AI Paralegal Tool Cost Per Attorney: Casetext CoCounsel, Harvey, Hebbia, Paxton AI, Diligen, EvenUp — Real Vendor Pricing (2026)

**Casetext CoCounsel** is the workhorse. Acquired by Thomson Reuters in 2023 for $650M, it now lives as a CoCounsel-branded layer inside the Westlaw ecosystem. Per https://www.thomsonreuters.com/en/products/cocounsel.html, the product handles legal research, deposition summarization, contract review, and database querying with retrieval grounded in Westlaw's case law corpus. The killer feature is citation reliability — because the retrieval layer is Westlaw, hallucinated citations are far less common than with general-purpose LLMs. The weakness is that it's bundled-pricing-only for most firms and the seat cost (~$500/month when sold standalone) makes it expensive for solos.

**Harvey** (https://www.harvey.ai/) is the BigLaw status symbol. Built on a combination of OpenAI and Anthropic foundation models with custom legal post-training, Harvey is deployed at firms like Allen & Overy, PwC, and a long list of AmLaw 50 shops. It does drafting, M&A workflow automation, research, and litigation prep — but it's only sold via enterprise contracts. There's no self-serve, no monthly billing, no public pricing page. Reported deal sizes put it at roughly $3K-$5K per lawyer per year on multi-year contracts, which means a 500-lawyer firm is writing a $1.5M-$2.5M annual check.

**Hebbia** (https://www.hebbia.com/) is the document-mountain tool. Originally targeted at hedge funds and private equity, it migrated into legal because the underlying problem — searching across 10,000+ documents and synthesizing answers with citations — is the same as legal diligence. Hebbia's 'Matrix' product runs parallel LLM queries across massive document sets and returns structured tables, which is gold for M&A diligence, regulatory investigations, and large litigation document reviews. Pricing is enterprise-only, typically $25K-$150K/year depending on user count and data volume.

**Paxton AI** (https://www.paxton.ai/pricing) is the disruptor. Founded in 2023, Paxton publishes prices openly — Personal at $9/month, Pro at $79/month, Premium at $149/month — and targets solos and midsize firms that can't justify $500/seat for CoCounsel. It does legal research with citation grounding, document drafting, contract review, and case analysis. It's not as deep as Harvey on enterprise workflow, and it doesn't have Westlaw's database, but for a solo lawyer doing trusts, family law, or small commercial work, it covers 80% of the job at 6% of the cost.

**Diligen** (https://diligen.com/) and **EvenUp** (https://www.evenuplaw.com/) are the specialists. Diligen does AI contract review for due diligence — point it at a data room of 5,000 contracts, get back a structured analysis of change-of-control clauses, MAC provisions, and indemnification caps. EvenUp is laser-focused on personal injury — it ingests medical records and generates demand letters, priced per case at $100-$300. Neither tool is a paralegal replacement across the board; they're paralegal replacements for one specific workflow each, and they're priced accordingly.

Start with the small-firm math. **Paxton AI Premium** at $149/month per seat (https://www.paxton.ai/pricing) lands at $1,788/year per attorney. For a 5-lawyer firm, that's $8,940/year — less than the cost of a single junior paralegal for one quarter. The tradeoff is that you lose Westlaw's case database, you lose enterprise SSO unless you're on Premium, and you're trusting Paxton's retrieval layer rather than Thomson Reuters' editorial team.

Step up to **Casetext CoCounsel**. Sold standalone, it runs roughly $500/seat/month per Thomson Reuters' published pricing references (https://www.thomsonreuters.com/en/products/cocounsel.html), which is $6,000/year per attorney. For most firms it's sold as a bundle with Westlaw, where the marginal cost is lower — but the total Westlaw + CoCounsel package for a 20-lawyer firm can easily exceed $200K/year. The justification: research time drops, citation reliability is high, and the workflow integrates with iManage and Microsoft 365 natively. If you're already paying for Westlaw, adding CoCounsel is usually the right move.

**Harvey** is BigLaw economics. Reported pricing of $3K-$5K per lawyer per year (per public reporting on procurement deal sizes; Harvey does not publish prices at https://www.harvey.ai/) means a 200-lawyer firm signs a $600K-$1M annual contract, typically on a 2-3 year term. The pitch isn't 'replace a paralegal' — it's 'every associate has a senior-associate-level assistant available 24/7 across drafting, research, and workflow.' Whether that math works depends entirely on how aggressive your firm is about retraining associates to use it daily; if 60% of seats sit idle, you've lit money on fire.

