Request Your Free Case Study Now:

"Identifying the 'Strike Zone' for Generative AI-Based Document Review"

Explore a real-world case study that reveals how legal teams can determine when and when not to apply GenAI in document review. Download it today and learn from practical testing and detailed results to see how targeted application of AI can enhance speed, accuracy, and efficiency in legal workflows.

As legal departments seek smarter, more efficient ways to manage discovery, generative AI (GenAI) is emerging as a compelling tool—when applied strategically. This case study offers a detailed, data-backed look at how one legal technology team rigorously tested GenAI's capabilities in document review using a previously adjudicated matter.

Following extensive testing of over 26,000 documents and controlled prompt engineering, researchers defined a “strike zone”—the conditions under which GenAI performs most effectively. The results demonstrate that GenAI can produce recall rates above 90% and precision rates near 70% across diverse document sets.

This case study guides legal leaders through the real limitations, ideal use cases, and strategic implications of GenAI-based review. It shares methodology insights, discusses model variability and accuracy, and highlights how to balance recall and precision across varying document richness levels.

Download this case study to learn:

• What characteristics make a document ideal—or problematic—for GenAI-based review.
• Why defining a “strike zone” improves the effectiveness of AI document processing.
• How precision and recall metrics were impacted by prompt refinement and data curation.
• What role human SME input plays in GenAI training and tuning.
• How to build a hybrid AI + traditional review workflow for faster, more accurate outcomes.

Download the case study today and explore the boundaries of AI-driven discovery.

Offered Free by: HaystackID
See All Resources from: HaystackID