Harvey vs Clio Duo vs Everlaw: which legal AI actually fits your firm, with verified pricing (2026)

**Harvey AI** is a matter-work copilot built for lawyers who already know what a Form 10-K, an SPA, and a litigation hold look like. It draws on a fine-tuned blend of OpenAI and Anthropic models layered with proprietary legal training, plumbed into iManage and NetDocuments so the AI can actually see the firm's document corpus. You can drop in a 200-page asset purchase agreement and ask for a risk-weighted issues list against the firm's playbook, run multi-jurisdiction research with citations, or kick off a due-diligence workflow that touches dozens of contracts in one pass. Harvey explicitly does not try to be a billing system, a docket manager, or a discovery platform — it is the brain that sits next to those.

**Clio Duo** is the opposite shape: a thin, embedded assistant inside a practice management platform you already pay for. It does not pretend to do M&A diligence. It drafts engagement letters, summarizes matter histories, suggests time entries based on calendar and document activity, generates client update emails, and runs natural-language search across your Clio matters. Per https://clio.com/duo/, Duo is positioned as the AI layer that makes solo-and-small lawyers faster at the administrative drag that eats their day. It does not connect to iManage. It does not run predictive coding. It does not produce a deal-room-quality diligence report. That is fine — that is not what a 6-lawyer plaintiffs firm needs.

**Everlaw** is a different category entirely. It is an e-discovery, investigations, and litigation platform — ingestion, processing, review, analytics, and presentation in one cloud product. The AI inside Everlaw is predictive coding, clustering, concept search, Storybuilder for chronology and witness work, and increasingly generative summarization of documents and depositions. Per https://www.everlaw.com/pricing/, the platform is sold per user per year with a storage component, because the cost driver in discovery is data volume, not seats. You use Everlaw when you have a 2 TB document production to review, not when you want help drafting a demand letter.

The honest takeaway: these three only "compete" in the sense that they all show up on the same shortlist when a firm's leadership says "we need an AI strategy." Once you actually decompose the work — matter substance, firm operations, discovery — they sort cleanly into three lanes. The mistake firms make is buying Harvey for a 12-lawyer firm that mostly does PI and family law (waste), buying Clio Duo for a 400-lawyer M&A practice (insufficient), or trying to do e-discovery in Harvey or Clio (don't).

**Harvey AI** does not publish prices, which by itself tells you something about the buyer profile. Based on procurement data circulated in 2025–2026 and consistent with how enterprise legal AI is sold, Harvey lands in roughly the $3,000–$5,000 per lawyer per year range with a 50-seat minimum and multi-year terms typical. That floor is real — Harvey has publicly emphasized BigLaw and elite-boutique focus, and the sales motion is built around firmwide deployments, not pilots of 5 lawyers in the corporate group. If you are a 200-lawyer firm, you are looking at $600K to $1M annually before any premium workflow tier. As of June 2026 — verify at https://harvey.ai/ — there is no self-serve, no free tier, no public price.

**Clio Duo** is published and predictable. Per https://clio.com/pricing/, Clio Manage runs $39 per seat per month at the EasyStart tier, $69 at Essentials, $99 at Advanced, and $149 at Complete (billed annually; month-to-month is higher). Duo, per https://clio.com/duo/, layers on top at roughly $40 per seat per month on lower tiers and up to $100 per seat per month on Advanced and Complete. A 10-lawyer firm on Advanced + Duo is therefore looking at about $99 + $100 = $199 per seat per month, or about $24K per year all-in for practice management and AI. That is roughly one tenth the per-seat cost of Harvey, for a tool that does roughly one tenth the substantive legal work — which is the right ratio.

**Everlaw** uses a per-user-plus-storage model, with Standard tier landing around $3,000 per seat per year and Enterprise tiers reaching $10,000–$12,000 per seat per year when you include premium analytics, advanced security, and the larger storage allotments. Per https://www.everlaw.com/pricing/, the actual invoice depends heavily on how many GB of data you are hosting, because hosting is metered. A litigation boutique running a single 1 TB matter for 18 months will pay materially more in storage than seat license, which is why Everlaw's true cost depends on case mix. Our AI document discovery cost guide walks through the per-GB math in detail.