**Hebbia** pricing scales with document volume and use case rather than seat count. A typical mid-firm M&A practice deployment in 2026 runs $50K-$100K/year per https://www.hebbia.com/ reseller reporting. Enterprise deployments at hedge funds and AmLaw 50 firms cross $150K. The ROI calculation is different from per-seat tools: if Hebbia saves 200 hours per deal across the diligence team and the firm runs 30 deals a year, the math is obvious. If you're doing 4 deals a year, you're vastly overpaying.

**Diligen** at $10K-$50K/year (https://diligen.com/) and **EvenUp** at $100-$300 per case (https://www.evenuplaw.com/) are the variable-cost plays. EvenUp specifically is the only one in this list that maps cleanly to lawyer billing — you pay per output, not per seat. For a PI shop doing 500 cases a year at $200 average, that's $100K, all directly attributable to revenue-generating files. As of June 2026 — verify at evenuplaw.com/pricing — the per-case model is the most defensible expense in this entire vendor list from a CFO's perspective.

**Casetext CoCounsel** integrates natively with Westlaw, Practical Law, Microsoft 365 (Word and Outlook), and iManage. If your firm already runs on the Thomson Reuters stack, CoCounsel slots in with single sign-on, document context, and minimal IT lift. The downside: if you're on NetDocuments instead of iManage, integration is shallower, and the value of the bundle drops because you're paying for a Westlaw subscription you don't need.

**Harvey** integrates with Microsoft 365, iManage, Litera, and most BigLaw document management stacks. Deployments are sales-engineering heavy — Harvey sends solutions architects who spend weeks tuning the platform to your firm's templates, precedent libraries, and practice-group workflows. This is a feature, not a bug, at the AmLaw 50 level, but it's why the contract minimums exist. You can't just buy 10 Harvey seats and roll them out next Tuesday.

**Hebbia** is built for data rooms. Native integrations with iManage, NetDocuments, SharePoint, Box, Datasite, and Intralinks mean you can point it at a 10,000-document deal room and have it producing structured output within hours. The 'Matrix' UI generates spreadsheet-style outputs that map directly to how diligence is reported, which is why it lands with corporate practice groups and PE firms specifically.

**Paxton AI** is browser-first. It integrates with Microsoft Word via add-in, supports cloud document import from Google Drive and OneDrive, and runs primarily in the web app. For solos, this is fine — you're not running a 50-person practice with enterprise DMS requirements. For midsize firms, the lack of deep iManage or NetDocuments integration matters, and it's why Paxton ceiling is typically around the 25-50 attorney firm size.

**Diligen** plugs into deal rooms and document repositories; **EvenUp** plugs into case management systems like Filevine, Litify, and Smokeball. Both are vertical workflow tools, not horizontal platforms — which means integration scope is narrower but deeper. EvenUp specifically pulls medical records, generates the demand, and pushes the output back to your case file with minimal manual touching.

For a **solo or 2-5 lawyer practice** doing general commercial, family, or trusts and estates work: **Paxton AI Premium** at $149/month (https://www.paxton.ai/pricing) is the right answer. You get citation-grounded research, drafting, and contract review at a flat predictable cost. The argument against — 'but I want Westlaw's case database' — is real only if you're litigating frequently in jurisdictions where Westlaw's headnotes and KeyCite are mission-critical. For 80% of solo practices, they're not.

For a **midsize firm of 10-50 lawyers** already on Westlaw: **Casetext CoCounsel** bundled with your existing Westlaw subscription. The marginal cost is bearable, the integration is native, and the citation reliability is the best in the market for litigation work. Don't bother with Harvey at this size — you don't have the procurement, IT, or change-management muscle to deploy it, and the per-seat cost is irrational.

For an **AmLaw 100 firm with deep procurement**: **Harvey** is the obvious play for general drafting and associate augmentation, **plus Hebbia** for M&A and large-document review, **plus CoCounsel** for litigation research where Westlaw is required. Yes, that's three platforms. Yes, the total spend crosses $2M/year for a 300-lawyer firm. The alternative — running on Google searches and junior associate hours — is more expensive when you actually price out the realized loss in associate efficiency.

