Everlaw vs Relativity aiR: pricing, features and which to choose

Everlaw is a cloud eDiscovery and litigation platform founded in 2010 by AJ Shankar after consulting work exposed recurring discovery problems. The company is based in Oakland, California, and serves law firms, corporate legal departments, government agencies, journalists, and nonprofits. Everlaw says it serves more than 1,000 customers, including Fortune 100 counsel, 93 of the Am Law 200, federal agencies, and all 50 state attorneys general. Reuters reported that the company raised $202 million in a 2021 Series D, bringing total funding to $305 million and its valuation above $2 billion. The company began as EasyESI and adopted the Everlaw name in 2014. This background helps explain its emphasis on replacing fragmented discovery systems with a shared workspace for review, analysis, preparation, and presentation.

A typical workflow starts with data imported from Microsoft 365, Google Workspace, Zoom, Slack, iManage, or native uploads. Everlaw processes those files into searchable databases and projects, where teams can search, cluster, review, code, redact, translate, and produce material. Legal holds, timelines, communication visualization, fact management, and Storybuilder connect document review with case preparation. Predictive coding and Coding Suggestions reduce repetitive classification. Deposition Analyzer and transcript tools support examination preparation. The API handles uploads, search, reporting, administration, billing-size retrieval, and document-text replacement. Everlaw includes onboarding, training, and support with its service. Matter teams can therefore move from collection through production without exporting every stage into separate review and presentation products. Because processing and review remain in one hosted environment, teams can reduce handoffs, but migration planning still matters when inherited collections use unusual formats or inconsistent metadata.

Everlaw's strengths are collaborative review, narrative case preparation, public-sector credentials, and AI that connects answers to source documents. Its peak-volume pricing can make costs harder to forecast, and Deep Dive requests can pass through subprocessors. DISCO is a close alternative with Cecilia, deposition workflows, timelines, and per-gigabyte pricing. RelativityOne offers a larger partner network and more deployment choice, while Logikcull is easier to scope for smaller matters. Everlaw does not offer customer self-hosting, and buyers seeking a public commercial calculator may prefer a more transparent vendor. Everlaw is most compelling when discovery and case storytelling belong to the same team, rather than when a buyer primarily needs a narrowly scoped drafting or collection utility. Legal teams wanting cloud-native review, investigation, and courtroom storytelling should pick Everlaw.

Relativity aiR is Relativity's generative AI suite for legal data intelligence inside RelativityOne. It targets litigation, investigations, document review, privilege work, and case preparation. Relativity announced limited availability for aiR for Review at Legalweek 2024, followed by general availability for Review in September 2024 and Privilege in November 2024. The company reported more than 100 million aiR document decisions during the 20 months ending in October 2025. Relativity also reported $160 million in research and development investment for 2025, a company wide figure rather than an aiR budget. The suite is designed for legal teams that need review controls, auditability, and AI assistance within an existing case data system. Its positioning therefore emphasizes controlled deployment within established litigation workflows rather than replacement of attorneys or outside counsel.

Relativity aiR begins with extracted text and images in a RelativityOne workspace. In aiR for Review, a user writes natural language criteria, tests prompts on a smaller subset, and analyzes a collection. Results identify significant documents, explain their relevance, and cite supporting passages. Privilege analyzes documents and relevant personas, predicts privilege, and drafts privilege log descriptions. Case Strategy supports fact extraction, timelines, summaries, and work product. Assist provides conversational search over legal data. Outputs include rationales and considerations, while Review Center can calculate precision, recall, and elusion metrics for quality control. These controls make the system more suitable for defensible review than a general purpose chatbot operating outside the matter workspace. They also give review leaders a structured basis for sampling, escalation, and documenting decisions before production.

The main limitation is that aiR depends on RelativityOne, which makes it less suitable for teams choosing a standalone review system. Inference may occur outside the instance storage region when Azure model availability requires it, although Relativity says customer data is not used to train third party models. Everlaw offers a separate cloud discovery platform with comparable AI review workflows, while DISCO focuses on cloud discovery and case preparation without requiring RelativityOne. Clearbrief focuses on cited drafting and discovery-related writing, and Briefpoint supports automated legal drafting as an add-on product. Westlaw Precision is aimed at legal research rather than matter data. Choose aiR when review, privilege, validation, and case intelligence should remain in one RelativityOne workspace. Confirm regional processing, contract scope, and migration costs before standardizing on it.