Everlaw AI

What is Everlaw AI?

Everlaw is a cloud-based e-discovery and litigation preparation platform. Founded in 2011 by AJ Shankar, the platform helps law firms, corporate legal departments, and government agencies process, review, classify, and analyze terabytes of documents in large-scale investigations or lawsuits.

How it works

During the discovery phase of a lawsuit, parties exchange enormous volumes of electronic data (emails, chat messages, PDF documents, spreadsheets). Everlaw imports this data and uses artificial intelligence with supervised learning (known in the legal industry as predictive coding). As lawyers mark documents as relevant or irrelevant, the AI learns the characteristics of those documents and projects relevance scores to the remaining millions of documents, significantly accelerating the review.

Key features

• Fast and Intuitive Search: Visual and fast search engine that allows building complex queries in seconds without coding.
• Predictive Coding (Active Learning): AI that learns from human reviewers' decisions to automatically classify documents by relevance.
• Everlaw Storybuilder: Integrated timeline and fact-narrative tool, linking physical evidence directly to the legal arguments of the petition.
• Generative AI (Everlaw AI Assistant): Integration of large language models to summarize long documents, draft factual summaries, and propose answers to complex questions about the case files.
• Optical Character Recognition (OCR) and Machine Translation: Conversion of images into searchable text and translation of dozens of languages in real time.

Available integrations

Everlaw has enterprise-grade native connectors to import data from common tools such as Google Workspace, Microsoft 365, Slack, Box, Dropbox, Zoom, and corporate custody systems, allowing direct ingestion of electronic evidence without intermediate local downloads.

Who it is for

• Medium and large law firms dealing with complex civil or commercial litigation.
• In-house legal departments of large corporations exposed to frequent audits or litigation.
• Regulatory agencies and government bodies involved in white-collar or competition crime investigations.

Real use cases

1. Rapid Internal Investigations: A corporation discovers a confidential data leak and uses Everlaw to analyze and summarize hours of employee chat histories in a few hours.
2. Review of Multibillion-Dollar Litigation: Firms managing lawsuits with millions of emails use predictive coding to identify and exclude duplicate or irrelevant files (de-duplication), reducing team costs.

Pricing

Pros and cons

Pros:

• Intuitive interface compared to legacy legal systems.
• Native timeline tool (Storybuilder) helps structure the legal thesis logically.
• Exceptional page loading and text search speed.

Cons:

• Can have a high cost for small-scale cases or litigation.
• Initial learning curve for lawyers less accustomed to data analysis technologies.

Alternatives to Everlaw

Key alternatives in the corporate legal market are:

• Relativity (RelativityOne): The classic, highly customizable market leader in e-discovery.
• Disco (CS Disco): Cloud legal platform that also bets heavily on AI for e-discovery optimization.
• Logikcull: More accessible e-discovery solution aimed at smaller-scale cases or smaller law firms.