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Relativity aiR for Litigation: Complete Buyer's Guide logo

Relativity aiR for Litigation: Complete Buyer's Guide

Enterprise-grade generative AI platform for litigation management

IDEAL FOR
Mid-to-large law firms (50+ attorneys) and corporate legal departments with substantial litigation volumes
Last updated: 3 weeks ago
3 min read
139 sources

Relativity aiR for Litigation is an enterprise-grade generative AI platform that transforms high-volume document review and litigation management through integrated artificial intelligence capabilities within the RelativityOne ecosystem.

Market Position & Maturity

Market Standing

Relativity aiR occupies a dominant position in the enterprise litigation AI market through its integration with RelativityOne's established ecosystem, serving as the AI evolution of the world's most widely deployed eDiscovery platform [122][135].

Company Maturity

Relativity's 20+ year market presence and established relationships with AmLaw 200 firms and corporate legal departments globally [135].

Growth Trajectory

Expanding customer implementations and documented success stories across government and commercial sectors [137][138].

Industry Recognition

Integration partnerships with major legal technology providers and adoption by leading litigation support firms like FTI Technology [124].

Strategic Partnerships

Strategic partnerships with Microsoft through Azure OpenAI integration demonstrate enterprise-grade technology alliances [122].

Longevity Assessment

Relativity's established business model and recurring revenue base from RelativityOne subscriptions provide stability indicators [135].

Proof of Capabilities

Customer Evidence

JND Legal Administration processed 650,000 documents in one day using aiR for Review, compared to traditional methods requiring weeks of manual review [137].

Quantified Outcomes

750+ hours of time savings and $85,000 in cost reductions on a corporate matter, with employee dispute cases showing 60% cost reduction in under 14 weeks [138].

Case Study Analysis

Healthcare sector validation comes through a documented case study where aiR for Privilege achieved $3 million in cost savings by reducing privilege review from 20 weeks to 2 weeks while increasing identification accuracy [124].

Market Validation

Adoption by FTI Technology, a leading litigation consulting firm, with professionals expressing excitement at aiR's potential to improve workflows alongside consultant expertise [124].

Competitive Wins

Government sector adoption provides critical validation for enterprise-grade capabilities, with documented implementations requiring FedRAMP compliance that most alternatives cannot provide [129][137].

Reference Customers

Enterprise customer profile analysis reveals adoption among organizations with litigation budgets exceeding $500,000 annually [136][138].

AI Technology

Relativity aiR's technical foundation centers on GPT-4 integration through Azure OpenAI, delivering multi-step reasoning capabilities [122][127].

Architecture

The platform's architecture emphasizes explainable AI outputs with transparent rationale and citations [123][127].

Primary Competitors

Lex Machina, Bloomberg Law, Westlaw Edge, Gavelytics, Casetext [17][24][27][129].

Competitive Advantages

Platform integration advantage through deep integration with RelativityOne's established litigation management ecosystem [122][127].

Market Positioning

Market consolidation trends favor comprehensive platforms like aiR over specialized tools requiring separate integration efforts [10].

Win/Loss Scenarios

Win for high-volume litigation with substantial document review requirements, government contractors needing FedRAMP compliance, and existing RelativityOne users seeking AI capabilities [129][137].

Key Features

Relativity aiR for Litigation product features
aiR for Review
Delivers accelerated document analysis through AI-powered relevance scoring and issue identification that goes beyond traditional keyword matching [123][127].
aiR for Privilege
Addresses privilege review inefficiencies through contextual document understanding rather than keyword matching [122][127].
aiR for Case Strategy
Extends beyond document review to support deposition preparation and timeline visualization [131].
Explainable AI Architecture
Provides transparent reasoning chains and citations for all AI predictions and recommendations [122][127].
Natural Language Processing
Enables conversational instructions with structured analysis responses including supporting evidence and reasoning chains [127][130].

Pros & Cons

Advantages
+Comprehensive platform integration within the RelativityOne ecosystem [122][127]
+Explainable AI architecture with transparent reasoning chains [122][127]
+FedRAMP compliance providing government-grade security certification [129]
Disadvantages
-Platform dependency requiring RelativityOne infrastructure [122][127]
-Extensive resource requirements for successful adoption [137][138]
-Budget barriers limiting accessibility for smaller organizations [136][138]

Use Cases

🚀
Mass Tort Litigation
Requires extensive document review, leveraging aiR's capabilities for high-volume analysis [129][137][138].
🚀
Government Investigations
Demands FedRAMP compliance, uniquely positioning aiR among AI litigation tools [129].
🚀
Corporate Internal Investigations
Needs rapid document analysis, benefiting from aiR's accelerated review capabilities [137].
🚀
Complex Commercial Disputes
Requires comprehensive case strategy development, supported by aiR's integrated approach [138].

Integrations

RelativityOne

Pricing

Enterprise Tier
$50,000-$200,000 range for mid-sized implementations
Includes comprehensive AI integration for high-volume litigation practices.

How We Researched This Guide

About This Guide: This comprehensive analysis is based on extensive competitive intelligence and real-world implementation data from leading AI vendors. StayModern updates this guide quarterly to reflect market developments and vendor performance changes.

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Standardized assessment framework across 8 key dimensions for objective comparison.

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Sources & References(139 sources)

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