Everlaw
Cloud ediscovery platform that grounds AI answers in your case evidence, with an open layer that feeds Claude, Harvey, Gemini, and Copilot.
Pick Everlaw when the matter is genuinely large and the review population is brutal — 239M+ documents and 1,000+ concurrent reviewers is the scenario it was engineered for, and Coding Suggestions (with single-document actions costing no credits) is worth a real pilot. The evidence-layer bet is the strongest thing here: keep Claude, Harvey, Gemini, or Copilot as your drafting stack and let the record stay governed in one place, now extended into Microsoft Word via Everlaw for Word (October 2026). Compare it against Relativity aiR and DISCO before committing, because the per-GB model and credit-metered Deep Dive, machine translation, custom extractions, and batch Coding Suggestions sit on top
Verified 5d ago · liveness 77/100 · cite: rightaichoice.com/tools/everlaw
- Large law firms running multi-million-document litigation with hundreds of concurrent reviewers
- Corporate legal teams investigating across email, chat, video, and messaging platforms
- Government agencies that require FedRAMP Class C (Moderate) and GovRAMP Moderate authorization
- Trial teams that need testimony, designations, transcripts, and exhibits in one system
- Solo practitioners and small firms with low document volumes that need cheap per-case pricing
- Organizations requiring on-premise or self-hosted deployment
- Teams planning heavy batch AI use without budgeting for credit-metered spend
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Skip Everlaw if your matters are small enough that a per-GB data model costs more than the review time it saves, or if you require on-premise deployment rather than a cloud-only platform.
Deep Dive natural-language Q&A runs on credits on top of your subscription, so heavy querying of large matters adds spend beyond the base price.
Everlaw sells per-GB of data managed with unlimited user licenses, so pricing fits large firms, corporate legal departments, and government agencies that already carry multi-million-document matters. Against Relativity, which also prices on data volume with add-on AI modules, Everlaw bundles in unlimited seats and metadata-migration support. Teams with small, occasional matters are usually better served by lower-cost review tools priced per case or per seat.
In short
Everlaw — Cloud ediscovery platform that grounds AI answers in your case evidence, with an open layer that feeds Claude, Harvey, Gemini, and Copilot. Best for Large law firms running multi-million-document litigation with hundreds of concurrent reviewers, Corporate legal teams investigating across email, chat, video, and messaging platforms, Government agencies that require FedRAMP Class C (Moderate) and GovRAMP Moderate authorization. Contact Sales pricing.
What's new in Everlaw
Checked 5 days agoAcross the latest 1 update: 1 launch.
What people actually say about Everlaw — is it worth it?
We ran a structured research pass across product reviews, community discussions, and post-purchase forum threads to surface the patterns vendors won't publish themselves. Below: the recurring strengths, the hidden costs people mention most, and the cohort that consistently regrets adopting this tool.
6 mentions across 3 sources (Hacker News, Product Hunt, Lemmy) · researched Aug 18, 2026.
Average across the 3 sources that answered — each source counts once, not each post.
- +Cloud-native platform scales to 10M+ documents with proven reliability.
- +AI features like Deep Dive offer natural language search with citations.
- +Coding Suggestions automates first-pass review with rationales.
- +Writing Assistant synthesizes evidence and drafts arguments.
- +Review Assistant handles Q&A, summaries, and topic analysis.
- −No published pricing details, making cost comparison difficult.
- −Batch AI actions require credits that expire at term end.
- −Community feedback is sparse, lacking depth on long-term use.
- −Learning curve typical for complex ediscovery platforms.
- −Dependence on external AI models may raise compliance concerns.
