptually similar documents within the dataset.
  9. Email Threading:
    • Understand email communications in context by grouping and reviewing emails by conversation.
    • Inclusive emails eliminate review redundancy, showing only the final email in a conversation thread.
  10. Near Duplicates:
    • Improve coding consistency by gathering and reviewing multiple document versions together.
  11. Intelligent Redaction:
    • Bulk identify, folder, and search for keywords and PII using the ‘COVER’ module.
    • Redact PII such as credit cards, phone numbers, emails, banking info, etc., and produce redacted PDFs.
  12. Conceptually Similar:
    • Find documents containing similar concepts, even if they don’t contain identical words.
    • Monitor reviewer productivity metrics and review quality using the built-in Oversight module.

Benefits of AI Adoption

  1. Cost Efficiency: AI solutions lower eDiscovery costs significantly by automating repetitive tasks and reducing the need for manual review, making legal services more accessible and affordable.
  2. Time Savings: AI-driven eDiscovery platforms accelerate the document review process, enabling legal teams to meet tight deadlines and respond swiftly to legal requests, investigations, or litigation.
  3. Accuracy and Consistency: Machine learning algorithms consistently apply predefined criteria to assess document relevance, minimizing the risk of human error and ensuring more consistent outcomes across document reviews.
  4. Scalability: AI technologies scale effortlessly to handle large volumes of data, making them well-suited for eDiscovery tasks in cases involving massive document productions or complex litigation.

At iCONECT, our commitment to innovation in Artificial Intelligence (AI) has been unwavering. We’ve harnessed AI to empower organizations to search, sort, identify, organize, and tag digital documents and data. From acquiring AI source code from Ayfie-Norway in 2021 to integrating with the patented Sentio technology, our journey underscores our responsible adoption of GenAI to enhance all platform aspects without compromising data integrity or security.


Below are three ways we can help you on your journey integrating responsible data intelligent into your company

  1. Schedule a demo with us. We can help show you around, answer questions, and help you see if iCONECT is right for you. Click Here!
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