For a **personal injury firm** of any size: **EvenUp** at $100-$300/case (https://www.evenuplaw.com/) is the highest-ROI single purchase in legal AI right now. Demand drafting is the single most time-consuming, lowest-leverage paralegal task in PI practice, and EvenUp's per-case pricing makes it a pure cost-of-goods-sold line item. Pair it with Paxton AI for general legal research and you've replaced most paralegal demand work for under $20K/year for a mid-sized shop.

For a **corporate M&A or PE-adjacent practice**: **Hebbia** plus **Diligen** is the pairing. Hebbia handles freeform diligence questions across the entire data room; Diligen handles structured contract review of the contract corpus specifically. Combined cost in the $60K-$150K/year range is reasonable for a practice that's running 20+ deals annually. As of June 2026 — verify at hebbia.com — Hebbia is in active rollout at multiple PE-backed law firm consolidators.

Every vendor in this article will tell you they don't train on customer data. Read the actual data processing agreement before you believe them — and especially before you upload privileged documents. **Casetext CoCounsel** runs on Thomson Reuters infrastructure with US data residency and no model training on customer content per the published TR data policy. This is the safest answer for most US firms by default because Thomson Reuters has 100+ years of dealing with attorney-client privilege concerns and the contractual language reflects that.

**Harvey** runs on Microsoft Azure with isolated tenants per customer. No training on customer data; data is encrypted at rest and in transit; SOC 2 Type II compliant per the Harvey trust center. For firms with EU data residency requirements, Harvey supports EU-region deployment on enterprise contracts. The catch: Harvey uses OpenAI and Anthropic foundation models, which means data flows through those providers' inference endpoints — both vendors have zero-data-retention agreements, but if your GC is concerned about US foundation model providers touching privileged data at all, Harvey is harder to defend than a self-hosted option.

**Hebbia** offers VPC deployment for enterprise customers, which means the platform runs in your cloud tenant rather than Hebbia's. This is the right answer for hedge funds and the most paranoid law firm IT teams. Standard SaaS deployment uses Hebbia's cloud with no training on customer data. SOC 2 Type II is standard. Hebbia publishes its security posture at https://www.hebbia.com/security.

**Paxton AI** doesn't train on customer data per https://www.paxton.ai/pricing and the linked privacy policy. It uses OpenAI, Anthropic, and Google models under the hood with their respective enterprise terms. For solos and small firms, this is fine. For anyone handling regulated data (HIPAA-covered medical records in PI work, for example), you need to confirm BAAs are in place at your tier — Paxton does support BAAs on Premium, but it's worth verifying directly.

**Diligen** and **EvenUp** both publish data handling policies that prohibit training on customer content. EvenUp specifically handles HIPAA-protected medical records and signs BAAs as standard. Diligen's diligence platform operates with data isolation per deal. None of the tools in this article support fully on-premise deployment — if 'no data leaves our network' is a hard requirement, you're not on this list, you're building an in-house RAG system with Llama or self-hosted Mistral and accepting the build cost.

At the **$9-$149/month Paxton AI** tier, you give up Westlaw's case database, deep iManage integration, dedicated customer success, and the ability to deploy at scale across a 100-lawyer firm with consistent training. What you get: predictable cost, fast onboarding, and a product that genuinely does the core paralegal-augmentation job for solo and small-firm work. Don't oversell this — Paxton is not Harvey, and pretending it is leads to disappointed senior partners.

At the **$500/seat/month Casetext CoCounsel** tier, you give up flexibility on model choice (you're using whatever TR ships), and you're locked into the Westlaw ecosystem. What you get: the most reliable citation grounding in the market, native integration with iManage and Microsoft 365, and the brand defense argument — when you tell your malpractice carrier you're using Thomson Reuters tooling, the underwriter doesn't blink.

At the **$3K-$5K/lawyer/year Harvey** tier, you give up published pricing transparency, fast deployment, and the ability to start small. Harvey deals are minimum 6-figure annual contracts (https://www.harvey.ai/), typically 2-3 year terms. What you get: an extensively trained legal AI deployed with sales engineering support, custom workflow tuning, and the operational maturity to actually drive adoption across hundreds of attorneys.

