ContractKen vs LegalOn: how they compare in 2026
LegalOn fits a team that wants review to connect to intake, a signed agreement store and legal department administration. Its prebuilt playbooks provide a broad starting set, and its higher packages add the workflow around the review itself. ContractKen is more focused on the lawyer drafting and negotiating in Word, with detailed fallback positions and a choice between firm rules and comprehensive clause analysis. Library counts are not directly comparable: LegalOn counts playbooks, while ContractKen's larger number counts clauses. The commercial distinction is clearer. LegalOn scopes its packages through sales, whereas ContractKen exposes a standard per user review price. Teams considering either should also distinguish the contract workflow they need from the provider permissions, retention rules and security assurance governing it.
At a glance
All 15 axes, side by side
The same grid applied to every vendor in the index, graded from public sources. Hover a grade to see what the letter means on that axis.
AI Centrality
How much of the product is actually AI. Whether the machine learning is the mechanism the buyer is paying for or a feature layered onto conventional software, and whether the vendor is specific about which is which.
Models classify clauses, compare negotiation positions, explain deviations and generate contract drafts or proposed edits. The current pipeline combines language inference, entity recognition, retrieval from approved material and generative models selected for the task. These functions are central to the review and drafting work. The Word application also retains useful nonmodel components: a shared clause library, playbook administration, formatting checks and reference validation. Users can organize approved language and maintain negotiation standards alongside the AI analysis. ContractKen thus joins model driven legal work to an established editing and knowledge workflow, rather than treating every formatting or storage operation as artificial intelligence.
Review reads a contract against each playbook guideline in turn and drafts redlines. Assistant answers questions about the open contract in Word or the browser, drafts fallback language and issues lists, and runs one click skills that extract terms, check definitions and summarize obligations. The Playbook Agent builds playbooks from a team's policies, templates and past redlines. The Intake Agent asks requesters follow up questions and routes a complete matter, classified by contract type, urgency, counterparty and deal value, and the Triage Agent screens low risk agreements against the playbook. Vault extracts key data, dates and obligations from the signed repository into a table a team can filter, and answers questions such as which contracts renew in the next 90 days. Translate pairs DeepL with LegalOn's own translation agent and sends back only the changes in the counterparty's language. All of it runs on models applied to playbook content that LegalOn's attorneys write.
Citation Accuracy and Hallucination Disclosure
Whether the vendor publishes measured accuracy on citations and assertions, grounds output to primary sources, and says plainly what its system does when it does not know. Legal has a documented public record of fabricated citations reaching filed briefs, so an untested claim of accuracy is not evidence.
Review findings connect to the relevant contract passage, and generated explanations draw on the customer's playbooks, clause library and prior agreements. Retrieval preserves section structure, definitions and cross references instead of splitting text without that context. Drafted clauses identify whether they came from a precedent, approved library language or a playbook requirement. Low confidence suggestions are flagged for review. The models undergo internal classification tests before deployment, but current numerical results, a reproducible test set and error rates for generated legal conclusions are not specified. A research result about similar legal models is separate from ContractKen's production accuracy.
Review grounds each issue in a playbook standard written by LegalOn's attorneys or by the customer, with the guidance and sample clauses behind it. Each guideline runs as its own check against the contract, about two dozen in parallel, rather than one pass over the whole document. The 2026 Contract Review Benchmark, released in June, set LegalOn against 11 general purpose AI systems across 3,282 pairwise reviews on 21 guidelines. An LLM judge, separate from the systems tested and blind to authorship, picked the more accurate, complete and useful review, and legal experts validated a sample of its outputs. LegalOn ranked first on all 21 provision types and finished a full review in 2.3 seconds. A downloadable report sets out four failure modes of general models on contract provisions.
Autonomy and Oversight Model
What the system decides on its own, what a lawyer must approve, and whether the vendor documents where the review point sits. A tool that drafts under review and a tool that files without one are different products and different risks.
