Harvey vs. CoCounsel vs. On-Premise AI: Which Makes Sense for a Florida Small Law Firm?

A managing partner at an 11-attorney Florida personal injury firm asked us a direct question last quarter: Harvey wants $1,500 per attorney per month, CoCounsel wants $225 per attorney per month, and Mi Assist Legal is a one-time install. What is the actual difference, and which one fits a firm like ours?

This article answers that question. It compares the three categories of legal AI tooling currently being marketed to small and mid-size Florida law firms, with specific attention to how each architecture affects compliance with Florida Bar Rule 4-1.6 and ABA Model Rule 1.6. The goal is not to advocate for one product, but to clarify the decision framework so a managing partner can evaluate the categories on their actual differences.

The Three Categories at a Glance

Category	Representative Product	Architecture	Approximate Pricing	Target Firm Size
Enterprise cloud AI	Harvey	Cloud, hosted	$1,200 to $2,000 per attorney per month	AmLaw 200, 50+ attorneys
Mid-market cloud AI	CoCounsel (Thomson Reuters)	Cloud, hosted	$225 per attorney per month base; higher with add-ons	10 to 200 attorneys
On-premise document search	Mi Assist Legal	Local, firm-owned hardware	One-time install + optional support	5 to 30 attorneys

Pricing data above is current as of 2026 based on public-facing pricing pages and industry reporting. Vendor quotes vary by firm size, term length, and bundled features.

The differences between these three categories are not primarily about feature quality. They are about architecture, pricing model, and compliance posture. Each of those three dimensions affects whether the tool fits a 5-30 attorney Florida firm.

Architecture: Where Does Your Data Go?

The most material difference between Harvey, CoCounsel, and on-premise AI is where the firm's data is processed.

Harvey is a cloud-hosted product. Documents uploaded to Harvey are processed on Harvey's infrastructure (which uses OpenAI's models under the hood per public statements). Data flow: firm laptop or document management system, then Harvey servers, then AI model, then back. Harvey publishes data handling commitments and SOC 2 documentation, but the act of transmitting client data outside the firm is the architectural premise.

CoCounsel, owned by Thomson Reuters since 2023, is also cloud-hosted. The data flow is similar in shape: firm system, then CoCounsel servers, then AI model. CoCounsel publishes data handling and confidentiality terms; the firm's contract with Thomson Reuters governs retention and use.

On-premise AI document search does not transmit data outside the firm. The system runs on hardware located inside the firm's office, typically a Mac Mini or a small server. The AI model and the document index both reside on that hardware. No firm data crosses the firm's network boundary in the course of routine use.

This architectural difference is the foundation for everything else that follows in the comparison. Pricing model, compliance posture, and operational characteristics all flow from where the data is processed.

Pricing Model: The 10-Attorney Firm Math

Consider the actual cost of each option for a 10-attorney Florida firm over three years.

Harvey at $1,500 per attorney per month for 10 attorneys is $15,000 per month, or $180,000 per year. Over three years, that is $540,000. Harvey's pricing is generally not negotiated below low four figures per seat for sub-100-attorney firms based on public reporting; firms below AmLaw 200 are not Harvey's primary target market.

CoCounsel at $225 per attorney per month for 10 attorneys is $2,250 per month, or $27,000 per year. Over three years, $81,000. CoCounsel's pricing is more accessible for the small firm market and is the most common cloud option for firms in the 10-50 attorney range.

On-premise AI document search typically involves a one-time installation cost (hardware plus implementation) and an optional support arrangement. The structure is fundamentally different from per-seat licensing because the cost does not scale linearly with attorney count. Total three-year cost for a 10-attorney firm is generally in the range of $20,000 to $60,000 depending on hardware, document volume, and support level. Exact figures vary; our pricing page explains the structure.

The pricing implication for a small firm is that cloud per-seat models scale with firm growth in a way that on-premise does not. A firm that grows from 10 to 20 attorneys doubles its CoCounsel cost. The same firm using on-premise document search adds incremental seat licenses or processing capacity, but the per-attorney marginal cost is significantly lower.

Rule 4-1.6 and ABA Rule 1.6: Disclosure Analysis

Florida Bar Rule 4-1.6 prohibits a lawyer from revealing information relating to the representation of a client without informed consent, with limited exceptions. ABA Model Rule 1.6 is materially identical. Florida Bar Opinion 24-1 (January 2024) interprets these rules in the AI context, requiring informed client consent before client information is transmitted to a third-party AI tool that retains or trains on inputs.

Each of the three categories has a different posture under this rule.

Harvey and CoCounsel transmit client information to third-party servers as a condition of operation. The vendor's data handling terms determine the retention and use, but the act of transmission is itself a disclosure for purposes of Rule 4-1.6. Florida attorneys using these tools should:

• Review the vendor's data retention and training terms before any client information is entered
• Confirm that vendor terms prohibit training on the firm's inputs
• Obtain informed client consent under Rule 4-1.6 before sending client information to the tool
• Document the consent in the engagement file

On-premise AI document search does not transmit client information to a third party. The data flow stays inside the firm's network. This means the disclosure event that would otherwise require client consent under Rule 4-1.6 does not occur. The other duties under Opinion 24-1 (competence, candor, supervision) still apply, but the consent requirement is not triggered.

This is a meaningful operational distinction for firms whose practice areas involve heightened confidentiality concerns: family law (financial disclosures, custody matters involving minors), immigration (clients whose status is sensitive), criminal defense (privileged communications), and personal injury (medical records subject to HIPAA).

What Each Tool Actually Does Well

Architectural differences aside, the three categories have different feature strengths.

