Massive discovery bottlenecked a lean legal team. AI surfaced key issue patterns, freeing attorneys to shape early case strategy.
A law firm managing large-scale discovery for corporate clients faced a high-stakes, multi-party dispute involving over 3 million initial documents.
After targeted search terms and date filtering, a lean attorney team was left with 500,000 documents requiring analysis under aggressive deadlines....
“Being able to quickly compare issue patterns across incoming and outgoing productions fundamentally changed how we viewed the facts and determined areas of focus. Without aiR for Review, that level of analysis simply wouldn’t have been possible.”
International law firm for corporate, intellectual property, and litigation matters.
Legal data platform for e-discovery, investigations, and contract review.
Related implementations across industries and use cases
Tasked with reviewing 300k documents in one week, a single partner used AI to classify complex issues and meet the court deadline.
Opaque AI flags forced counsel to manually re-read documents. Now, generative AI cites its reasoning to accelerate final decisions.
Lease review took days of associate time. AI now synthesizes facts in minutes, freeing 40 hours per case for strategy.
Tasked with reviewing 300k documents in one week, a single partner used AI to classify complex issues and meet the court deadline.
Reviewing expert reports took hours of manual scrutiny. AI now surfaces inconsistencies and structures findings in minutes.
Infrastructure compliance checks took months. Now, engineers use AI to parse massive datasets, cutting final review cycles by up to 90%.
Auditors lost hours manually recalculating financial statements. Now, AI verifies math and consistency so teams can analyze exceptions.
Opaque AI flags forced counsel to manually re-read documents. Now, generative AI cites its reasoning to accelerate final decisions.
Attorneys juggled fragmented tools to search 50,000 cases. An AI orchestrator now routes queries to sub-agents in a single chat.
Massive discovery bottlenecked a lean legal team. AI surfaced key issue patterns, freeing attorneys to shape early case strategy.
A law firm managing large-scale discovery for corporate clients faced a high-stakes, multi-party dispute involving over 3 million initial documents.
After targeted search terms and date filtering, a lean attorney team was left with 500,000 documents requiring analysis under aggressive deadlines....
“Being able to quickly compare issue patterns across incoming and outgoing productions fundamentally changed how we viewed the facts and determined areas of focus. Without aiR for Review, that level of analysis simply wouldn’t have been possible.”
International law firm for corporate, intellectual property, and litigation matters.
Legal data platform for e-discovery, investigations, and contract review.
Related implementations across industries and use cases
Tasked with reviewing 300k documents in one week, a single partner used AI to classify complex issues and meet the court deadline.
Opaque AI flags forced counsel to manually re-read documents. Now, generative AI cites its reasoning to accelerate final decisions.
Lease review took days of associate time. AI now synthesizes facts in minutes, freeing 40 hours per case for strategy.
Tasked with reviewing 300k documents in one week, a single partner used AI to classify complex issues and meet the court deadline.
Reviewing expert reports took hours of manual scrutiny. AI now surfaces inconsistencies and structures findings in minutes.
Infrastructure compliance checks took months. Now, engineers use AI to parse massive datasets, cutting final review cycles by up to 90%.
Auditors lost hours manually recalculating financial statements. Now, AI verifies math and consistency so teams can analyze exceptions.
Opaque AI flags forced counsel to manually re-read documents. Now, generative AI cites its reasoning to accelerate final decisions.
Attorneys juggled fragmented tools to search 50,000 cases. An AI orchestrator now routes queries to sub-agents in a single chat.