Playbook Driven Review checks preferred, fallback and walkaway positions; Comprehensive Review provides an alternative when no organizational playbook exists. Risk sensitivity can be adjusted, and the playbook framework distinguishes deviations that require escalation to a partner. Reviewers navigate to the exact clause, inspect an explanation and approve, modify or reject a proposed change. No edit enters the agreement without explicit human approval. Drafts receive a playbook compliance report before use, and administrators control who can change the playbook itself. These controls separate automatic analysis from the lawyer's decision about the final language and the route for an unacceptable negotiating position.
Routine paper moves on its own and judgment stays with the user. The Triage Agent screens low risk agreements against the playbook, approves the standard ones and escalates the exceptions, and the Intake Agent follows up with requesters until intake is complete. Every agent returns output for review, with legal setting the guardrails and keeping final approval. Review ranks each issue low, medium or high with the playbook guidance behind it, and redlines land as tracked changes a user accepts or rejects. One click AI Revise in Word works through the same tracked changes. Who sets the line between standard and nonstandard paper, and what happens after a wrong approval, is not described.
Operational and Outcome Evidence
Named, dated evidence that the product works in production at real firms or legal departments. Case studies with figures and identified customers count. Unattributed testimonials and launch announcements do not.
Named practitioners describe using ContractKen in contract work. Aseet Patel, a lawyer and legal technology founder, uses it for agreements and term sheets before sending work to outside counsel for final review. Sharon Zachariah, an innovation lawyer and former partner, describes using it after drafting or reviewing client contracts. These accounts identify people and actual tasks, but give no dated baseline or measurement method. Separate drafting illustrations promise substantial reductions in time to a first draft, and the review calculator estimates savings from assumed workloads. Those illustrations do not establish measured outcomes for either named practitioner or the current AI pipeline.
Four customer stories pair a named company with figures. TriHealth, a Cincinnati health system whose legal team handles more than 1,500 contracts a year, cut review time by 75%. Its associate general counsel says clinical trial agreements that took hours now take about 20 minutes. Industrial Service Solutions saves its lead reviewer more than 15 hours a week and cut turnaround by 70%. Achievers, an HR technology company, reports NDA review time down 70% and $1,000 to $2,000 saved per third party contract. MCEA Holdings, a Japanese holding company, handles 50% more contracts without added headcount and resolves matters 20% faster. Each story names the speaker and role and sets out the starting point, such as a two week turnaround at Industrial Service Solutions and 15 to 20 minutes per NDA at Achievers. The site counts more than 9,000 customers.
Privilege and Confidentiality Posture
How client confidences are handled: attorney client privilege and work product treatment, segregation of one client matter from another, whether client data trains any model, and what the vendor commits to in writing rather than in marketing.
The security commitments treat content as confidential work product, restrict staff access to necessary support under confidentiality obligations and separate customer tenants with individual encryption keys. The Moderation Layer masks sensitive text locally, offers a preview and validates the sanitized version before external model processing. Public or shared model training is excluded in the security FAQ, while the architecture also describes controlled feedback learning and private customization. The general terms reserve content review for service improvement. Retention and purge controls exist, but internal matter walls and a consistent contractual training restriction are not established across these different surfaces.
Customer content stays the customer's property under section 7.2 of the subscription terms, with a license to LegalOn only to provide the service. Each customer account runs in a segregated environment with strict access controls, and data is encrypted at rest and in transit. Azure OpenAI processes content under terms that it is not used to train, retrain or improve the models and is not stored for any period, including for abuse monitoring. Section 7.3 lets LegalOn aggregate or deidentify customer content into analyses it owns and uses to improve the service, provided they cannot be linked to the customer. Section 2.2 states that LegalOn is not a law firm and that communications between LegalOn and the customer carry no attorney client privilege. Work product handling is not addressed.
UPL and Professional Responsibility Posture
Whether the vendor is clear that it supplies a tool rather than legal advice, who its audience is, and how it addresses unauthorized practice of law, competence and supervision duties, and jurisdiction limits. ABA Formal Opinion 512 is the reference point. Where the advice line is not the duty a product raises, the axis is read through the nearest professional duty it does raise: judicial conduct rules and the reviewing duty for products sold only to courts, and the duty to bill for time actually spent for products that draft time entries.
