Don’t Chase Words, Find Meaning

Traditional keyword searching is inherently limited. Attorneys have to guess at the right terms, anticipate nicknames, acronyms, and code words, and then spend hours sorting through irrelevant material that simply happens to contain those terms. This approach increases the risk of missing critical documents while also driving up review costs. In high-stakes litigation, neither overproduction nor inadvertent omission is defensible.

Relativity’s aiR for Review changes this by reviewing documents in context. By supplying a matter overview, lists of key people and aliases, organizations, noteworthy terms, and clear relevance criteria, you effectively brief the AI like you would an associate. It then applies that knowledge across the entire dataset, identifying relevant material even when the magic words never appear.

The result is a review process that is both more efficient and more defensible. Instead of delivering a bloated keyword hit list, AI narrows the review set to documents that actually meet the case criteria. That translates to lower client costs, faster timelines, and reduced litigation risk, all while maintaining consistency and quality across the review. In a competitive environment where clients demand efficiency and precision, AI review offers a strategic advantage over legacy keyword searching.

At Page One, we know that moving from keyword guesswork to AI-powered context can feel like a big shift, but it’s one that delivers measurable advantages in efficiency, accuracy, and defensibility. Our team has the expertise to help you design workflows, set the right criteria, and get the most out of Relativity’s aiR for Review. If you’re ready to explore how generative AI can transform your document review, we’d love to start the conversation. After all, when it comes to your matters and your clients, we’re always More Powerful Together.