What is eDiscovery with advanced AI?

"Advanced AI" in eDiscovery refers to methods that go beyond simple keyword search and basic filtering to understand the content and context of documents. These techniques help legal teams manage the growing volume and variety of electronically stored information without a matching increase in review hours.

The capabilities most often described as advanced AI include:

• Predictive coding and technology-assisted review (TAR): models learn from reviewer decisions to rank documents by likely relevance, so the most important material surfaces first.

• Conceptual and semantic search: finds documents by meaning and related ideas, not just exact words, catching relevant records that keyword search misses.

• Generative AI: summarizes long or complex documents, extracts key facts and dates, and answers natural-language questions about a data set.

• Classification models: flag privilege, sensitivity, or issue categories to guide and prioritize review.

Used well, these tools shift reviewers from reading everything to working with prioritized, summarized, and fact-tagged material. Two principles keep advanced AI defensible: keep a qualified human in control of final coding decisions, and validate performance on your own data, for example by sampling to measure precision and recall before relying on the results. Because accuracy varies by data set and vendor, it is wise to test any platform on a representative sample rather than on marketing figures.

For a plain-language overview of what AI can and cannot do in this space, see eDiscovery AI: What It Is and What It Can Do.

Claira is an AI eDiscovery platform that applies these techniques - classification, summarization, and fact extraction - across large review sets. See how it works.