The terms distinguish ContractKen from a law firm or attorney and state that its information is not legal advice. They direct people needing advice to a licensed lawyer and do not create a professional relationship with the vendor. The product reinforces supervision through source inspection, playbook controls and required approval of generated changes. Its confidentiality explanation also engages with lawyers' duties under ABA Formal Opinion 512. Standard clauses include common law jurisdiction notes, but that coverage does not define a complete set of professional practice limits. The trial audience includes people who are not lawyers as well as legal teams.
Section 2.2 of the subscription terms says LegalOn is neither a law firm nor an attorney and is no substitute for an attorney's advice, and the website terms add that it gives no legal advice. Solution pages sell review to procurement, sales and contract management teams as well as lawyers, and the law firm page offers playbooks that adjust to each client's risk profile. Competence and supervision duties are not addressed, and international playbooks give guidance across 23 countries with no stated limit on where the product may be used.
AI Governance and Bias Disclosure
Published governance over model behavior: who owns it inside the vendor, what is tested before release, and what is disclosed about disparate output across matter types, parties, or populations.
ContractKen describes a controlled model update process using feedback from accepted, modified and rejected suggestions. Those signals are aggregated and reviewed before supervised retraining, rather than changing the model instantly after each user action. Updated models face held out tests using precision, recall and F1 measures; performance must remain stable or improve before release. Administrators can also restrict sensitive information through redaction rules. This is a concrete development and release framework. A named person accountable for AI governance, current test results and findings about uneven performance across jurisdictions, contract types or groups are not specified.
The 2026 Contract Review Benchmark tests LegalOn against other AI systems. Pairwise reviews were judged by an LLM blind to authorship, and legal experts validated a sample of its decisions. Results are reported by provision type, with a report on four failure modes of general models, and a workflow survey of 500 legal professionals sits beside it. Attorneys on staff write the playbooks and keep them current as laws and standards change. An owner for model governance is not named.
AI Safety and Data Stewardship
Retention, deletion, access control, and what happens to prompts and documents after they are processed. Whether the vendor states its subprocessors and its incident practice, or leaves the buyer to assume.
Administrators can request an immediate purge of contracts, prompts, logs and backups. Operational logs normally remain for 30 days, with a contractual option to set that period to zero. Enterprise controls include single sign on, administrator multifactor authentication and permissions for playbook uploads, draft review and data export. Staff access is restricted and logged. The security FAQ states continuous monitoring and material incident notification within 72 hours or a faster legal deadline. A complete current subprocessor register and the DPA require a request, and the default retention period for application prompts and generated output is not separately stated.
Each customer account runs in a segregated environment with strict access controls, data is encrypted at rest and in transit, and LegalOn runs annual penetration tests, regular vulnerability scans and a patch management process. Contracting plans add enterprise single sign on, multifactor authentication and IP allow lists. The data processing addendum keeps a subprocessor list with functions and locations in the trust center, currently Google Cloud Platform, Auth0, Microsoft Azure for the OpenAI service and Datadog. A new subprocessor comes with prior written notice and ten days to object, and a personal data breach is reported to the customer without undue delay. Under section 9.2 of the subscription terms a customer can export content during the term, and LegalOn may delete it 30 days after the term ends. Trust center controls include data retention procedures, deletion of customer data on exit and tested continuity and disaster recovery plans.
AI Liability and Recourse
What the vendor stands behind contractually when its output is wrong. Indemnities, caps, carve outs, insurance, and whether any of it is published or only reachable through a negotiated agreement.
The public terms disclaim accuracy, completeness and noninfringement warranties and cap aggregate liability at the greater of $100 or fees paid in the preceding 12 months. Exceptions concern death, property damage or injury from gross negligence, and fraud or fraudulent misrepresentation. Customers indemnify ContractKen for specified claims. The security FAQ offers a stronger position, including an IP indemnity, performance warranty, cyber and professional insurance and different liability exceptions. Paid customers may instead have an Enterprise Services Agreement, whose text is not available here. Those stronger commitments therefore do not clearly replace the default terms for every subscriber.