Here is the comparison nobody wants to make explicit: a 12-lawyer commercial litigation firm could spend $24K/yr on Clio + Duo, $50K–$100K/yr on Everlaw for the cases that warrant it, and zero on Harvey — and be perfectly equipped. A 250-lawyer AmLaw firm will spend $750K–$1.25M/yr on Harvey, layer Everlaw on top for litigation matters, and not use Clio at all. The three tools are not alternatives; they are line items in different parts of the same legal-tech budget. As of June 2026 — verify at https://clio.com/pricing/, https://www.everlaw.com/pricing/, and via Harvey sales — the gap between published and "call us" pricing is exactly the gap between the SMB and enterprise legal markets.

**Harvey AI** is built to live inside the BigLaw document fabric. It integrates natively with iManage Work and NetDocuments — the two DMS platforms that run almost every AmLaw 200 firm — and ties into Microsoft 365 for Word and Outlook surfaces. The architecture is segregated multi-tenant cloud with firm-level isolation, and the model layer mixes OpenAI, Anthropic, and Harvey's own fine-tunes. The point of this stack is that a lawyer can ask Harvey "draft a closing checklist based on this NDA and the SPA in the matter folder" and Harvey actually pulls from the matter, not from a generic dataset. Without DMS integration, none of this works — which is one reason Harvey is a poor fit for firms still living in Outlook attachments and shared drives.

**Clio Duo** is the opposite — it does not need to integrate, because it is the AI inside the platform. Clio Manage already holds your matters, contacts, calendars, billing, and documents. Duo just reads what is already there. Per https://clio.com/duo/, the assistant surfaces inside the same Clio web app where lawyers do timekeeping and intake, plus a Microsoft Word add-in for drafting. There is no iManage connection because Clio is the DMS for these firms. The architectural simplicity is exactly why Duo can be priced at $40–$100/seat/mo — there is no integration engineering for the customer to do, no MSA with a separate AI vendor, no procurement cycle beyond expanding the existing Clio contract.

**Everlaw** is its own world. Cases are ingested via API, SFTP, or direct connectors from Microsoft 365, Google Workspace, Slack, Zoom, and modern collection tools, plus Relativity load files for matters migrated in from legacy platforms. The platform runs in AWS with regional residency in the US, EU, Australia, and Canada per https://www.everlaw.com/pricing/ and the security documentation. Integration with the firm's DMS is largely irrelevant — discovery data lives in Everlaw for the duration of the matter and gets exported as productions, not synced back to iManage. This is why Everlaw operates orthogonally to Harvey: a firm can run both, with Harvey handling substantive matter work and Everlaw handling the discovery stream of any litigation.

If you are doing the architectural decision tree honestly: firms on iManage or NetDocuments default-evaluate Harvey; firms on Clio default-evaluate Duo; firms with any meaningful litigation or investigations book default-evaluate Everlaw regardless of which of the other two they pick. The DMS question more or less decides the Harvey-vs-Clio fork, and the case-type question decides whether Everlaw belongs in the stack at all.

Legal AI procurement lives or dies on three questions: where does the data sit, who can train on it, and how do we maintain privilege. **Harvey AI** answers all three explicitly — data is segregated per firm tenant, customer data is not used to train base models without explicit opt-in, and regional deployments cover US, EU, and UK. SOC 2 Type II is table stakes; firms doing UK and EU matters typically demand the regional tenant. Privilege is preserved by contractual data-handling commitments plus the segregated architecture; the firm's outside-counsel data does not commingle with another firm's tenant.

**Clio Duo**, per https://clio.com/duo/ and the Clio Trust Center, runs on a similar set of commitments — SOC 2 Type II, encryption in transit and at rest, no training on customer data, and contractual confidentiality. Where Duo differs is that it sits inside a SaaS multi-tenant practice management system, which has been the model small firms have lived with for over a decade. Privilege analysis for Duo is essentially the same analysis firms already made when they put client matters in Clio Manage in the first place. The new wrinkle is the AI layer's prompt and response handling, which Clio documents in the Duo trust documentation.

**Everlaw** is purpose-built around discovery-grade security. Per https://www.everlaw.com/pricing/ and the security pages, the platform offers SOC 2 Type II, ISO 27001, FedRAMP Moderate for federal customers, and regional data residency. Because Everlaw holds raw productions — often including privileged documents pending review — the access controls, audit logging, and chain-of-custody features are more elaborate than what either Harvey or Duo expose. This is also why Everlaw is the right answer for regulator-facing matters where the protective order requires specific handling commitments.