- • Batch AI credits can add up and expire if unused
- • Potential overage charges for data beyond included limits
Viability Score
How well maintained and how widely used is Everlaw? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →Key Features
- Deep Dive natural-language Q&A with cited answers across tens of millions of documents
- Coding Suggestions for first-pass review with categorizations and rationales
- Writing Assistant drafts case documents grounded in your own evidence
- Review Assistant for single-document Q&A, summaries, and custom extractions
- Predictive Coding and active learning to prioritize review
- Concept Clustering and Communication Visualizer analytics
- Batch AI actions: summaries, topics, custom extractions, machine translation
- Machine translation across 100+ languages (single documents cost no credits)
- Legal holds preserved at the source with custodian tracking and audit trails
- Legal hold collection from Slack, Teams, iMessage, and WhatsApp
- Audio and video transcription
- Storybuilder for timelines, transcript analysis, and deposition prep
- Everlaw for Word, bringing case evidence into the document drafting environment
- Cloud Connectors for Microsoft 365, Zoom, and Google Workspace
- Processing at up to 1M documents per hour across 194 supported file types
About Everlaw
Everlaw is cloud-native ediscovery software built for law firms, corporate legal departments, and government agencies. It is positioned as an evidentiary system of record: the place where case data is collected, reviewed, and turned into strategy, with AI outputs tied back to documents you actually produced. The published scale numbers are unusually specific — a largest single matter of 239M+ documents, 1,000+ concurrent reviewers on one case, and 194 supported file types — and those matter more than marketing language, because review collapses when throughput or file coverage fails. AI runs across the matter rather than in one side panel. Deep Dive answers natural-language questions about case data with cited answers and, per Everlaw, carries 400x the RAG capacity of comparable tools. Coding Suggestions handles first-pass review; single-document actions cost no credits. Machine translation covers 100+ languages, custom extractions pull structured fields out of documents, and Storybuilder organizes timelines, transcripts, and deposition preparation. Batch AI actions, Predictive Coding, and Concept Clustering round out the analytics side. Legal holds are preserved at the source with custodian tracking and audit trails, and collection extends to Slack, Teams, iMessage, and WhatsApp. Ingestion runs through Cloud Connectors for Microsoft 365, Zoom, and Google Workspace, with processing quoted at up to 1M documents per hour. Redactions cover batch, native spreadsheet, and video. As of October 2026, Everlaw for Word pulls evidence directly into the environment where you draft. The strategy has shifted toward being the evidence layer underneath whatever drafting tool your team already uses — Everlaw connects to Claude, Harvey, Gemini, and Microsoft Copilot so those systems retrieve against governed case evidence. It fits large, document-heavy matters; low-volume practices should look closely at how the commercial model scales with data volume rather than seats.
Behind the Verdict
Everlaw's real argument is architectural rather than feature-list. Most ediscovery vendors bolt an AI assistant onto a review database; Everlaw is selling the database as the substrate that any AI — including ones it doesn't own, like Claude, Harvey, Gemini, and Microsoft Copilot — has to read from. That is a defensible position, because the hard part of legal AI is not generation, it is retrieval against a complete, deduplicated, privilege-aware corpus with a chain of custody behind it. The scale claims back this up with numbers rather than adjectives: 239M+ documents in a single matter, 1,000+ simultaneous reviewers, 400x RAG capacity versus comparable tools, 194 file types, processing at up to 1M documents per hour. Those are the figures that predict whether a platform survives a real production deadline. The AI surface is broad and deliberately tiered: Deep Dive for cited natural-language Q&A, Coding Suggestions and Predictive Coding for first-pass review, Review Assistant for single-document Q&A and custom extractions, Writing Assistant for drafting grounded in your own record, Concept Clustering and Communication Visualizer for the analytics view, plus batch translation across 100+ languages and audio/video transcription. Single-document Deep Dive, translation, and extraction actions are explicitly free of credit consumption, which makes targeted use cheap and batch use the thing you have to budget. The honest constraints are three. First, pricing scales with data volume under a per-GB model rather than with seats, so the platform's economics reward large matters and punish small ones — a 5,000-document employment dispute does not need this machine. Second, the AI that runs in batch is credit-metered on top of subscription, so a team planning heavy Deep Dive or bulk translation should model that spend before signing. Third, it is cloud-only, which rules out organizations with self-hosting mandates. FedRAMP Class C (Moderate), GovRAMP Moderate, and SOC 2 Type 2 cover the compliance side for government and regulated buyers. The best fit is a firm or legal department that already owns a drafting stack and wants its retrieval layer fixed, or a government/public records team buried in FOIA backlogs. The worst fit is a solo practitioner shopping on price per case, or anyone who wants to run this in their own datacenter.
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Real-world workflow fit
Concrete scenarios for the personas Everlaw actually fits — and what changes day-one when you adopt it.
A new matter lands with 4M documents collected from Microsoft 365, Slack, and Zoom. The team ingests through Cloud Connectors, processes at high speed, runs Predictive Coding and Coding Suggestions for first-pass review, then uses Deep Dive to answer targeted factual questions with citations.
Outcome: Review population shrinks before senior time is spent on it, and every AI answer is traceable to a produced document, which holds up when opposing counsel challenges the methodology.
A whistleblower complaint requires preserving Slack and Teams messages plus iMessage and WhatsApp data. Counsel issues legal holds at the source with custodian tracking, collects the messaging data, and uses Concept Clustering with Communication Visualizer to map who talked to whom and when.
Outcome: The hold is defensible with a full audit trail, and the communication map surfaces the key witness exchanges before interviews are scheduled.
A backlog of public records requests requires redaction and disclosure deadlines. The team uses the Public Records solution's intake portal and case management, with batch redactions plus native spreadsheet and video redactions, on a FedRAMP Class C (Moderate) and GovRAMP Moderate authorized platform.
Outcome: Requests move through a governed workflow with compliance reporting, and redaction work that used to be manual runs in batch.
Use Cases
- Search millions of documents with natural-language queries and get cited answers back for the evidence that matters.
- Automate first-pass review with AI coding suggestions that categorize documents and explain the rationale.