Section 12 of the subscription terms caps each party's liability at the fees paid or payable in the 12 months before the claim. For a customer with no payment obligation, such as a trial, the cap is $1,000. Lost profits, lost data and consequential damages are excluded, and the cap does not limit the customer's own indemnity or payment duties. Against third party claims that use of the service infringes a United States patent, trademark or copyright or misappropriates a trade secret, LegalOn defends or settles and pays damages finally awarded. The indemnity does not reach the customer's negligence, abuse or misapplication of the service. The warranty promises that the service performs materially as documented, and the rest of the service is provided as is. The trust center holds a 2025 cyber insurance policy released on request, and California law governs the terms.
Practice Systems Integration Depth
How deeply the product reaches into the systems legal work already lives in: document management such as iManage and NetDocuments, Word and Outlook, contract lifecycle management, matter management, e-billing, and court filing systems.
The Word add in reads the active agreement chosen by the user, rather than scanning other files or email. Review findings navigate to the underlying clause. Approved suggestions return through Office.js as ordinary tracked changes with explanatory comments, and the privacy mapping restores original names and values. Users supply their playbooks, precedents and clause language, then review output within the same document. Standard setup requires Microsoft Word and includes onboarding support. Integrations with systems such as iManage belong to the separately quoted custom workflow offer; they are distinct from the detailed, standard Word editing connection.
Word is the main working surface, with review, redlining, drafting, questions and one click AI Revise built on Word's tracked changes. Requests arrive from Slack, email and custom forms, with Microsoft Teams also included in the Productivity Suite intake options, and SharePoint, Google Drive and Box connect for direct access to files. A public REST API covers three areas. The Contract and Files API moves contract files and data in and out, and the User Management API manages users, groups, workspaces and departments. The Matter API creates matters from a ticketing tool, form or CRM and keeps status, assignees and messages in sync. Access uses OAuth 2.0 client credentials and is scoped to the workspaces a user already holds. iManage and NetDocuments are not named.
Deployment Model and Data Residency
Where the software runs and where the data sits. Multi tenant cloud, single tenant, private deployment, on premises, and whether region of residence is a published option or an enterprise conversation.
The standard service combines a Word add in with a hosted analysis pipeline. Sensitive entities can be replaced locally before sanitized text reaches ContractKen's servers and external AI providers. Primary hosting is on AWS, with European Union or United States residency available on request. Regulated teams can obtain private inference in their own Azure tenant or virtual private cloud, and enterprise customers can supply an endpoint. These options distinguish local preparation from remote analysis. Exact cloud regions, the location of every provider's processing and the configuration or price differences between residency choices are not specified.
Hosting runs in the United States on Amazon Web Services and Google Cloud Platform, with a segregated environment for each customer account. ISO 27017 certification covers the controls for multi tenant cloud operation. The data processing addendum brings in standard contractual clauses and the UK addendum for personal data moved from Europe, and the privacy policy says personal information may move to the United States or Japan. No single tenant, private or regional option is offered, and where Azure OpenAI processes model calls is not stated.
Security Certifications and Trust Center
Independent attestation a buyer can pull without a sales call: SOC 2, ISO 27001, penetration test summaries, a trust center with current reports and named scope rather than a badge image.
ContractKen describes SOC 2 Type II certification as in progress and its controls as aligned with ISO 27001 and ISO 27701. The security FAQ also mentions a report under a nondisclosure agreement, without identifying a completed audit period or service scope. Encryption, tenant isolation, administrator authentication, annual independent penetration testing and customer audit access are separate operating controls. Penetration test summaries and a security paper are available on request. Its own certification remains unfinished, without a dated independent audit, a named auditor or a defined assurance scope covering the ContractKen service.