Harvey is built for high-volume litigation document review and complex transactional drafting. The product reflects the workflows of large firms with dedicated litigation support staff, document review attorneys, and case teams of 10+. Harvey's strength is depth of integration with the workflows of an AmLaw 200 firm.

CoCounsel is positioned as a generalist legal AI tool with research, drafting, and document analysis features. Its strength is breadth: it covers multiple workflows in a single product. The Thomson Reuters acquisition added Westlaw integration, which is meaningful for firms that already pay for Westlaw.

On-premise document search like Mi Assist Legal is purpose-built for one workflow: searching the firm's existing document corpus and returning answers grounded in those documents with source citations. It is not a research tool (it does not search outside the firm's documents). It is not a drafting tool (it does not generate first drafts of pleadings or contracts). It is a document retrieval and question-answering system optimized for the firm's own files.

For a 5-30 attorney firm, the question is which workflow has the highest time cost. ABA-affiliated time tracking research consistently shows attorneys at small firms spending 35% to 50% of billable time on document review, research, and information retrieval from existing files. Document search optimization addresses that single largest time bucket.

The Five Questions Before Signing

A managing partner evaluating any of the three categories should be able to obtain a clear answer to each of the following questions before signing a contract. The answers are the basis for a defensible vendor selection decision.

1. Where is our data processed? Is it on the vendor's servers, our own hardware, or a hybrid? What jurisdictions does the data touch?
2. Does the vendor train models on our inputs? What is the contractual prohibition, and how is it enforced? Is there an opt-out, or is it the default?
3. What is the data retention policy? When client information is sent to the tool, is it retained on vendor servers? For how long? Can the firm require deletion?
4. What happens to our data if we cancel? Does the vendor delete it? Within what time frame? Is the deletion auditable?
5. What is the per-attorney cost over five years? Including any anticipated price escalations, what does the firm spend in total? How does the cost scale if the firm grows?

A vendor that cannot give a clean answer to any of these five questions has a process problem the firm should not absorb. A vendor that can answer all five favorably is a candidate for the next stage of evaluation.

When Harvey Makes Sense

Harvey is the right tool when the firm has 50+ attorneys, a litigation or transactional practice with case teams large enough to amortize per-seat licensing, and the budget and procurement infrastructure of an AmLaw 200 firm. For firms below that scale, Harvey's pricing structure is generally not aligned with the firm's economics.

When CoCounsel Makes Sense

CoCounsel is the right tool when the firm wants a cloud-based generalist tool, has clear client consent processes for transmitting confidential information to third-party tools, and can absorb the per-seat cost as the firm grows. CoCounsel's Westlaw integration adds value for firms that already have Westlaw subscriptions.

When On-Premise Makes Sense

On-premise document search is the right tool when the firm has 5-30 attorneys, has a meaningful corpus of internal documents (case files, contracts, correspondence) that attorneys spend significant time searching, has confidentiality concerns that make cloud transmission a compliance burden, and prefers a one-time investment over ongoing per-seat licensing.

The PI firm, family law firm, immigration firm, and real estate firm profiles fit this set of conditions in particular. Practice areas with sensitive client data benefit most from architecture that does not transmit that data outside the firm.

What Mi Assist Legal Does

Mi Assist Legal is an on-premise AI document search system designed specifically for 5-30 attorney Florida firms. The system installs on a Mac Mini or compatible server inside the firm's office. It indexes the firm's case files, contracts, pleadings, and correspondence. Attorneys ask questions in natural language and receive answers with source citations.

The architectural choice is deliberate. For Florida firms in PI, family law, immigration, and real estate, the Rule 4-1.6 posture of an on-premise system is materially different from a cloud system. Our security page describes the deployment architecture in detail. Pricing is structured as a one-time installation rather than per-attorney licensing.

Frequently Asked Questions

Q: Is Harvey worth the price for a small Florida law firm?

For firms below 50 attorneys, the per-seat cost of Harvey generally exceeds the value derived. Harvey's product is optimized for the workflows of large litigation and transactional firms. Small firms typically realize more value from a tool designed for their scale.

Q: Can a small firm just use ChatGPT instead of these tools?

ChatGPT, like other consumer cloud AI tools, transmits inputs to OpenAI's servers. Under Florida Bar Opinion 24-1, this is a third-party disclosure of client information that requires informed client consent under Rule 4-1.6 if any client-related information is included in the input. Most firms find the per-matter consent burden impractical at scale.

Q: Does on-premise AI work for firms outside Florida?

Yes. The architectural advantages (no third-party disclosure, predictable cost) apply regardless of jurisdiction. ABA Model Rule 1.6, which most state bars have adopted in similar form, contains the same disclosure consent requirement that Florida Rule 4-1.6 contains.

Q: How does CoCounsel compare to on-premise document search on accuracy?

The accuracy comparison depends on the workflow. For research questions that require citations to outside sources (case law, statutes), CoCounsel's integration with Westlaw is an advantage. For questions that require retrieval from the firm's own document corpus, on-premise systems have direct access to the firm's documents and return source-cited answers from those documents. The two products are optimized for different retrieval problems.

Q: What is the typical ROI timeline for an on-premise system at a 10-attorney firm?

Firms typically calculate ROI based on attorney time recovered from document search and review tasks. At billable rates of $250 to $400 per hour and the documented 35% to 50% of attorney time spent on document-related work, even a 10% reduction in document search time produces meaningful annualized recovery. Most firms see payback within 12 months on a one-time installation.

---

This article is intended for educational purposes. Pricing data is current as of the publication date and may change. Florida attorneys should consult current Florida Bar Rules, Florida Bar Opinion 24-1, and ABA Model Rule 1.6 in evaluating AI vendor decisions.