- Draft deposition outlines and trial arguments by synthesizing case evidence with Writing Assistant.
- Run early case assessment to cut the documents promoted to active review.
- Manage legal holds and preserve evidence across Microsoft 365, Slack, Teams, iMessage, and WhatsApp.
- Translate foreign-language documents in batch and store translations inside the ediscovery workflow.
- Handle FOIA and public records requests with Everlaw's dedicated Public Records solution.
- Conduct internal investigations for cyber breaches, whistleblower actions, and audits.
Models Under the Hood
as of 2026-10-15
Limitations
- Everlaw is a cloud-only litigation ediscovery platform, with no self-hosted deployment option indicated in the evidence.
- Deep Dive, batch Coding Suggestions, batch machine translation, and batch custom extractions are credit-based add-ons on top of the base subscription, while single-document Coding Suggestions, machine translation, and custom extractions cost no credits per the pricing page.
- It is positioned for large legal teams and agencies — Fortune 100 counsel, 93 of the Am Law 200, federal agencies, and all 50 state attorneys general — so it may be more platform than a small firm needs.
- Pricing is not published; quotes are handled via 'Schedule a Meeting.'
as of 2026-10-13
Verification history
We have re-verified Everlaw 20 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-checked, vendor evidence unchanged
Showing the 6 most recent of 20 verification passes.
Free to cite with attribution — this page re-verifies continuously.
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Where the pricing makes sense
The company stage and team size where Everlaw's pricing actually pencils out — and where peers do it cheaper.
Everlaw sells per-GB of data managed with unlimited user licenses, so pricing fits large firms, corporate legal departments, and government agencies that already carry multi-million-document matters. Against Relativity, which also prices on data volume with add-on AI modules, Everlaw bundles in unlimited seats and metadata-migration support. Teams with small, occasional matters are usually better served by lower-cost review tools priced per case or per seat.
Setup time & first value
How long it actually takes to get something useful out of Everlaw — broken out by persona, not the marketing-page minute.
Large firms with an existing data map can typically be ingesting through Cloud Connectors within days of kickoff, with onboarding and standard data migration provided by Everlaw. Corporate teams starting from a single investigation can be issuing legal holds in the first week. Government agencies should budget additional time for authorization and procurement rather than for the software itself.
Switching to or from Everlaw
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From Relativity: use Everlaw's standard data migration to carry case data over, then map review workflows onto Predictive Coding and Coding Suggestions.
- →From Logikcull or Everlaw's SMB-priced peers: the migration path is a scope question as much as a technical one — per-GB economics only pay off once volumes are large.
- →From an on-premise review installation: expect a collection-and-ingestion project rather than a direct platform swap, since Everlaw is cloud-only.
- →From a drafting stack (Claude, Harvey, Gemini, Copilot) that lacks a governed evidence layer: leave drafting where it is and connect it to Everlaw rather than migrating tools.
- ↗To Relativity: standard data migration is supported, and the AI modules map roughly onto Review Assistant and Predictive Coding equivalents.
- ↗To DISCO: export productions and native files, then rebuild review workflows in Disco's per-case model.
- ↗To a low-volume review tool: expect a production-and-export project, and note this usually happens because the volume no longer justifies per-GB pricing.
Integrations
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Everlaw”, and we withheld 6: 6 could not be judged, because “Everlaw” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Everlaw.
Official links
Tools that pair well with Everlaw
Common stack mates teams adopt alongside Everlaw, with the specific reason each pairing earns its keep.
Paxton AI
Paxton AI is a legal AI assistant that grounds litigation research and drafting in your case's matter record.
Lexis+ AI
Legal AI drafting and research with Shepard's citation verification built into every workflow.
AI Lawyer
Legal AI assistant for research, document summaries, comparison, OCR and drafting on web, iOS and Android.
Featured Head-to-Head Comparisons
Casetext vs Everlaw
If your bottleneck is document review and trial prep on massive datasets, Everlaw is the clear pick with its robust AI review and FedRAMP compliance. If your daily grind is legal research and contract analysis, Casetext's integration with Westlaw makes it a stronger fit. Choose based on your primary workflow: ediscovery vs. research.
Folder Pilot vs Everlaw
These are not competitors so much as different rungs of the same ladder: Everlaw is a full ediscovery platform for firms and agencies running document-heavy litigation and investigations, while Folder Pilot is a lightweight search-and-cited-Q&A tool for small teams. Pick Everlaw if you need processing, predictive coding, legal holds, and integrations with Harvey, CoCounsel, Copilot, or Gemini — and you can absorb enterprise, contact-sales pricing. Pick Folder Pilot if your problem is 'find and verify the clause fast' across a modest PDF/DOCX/TXT set and you want to start on a freemium plan. A large firm will outgrow Folder Pilot; a solo practitioner has no reason to buy Everlaw.
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