SOC 2 Type II, ISO/IEC 27001:2022 and ISO/IEC 27017:2015 certification are stated. The trust center holds the 2025 SOC 2 report in English and Japanese and the 2025 ISO 27001 and 27017 certificates. A 2025 cloud web penetration test, a network vulnerability assessment and security white paper v1.3 sit beside them, all released through a request for access. Badges on the integration and pricing pages name ISO 27007 and ISO 27011 where the security page names 27017.
Model Supply Chain Disclosure
Which models sit underneath, whose they are, where they run, and whether the vendor commits to telling customers when that changes. A legal buyer inherits every dependency it cannot see.
The architecture identifies DeBERTa for clause classification and natural language inference, plus spaCy and custom entity types for recognition. Generative models handle explanations and edits after retrieval from approved material. The security FAQ names OpenAI and Google as example API providers, while enterprise customers can bring their own endpoint. Routing selects models by task and can change as performance improves. Exact generative model families, versions and processing regions are not specified. The 30 day notice commitment concerns material changes to data handling or service levels, rather than every substitution of a model in the pipeline.
Microsoft's Azure OpenAI service is the named model provider for review and drafting, under terms that it does not train on or store customer data, including for abuse monitoring and debugging. Translation runs on DeepL alongside LegalOn's own translation agent. The subprocessor list places Microsoft Azure beside Google Cloud Platform, Auth0 and Datadog, and a new subprocessor comes with prior written notice. Review runs focused checks per guideline in parallel. Which models serve those checks, and where they run, is not stated.
Commercial Transparency
Whether a buyer can learn what this costs without entering a sales process: published rates, the unit being charged, what sits behind an enterprise tier, and what implementation adds.
The standard Word subscription costs $149 per user per month on monthly billing or $119 with annual billing. It has no minimum seat requirement and includes unlimited review and redlining, a clause library, playbooks, formatting, onboarding and training. A guided trial lasts 14 days, and cancellations or seat reductions can receive a prorated refund. Custom AI and workflow projects use a quoted proof of concept lasting eight to 12 weeks, including usage and customization. Standard installation is included; custom implementation support is also described as included, but the project fee and enterprise deployment price are not stated.
Pricing is set in a sales conversation, and the pricing page lays out three plans without figures. Core Review, for solo attorneys and fractional general counsel, includes unlimited chat, review and redlining, 135 or more playbooks, a document repository, more than 100 templates and the Word add in. Contracting Suite adds custom playbooks, the Playbook Agent, Vault and Vault Projects, team training, dedicated support and enterprise sign on. Productivity Suite adds Matter Management with intake and triage agents, a matter dashboard and matter intelligence. Every plan includes unlimited usage and guided onboarding. Entity Management, Board, Translate, international playbooks and managed playbooks are further modules.
Firm and Practice Coverage
Who the product is actually built for. AmLaw, midlaw, small firm and solo, in house departments, government and courts, and which practice areas are supported rather than merely claimed.
Law firms and internal legal teams can review commercial agreements, draft from prior transactions and maintain shared negotiation language. Examples include nondisclosure, service, software, employment, supply, lease and acquisition agreements. Prebuilt clauses cover common law jurisdictions including the United States, United Kingdom and Australia, with jurisdiction notes and tags for custom language. Separate playbooks can serve different teams, contract types or jurisdictions. Multilingual review is described broadly, but a tested language matrix and unsupported practice boundaries are not specified. The product centers on transactional drafting and negotiation; its clause guidance does not establish a general legal research or litigation service.
Buyer pages cover in house legal, legal operations, procurement, contract management, sales and law firms, and industry pages cover construction, financial services, business services, private markets, healthcare, manufacturing and software. Playbooks are specific to contract type and to whether the customer sends or receives the paper, and international playbooks cover common commercial contracts in 23 countries, from the United Kingdom to Singapore. Translation runs across 28 or more languages. The product covers contracting work from intake to signed agreements, plus entity and board records. Litigation and legal research are outside it.
The 12 legal signals, side by side
Recorded rather than graded. These are the questions a practitioner has to answer before a tool touches a client matter, and the answers are taken from public material only.