At the **$25K-$150K/year Hebbia** tier, you give up general-purpose drafting capability — Hebbia is a document-analysis tool, not a drafting assistant. What you get: the best multi-document analysis platform in the market, structured tabular outputs that map directly to diligence reporting, and the ability to handle data rooms that would crush other tools. If your practice is M&A, regulatory, or large-litigation document review, Hebbia justifies the cost. If it's not, Hebbia is the wrong tool.

At the **$10K-$50K/year Diligen** and **$100-$300/case EvenUp** tier, you give up generalization entirely. These tools are vertical specialists. The benefit is that they outperform horizontal platforms within their respective niches by a wide margin and the per-output pricing on EvenUp specifically maps to revenue better than any other model in this list. Buy them additively, not as replacements for horizontal tools.

Implementation services. **Harvey** and **Hebbia** deployments routinely include $25K-$100K in implementation, training, and workflow customization fees that don't appear on any vendor pricing page because they're not on any vendor pricing page. Procurement teams need to budget for this explicitly. **Casetext CoCounsel** when sold standalone is mostly self-serve; when bundled with Westlaw, training is usually included in the Westlaw success program.

Change management and training. The single biggest reason firms waste money on legal AI is buying seats they don't use. A 50-lawyer firm that buys 50 Harvey seats and gets 12 lawyers actually using the tool daily has wasted 76% of the spend. Budget for an internal champion at minimum, ideally a partial-FTE knowledge management lead whose job is driving adoption. This isn't optional — every firm that's published case studies on successful legal AI rollouts has someone in this role.

Model usage overages. **Paxton AI Premium** at $149/month includes 'unlimited' queries with fair-use limits per https://www.paxton.ai/pricing. **Harvey** contracts typically include usage-based components on top of seat fees for the heaviest enterprise workflows. Read the contract for usage caps before you scale to a 300-attorney pilot — overage clauses can double the effective per-seat cost if you're not careful.

Integration and DMS connector fees. Connecting any of these tools to iManage, NetDocuments, or a non-standard DMS often involves a one-time setup fee in the $5K-$25K range. Some vendors include this; many don't. This is the kind of line item that procurement misses and then becomes a budget surprise in Q3.

Audit and compliance review. Your malpractice carrier may require an annual security review of any AI tool that touches privileged work product. Some vendors charge for the documentation packages required; others provide them free. Build this into year-2 budget planning — it's a recurring cost, not a one-time setup.

Pick three vendors maximum. Trying to evaluate all six in this article in parallel guarantees a sloppy decision. The pragmatic short list for most firms is: one horizontal platform (**Paxton AI**, **CoCounsel**, or **Harvey** depending on firm size), one document-analysis tool if you do diligence (**Hebbia** or **Diligen**), and **EvenUp** if you do PI. Don't evaluate Hebbia if you don't do diligence — you'll discover it's amazing at a thing you don't need.

Bring real work. Generic demos from vendor sales engineers are worthless. Pick three actual matters from the last 90 days — one research task, one drafting task, one document review task — and have the vendor run their tool on those matters during the evaluation. Measure time saved against the actual hours billed on those matters. This is the only number that matters.

Compare against your current cost. A paralegal at $75K fully loaded costs ~$60/hour. A first-year associate at $250K fully loaded costs ~$150/hour. The right comparison for every AI tool is not 'does this cost less than the subscription' — it's 'does this save more paralegal or associate hours per attorney than it costs.' If a $500/seat/month CoCounsel deployment saves 10 paralegal hours per attorney per month, the math is overwhelmingly positive ($600 saved vs $500 spent, before associate leverage).

Get the security review done in parallel, not after. The biggest delay in legal AI deployment isn't picking the tool — it's the malpractice carrier and IT security review afterward. Start the security review the day you start the evaluation, not the day you sign the contract. Every vendor in this article can supply SOC 2 reports, DPAs, and BAAs on request; collect them on day one.

Get the partner committee bought in before the procurement decision, not after. The fastest way to waste $200K on a Harvey contract is to sign it without the litigation partners having tried the tool. Run a 20-attorney pilot, have the pilot users demo their work product to the partner committee, and let the partners make the call. As of June 2026 — verify at harvey.ai for current deal terms — Harvey runs pilot programs that are explicitly designed to support this internal-sell motion.