The blunt comparison: Harvey is enterprise-grade and ready for AmLaw security review; Duo is SMB-grade and aligned with the security posture solos and small firms already accept on Clio; Everlaw is discovery-grade and meets the higher bar required when you are holding millions of documents subject to court orders and clawback agreements. None of the three is a meaningful privilege risk if procured correctly — but all three require the firm to actually read the DPA and AI addendum before signing.

A useful diagnostic when comparing legal AI is to walk through a single Tuesday at the firm and ask which tool the lawyer would actually open. For a BigLaw senior associate on an M&A deal, Tuesday looks like: review the redline of the disclosure schedules, draft a memo on a regulatory question, run diligence on a target's IP portfolio, and prep a closing checklist. **Harvey AI** is the tool that surfaces in every one of those tasks, because Harvey is built for exactly that shape of work. Clio Duo would be useless here — there is no Clio in the firm. Everlaw is only relevant if the M&A deal has a litigation overhang.

For a solo employment lawyer, Tuesday looks like: client intake for a wrongful termination case, draft a demand letter, log billable time for three matters, prepare a fee agreement, and email an update to an existing client. **Clio Duo** touches every step — intake summary, demand letter draft, time entry suggestions, fee agreement template fill, and a one-click client update draft. Harvey is overkill and overpriced. Everlaw is irrelevant unless and until the case actually files and gets to discovery, which is months away.

For a litigation partner running a federal antitrust matter, Tuesday looks like: review a witness deposition transcript, run a search for any document mentioning a specific product line and competitor, kick off a privilege review on the latest production from opposing counsel, and prepare a case timeline for an upcoming summary judgment motion. **Everlaw** is the tool — Storybuilder for the timeline, predictive coding for the privilege review, generative summarization for the deposition. Harvey may handle the brief drafting on top, but the discovery layer is Everlaw's job. Clio Duo has nothing to offer at this level of matter.

The day-in-the-life test makes the buyer profile obvious. If most of the firm's billable time goes into transactional or research-heavy matter work at the AmLaw end of the market, Harvey is the spend. If most of the billable time is small-matter operations and the firm runs on Clio, Duo is the spend. If most of the billable time is litigation with serious document volume, Everlaw is the spend. Firms with mixed practice often end up with two of the three — typically Harvey + Everlaw at BigLaw, or Clio Duo + Everlaw at midsize litigation boutiques.

Legal AI accuracy is not optional and not negotiable. **Harvey AI** has invested heavily in evaluation, internal red-teaming, and published case studies with firms like A&O Shearman, Paul Weiss, and PwC Legal. Harvey's positioning is that base LLMs are insufficient for legal use without fine-tuning, retrieval grounding, and citation enforcement — which is the architectural reason for the price tag. Buyers should still demand to see evaluation methodology, accept that hallucinations are still possible especially on jurisdiction-specific questions, and require human review on any output that touches a client deliverable.

**Clio Duo** is honest about its scope. Duo is not pitched as a research engine that will give you binding authority on a complex federal question. It is pitched as a productivity layer that drafts boilerplate, summarizes activity, and reduces typing. The accuracy bar for an engagement letter draft or a time entry suggestion is meaningfully lower than the bar for a 30-page memo on ERISA preemption, and Duo plays in the former category. Per https://clio.com/duo/, the assistant is explicit about citing sources from the firm's own matters where relevant, which scopes the hallucination risk down to firm-internal data rather than open-web legal research.

**Everlaw** has the cleanest evaluation story of the three because predictive coding is a regulated discipline. Courts in the US have spent over a decade accepting TAR (technology-assisted review) workflows with documented precision and recall metrics, and Everlaw exposes those metrics in the review interface. The newer generative features — document summarization, deposition summarization, Storybuilder narrative — sit on top of the same auditable workflow. Lawyers reviewing privilege still see the documents; the AI prioritizes the queue but does not produce the final call without a human in the loop. This is the right pattern, and it is what every legal AI tool should look like.

The cross-cutting rule for all three: never deploy legal AI without a written acceptable-use policy, a sample-output review protocol, and a quarterly accuracy audit. Harvey and Everlaw will help you write those policies in the sales process; Clio Duo customers are more often on their own. State bar guidance from California, New York, Florida, and the ABA's Formal Opinion 512 all converge on the same baseline — lawyers remain responsible for the work product, full stop. If you want the deeper comparison of how these tools handle contract review specifically, our AI contract review cost comparison goes through the accuracy benchmarks.