Client Data in Training
Can material a lawyer puts into this product be used to train a model?
Section 8 permits review or editing of content for "operating and improving the Service" without a model training exclusion. The security FAQ excludes training public or shared models, while the architecture describes aggregated lawyer feedback used in controlled retraining and private customization. Another statement says no customer data trains models. The Enterprise Services Agreement may supersede the general terms, but its training clause is not available in the public agreement.
Section 7.3 of LegalOn's subscription terms, last modified 1 June 2026, allows LegalOn and its affiliates to aggregate or deidentify customer content, alone or combined with data from other sources. The resulting analyses may be used for internal business purposes "including to improve the Services", and LegalOn owns them and may disclose them as long as they cannot reasonably be linked to the customer. The data processing addendum keeps the same right to use deidentified or aggregated customer data to improve LegalOn's systems after the contract ends.
No clause carves model training out of that use. At the model layer, Microsoft's Azure OpenAI service runs under protections that keep customer data out of training, retraining or improving its models.
Prompt and Output Retention
How long does the product keep what a lawyer typed, and can that be set to zero?
Administrators may request immediate deletion of contracts, prompts, logs and backups. The security FAQ gives operational logs a 30 day default and allows that period to be set contractually to zero. It does not separately define a default window for application prompts or generated answers. The privacy policy's period after account termination concerns personal information and does not establish how long AI interactions remain during active use.
Model calls through Azure OpenAI leave no customer data stored for any period, including for abuse monitoring and debugging. Contracts in Vault stay for the subscription term, a customer can export them, and LegalOn may delete them 30 days after the term ends. Personal data is kept as long as reasonably necessary, and no customer setting for retention during the term is described.
Ethical Walls and Matter Segregation
Does retrieval respect the firm’s ethical walls, or can the model read across them?
Customer tenants are logically separated and use individual encryption keys. Enterprise roles control who uploads playbooks, reviews drafts or exports information, and shared precedents are available to authorized team members. These controls separate organizations and administrative activities. A permission model that divides opposing matters within one firm, or carries a connected document system's ethical walls into retrieval at query time, is not specified in the standard Word workflow.
Inside a customer, contracts are organized by workspace, project or department, and workspace access is set by user group, with changes cascading to every user in the group. API calls are scoped to the workspaces a user already holds. Each customer account runs in its own segregated environment. These permissions govern contract access and the scope of API responses; walls at the level of a single matter are not described.
Third Party Request and Subpoena Notice
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
The terms allow ContractKen to preserve or share information when reasonably necessary for legal process, law enforcement and protection of rights or safety. The privacy policy also permits disclosures in response to legal requirements. Neither sets out advance customer notice for a subpoena, a process for challenging a request or a transparency report. The separate security incident notice commitment concerns breaches and does not supply a legal demand notification policy.
Section 8.2 of the subscription terms requires prior notice of a legally compelled disclosure where the law permits, and reasonable help if the customer contests it. Under the data processing addendum, LegalOn tells the customer of requests from regulators about personal data and does not answer them without approval. The privacy policy allows disclosure to law enforcement and authorities for legal compliance. No transparency report is offered.
Primary Law Corpus Provenance
Where does the law in this product come from, and does the vendor have the right to use it?
Review and drafting use the customer's playbooks, clause library and prior agreements. ContractKen also supplies a library of commercial clauses and describes bundled language as authored internally, licensed or drawn from public domain material. Individual external sources and their rights are not listed, nor is an update schedule for a primary law corpus. Jurisdiction notes and refreshed sample language support drafting without establishing a comprehensive collection of legal authority.
Playbooks are written and maintained by LegalOn's attorneys for each contract type and negotiating position, more than 135 of them, and are kept current as laws and standards change. More than 100 attorney drafted templates sit beside them. Playbook Agent also turns the customer's guidelines, templates and previous redlines into custom review instructions. The legal sources and licensing basis behind each prepared standard are not named.
Good Law Verification
Does the product tell you when the authority it just cited has been overruled?
ContractKen can flag a precedent that no longer matches the team's current playbook and replace language from the approved clause library. It also traces generated clauses to their inputs. These checks concern contract standards and provenance, rather than the subsequent treatment of a judicial decision. A commercial citator connection, a method for checking whether authority has been overruled or an inline legal status warning is not specified.
Review tests contracts against playbook standards rather than case law, and the playbooks are kept current as laws change. No flag on cited cases or check of later history is part of the product.
Refusal and Uncertainty Behavior
What does the product do when the answer is not in the corpus?
The interface flags low confidence suggestions and gives reviewers supporting sources, explanations and control over proposed edits. Playbook thresholds identify unacceptable negotiating positions and can send those issues to a partner. That escalation is about contract risk rather than unsupported answers. An explicit refusal response when retrieval cannot support a generated conclusion, or a published demonstration of the system declining such a question, is not described.
Review flags each issue with an importance of low, medium or high and supplies the playbook guidance and sample clauses behind it. No path is described for an issue the product cannot assess.
Fabricated Citation Record
Does a public court record exist addressing fabricated or hallucinated legal citations in output from this product?
The AI Hallucination Cases database has no entry naming ContractKen as the tool behind fabricated legal citations as of October 15, 2026. Its stated work centers on contract drafting, clause review and proposed Word edits, with the lawyer approving changes. This court record concerns one specific kind of incident; it does not establish an error rate for those tasks or validate the accuracy of the current models.
The AI Hallucination Cases database maintained by Damien Charlotin, which records court decisions worldwide that address hallucinated AI content and the tool involved where known, has no entry naming LegalOn. Its products review, draft and manage contracts for in house and contracting teams.
Bar Guidance Alignment
Has the vendor engaged in public with the ethics opinions its buyers are bound by?
The Moderation Layer explanation addresses ABA Formal Opinion 512 and connects its confidentiality duties to local masking, user previews and logs of external AI requests. It discusses informed consent and also references several state bars, the SRA and the CCBE. It does not map the product to named opinions in multiple jurisdictions. These statements explain ContractKen's approach; they do not guarantee privilege or establish that every deployment satisfies a lawyer's duties.
The company's research covers AI adoption, a workflow survey of 500 legal professionals and its contract review benchmark. No named bar opinion or jurisdiction specific ethics guidance accompanies those studies.
Billing and Fee Posture
Does the vendor address what happens to the bill when the work takes an hour instead of six?
The privacy workflow logs who triggered AI analysis, what information went to which provider and when. Enterprise administrators can export document activity and enable prompt history exports, while Word preserves accepted edits and comments. These records identify parts of the assisted work performed on an agreement. ContractKen also markets shorter drafting and review times, but gives no corresponding guidance on recording billable hours, charging clients or disclosing the effect of those savings.
LegalOn sells to in house legal, legal operations, procurement, contract management and sales teams, and to law firms. Its law firm page pitches taking on more clients by cutting manual review time by up to 85%. TriHealth, a Cincinnati health system, reports clinical trial agreements that once took hours now reviewed in about 20 minutes, a 75% reduction. No per matter billing record or guidance on client fee treatment accompanies those savings claims.
Outside Counsel Guideline Readiness
Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?
ContractKen offers a DPA, current subprocessor register, security paper, data flow diagram and insurance certificates on request. Some assurance materials require a nondisclosure agreement. Its public security FAQ explains tenant separation, model provider restrictions and purge options, but is not a complete provider list or a client consent package. A firm can begin its assessment from those commitments, while the detailed materials for a client's AI requirements require direct contact.
The trust center keeps the subprocessor list that the data processing addendum points to, with Google Cloud Platform, Auth0, Microsoft Azure for the OpenAI service and Datadog, their functions and processing locations. A new subprocessor is announced with ten days to object. The SOC 2 report, ISO certificates and security white paper are released on request, and no client facing disclosure template is offered.
Court Disclosure Support
If a judge’s standing order requires an AI disclosure, can the product produce one?