**Harvey AI** is the right buy when the firm has 50-plus lawyers, an iManage or NetDocuments DMS, a meaningful transactional or research-heavy practice, and a partner-level sponsor willing to drive firmwide adoption. The seat floor, the integration complexity, and the price tag all only make sense at that scale. Harvey at a 15-lawyer firm is the legal-tech equivalent of leasing a Gulfstream to commute to a satellite office — it works, it is extraordinary, and you have set fire to the operating budget. If the firm cannot articulate at least 100 hours per lawyer per year of substantive matter work that Harvey will accelerate, the math does not pencil.

**Clio Duo** is the right buy when the firm is already on Clio Manage, has under roughly 50 lawyers, and is mostly doing small-matter operations — PI, family, employment, immigration, criminal defense, plaintiffs work, small-business advisory. Duo at $40–$100/seat/mo is a rounding error against the time it saves on intake, drafting, and timekeeping. The honest objection is that firms not on Clio should not switch to Clio just for Duo; the broader practice management decision dominates the AI add-on decision. If you are on PracticePanther, MyCase, or Smokeball, evaluate their respective AI offerings rather than migrating to Clio purely for Duo.

**Everlaw** is the right buy whenever the firm has active litigation, investigations, or regulatory matters with document populations of meaningful size. The threshold is not firm size — it is matter type. A 5-lawyer litigation boutique handling commercial disputes for mid-market companies will get more value from Everlaw than a 200-lawyer corporate firm that rarely sees a deposition. The model is also more elastic than the others — you can scope Everlaw to a single matter, get out when the matter ends, and not pay enterprise overhead on quiet years. Per https://www.everlaw.com/pricing/, the per-user-plus-storage model rewards short, intense engagements as much as ongoing book-of-business work.

The cleanest combinations in practice: AmLaw 50 firm — Harvey for substantive work plus Everlaw for litigation matters. Midsize boutique with a mixed book — Everlaw for litigation plus Clio or a competitor for practice management with embedded AI. Solo or small firm — Clio Duo on Clio Manage with no Harvey and Everlaw only as needed per matter. In-house legal department — typically Harvey at scale plus an e-discovery tool (Everlaw or Relativity One) for investigations; Clio is rarely in-house. None of these stacks is theoretical — they are what firms are actually procuring as of June 2026.

**Harvey AI**'s demo will show you a perfect diligence run on a clean SPA with model citations. What the demo will not emphasize is that Harvey is only as good as the firm's document hygiene — if matter folders are inconsistent, if iManage workspaces are a mess, if knowledge management has been an afterthought, Harvey's outputs degrade fast. Firms that succeed with Harvey have also invested in DMS cleanup, taxonomy work, and template standardization. Firms that buy Harvey hoping it will rescue them from disorganized matter data tend to renew quietly disappointed.

**Clio Duo**'s demo will show a polished intake-to-engagement-letter flow. What the demo will not emphasize is that Duo's value scales with how much of the firm's work is already inside Clio. A solo who runs intake in Calendly, billing in QuickBooks Online directly, documents in Dropbox, and only uses Clio for matter tracking will get a fraction of the Duo benefit. The pitch is right for firms that have already consolidated on Clio as the operational system of record. The pitch is wrong for firms using Clio as a glorified contact database.

**Everlaw**'s demo will show Storybuilder pulling a perfect chronology from a deposition. What the demo will not emphasize is that storage is the long-term cost driver and that decommissioning matters cleanly matters. A firm that ingests a TB of data for a matter and forgets to archive or delete after settlement is paying storage for years. The honest answer is to build matter lifecycle policies — ingestion, retention, export, deletion — before signing, and to negotiate storage tiers based on realistic case mix rather than the most expensive recent matter.

The cross-cutting tell: any legal AI vendor that will not give you a written commitment on training data, output indemnification, and exit data export is not ready for serious procurement. All three vendors here are — but you should still ask, in writing, in the master services agreement, every time. As of June 2026 — verify at https://harvey.ai/, https://clio.com/pricing/, and https://www.everlaw.com/pricing/ — the contractual language matters more than the marketing copy.