Anonymized versions and interaction logs preserve the information sent to AI providers, while drafting identifies source clauses and Word retains accepted edits. Administrators can export activity logs and prompt history. These provide pieces of an explanation of how an agreement was produced. A single export tying each generated passage to the exact model version, retrieved sources and a named human verification step for a court certification is not specified.
Review ties each issue to the playbook standard behind it, and Matter Management keeps each request's history, status and cycle time. No record of AI use for a court filing is offered.
The questions both sides leave open
Derived from the records above rather than written, so it cannot favor either vendor. Take these into both conversations and ask each side the same question.
- Good Law Verification
Which one fits
Choose ContractKen if
- The first requirement is drafting or marking up an agreement in Word, with detailed negotiation positions kept in the playbook.
- Your lawyers need a comprehensive clause check as well as review against their own standards.
- A published standard review price and configurable local masking are useful starting conditions for the evaluation.
Choose LegalOn if
- Legal requests arrive through several business channels and need intake, triage and matter administration alongside contract review.
- You want attorney written playbooks plus a suite that can extend to a signed agreement vault and department management.
- A supported rollout with guided onboarding and a package selected for the legal department is part of the purchase.
In summary
ContractKen
ContractKen offers drafting and review tools centered on the working Word file. A lawyer can use a firm playbook or run Comprehensive Review against a library of more than 700 clauses, with proposed Surgical Redlines and explanatory comments. The AI Legal Index identifies its distinction between preferred, fallback and walkaway positions as a concrete way to encode negotiation judgment. Drafting can draw on precedents, term sheets and other sources, and the Moderation Layer can mask sensitive text locally before configured processing. Its standard review subscription has a public per user rate. The company offers private enterprise inference, while its standard terms and unfinished SOC 2 Type II work remain separate considerations.
LegalOn
LegalOn combines attorney written review playbooks with a wider legal department workflow. Its review service operates in Word and the browser, while Vault stores executed agreements and Matter Management handles incoming requests. More than 135 playbooks provide starting positions, and the Playbook Agent builds custom instructions from a team's own material. The AI Legal Index identifies intake through email, forms, Slack and Microsoft Teams as a distinction for teams coordinating business requests alongside review. Three main packages separate individual review, contracting and department operations, with custom pricing and guided onboarding. Translation and additional management modules extend the suite, but do not establish identical legal reliability across every supported language.
Questions buyers ask
Does ContractKen's clause count mean it has more playbooks than LegalOn?
No. The products count different things. LegalOn describes more than 135 prebuilt playbooks, while ContractKen's comprehensive library contains more than 700 clauses. Neither count alone measures coverage or correctness for a particular agreement. From the AI Legal Index, based on each vendor's own published materials as of October 15, 2026. No vendor pays for placement.
Can LegalOn take requests from Microsoft Teams?
Yes. Teams is included among the Productivity Suite intake options, alongside email, forms and Slack. That department intake workflow is distinct from checking and revising an agreement in Word. From the AI Legal Index, based on each vendor's own published materials as of October 15, 2026. No vendor pays for placement.
Which has a public standard review price?
ContractKen lists $119 per user per month with annual billing, or $149 monthly, for its standard Review plan. LegalOn describes package inclusions but requires a quote. Optional enterprise arrangements and additional modules remain separate from that comparison. From the AI Legal Index, based on each vendor's own published materials as of October 15, 2026. No vendor pays for placement.
Do both create custom review standards?
Yes. LegalOn's Playbook Agent can use a team's templates, guidelines and past redlines. ContractKen lets a firm define preferred terms, fallback language, walkaway limits and escalation conditions. In either case, the quality of those instructions remains distinct from the number of supplied templates. From the AI Legal Index, based on each vendor's own published materials as of October 15, 2026. No vendor pays for placement.
Neither vendor paid for inclusion, placement or a grade, and neither reviewed this page before it published. Everything on it comes from public material on the dates shown. How the index grades.
LegalOn and ContractKen did not review this comparison. Their clause and playbook counts refer to different units. ContractKen's public standard price does not establish the cost of a custom private deployment.