LegalOn vs Pactly: how they compare in 2026
Starting a review without building a playbook is LegalOn's clearest distinction here: more than 135 attorney written playbooks cover common agreements and negotiating positions. Pactly instead makes the team's preferred positions, examples and fallback drafting explicit within its review setup. For reviewers handling international agreements, AI Legal Index highlights LegalOn's translation into English and back into the original language as a specific workflow difference. Both support contract review in Word, and both extend beyond a single redlining task. LegalOn includes matter intake, an assistant and Vault within its wider platform. Pactly brings generation, approvals and signatures together and offers Projects separately for repeated portfolio questions. Pactly's cells expose reasoning and source excerpts, and a verified correction remains protected when the table is analyzed again.
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.
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.
Models identify clauses and concepts for playbook review, generate proposed revisions and extract values across contract collections. Assist adds questions about a contract's text and history, with proposed edits and comments in Word. Projects applies the same questions to many agreements and returns a structured table with reasoning and source passages. These are core analysis functions alongside the conventional platform: questionnaires generate approved templates, workflows route approvals, signatures execute agreements and reminders track renewals. Those administrative features do not depend on generative output. Projects is available separately, while Growth and Ultimate include it within an unspecified fair use allowance.
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 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.
Projects connects an extracted value to reasoning, a quoted source passage and a document view that highlights the relevant text. Users can correct a value, preserve the original AI extraction and mark a result as verified. The guidance names concrete failure modes, including confusion between effective and commencement dates, loss of qualifiers in compound liability caps and missing values in drafts with placeholders. Word review also exposes the clauses behind each playbook assessment. No reproducible benchmark or measured error rate accompanies these mechanisms. The terms expressly warn that AI answers can be incomplete or wrong and require checking against the source.
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.
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.
Assist never applies a contract edit or comment silently: proposed changes require acceptance and enter Word as tracked changes. A reviewer can reject, revise or copy the proposal, and a support message is not sent without the user's choice. Playbook results can be Uncertain, returning the decision to a human; accepted deviations carry a written justification. Projects preserves corrected and verified values during reruns and identifies outdated results when a column question changes. The external MCP connection is read only and cannot create, modify, delete or send signature requests. Standalone Word generation remains described as an upcoming release rather than an existing unrestricted action.
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.
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.
A September 2022 case study identifies Virtuos and its Senior Legal Counsel, Johnathan Yong, and describes an NDA process before and after adopting Pactly. Requests previously took several days or sometimes a week across Word, shared drives and email. Following template questionnaires, legal review and DocuSign execution, reported median finalization fell to two hours and median completion of a signed agreement to twelve hours. Yong describes feedback more than two months after implementation. The account explains the workflow change and measured contract type, although it does not provide the sample size. It measures contract automation rather than the accuracy of today's generative review features.
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.
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.
The service agreement protects nonpublic customer data as confidential information and preserves customer ownership. Its improvement license nevertheless permits analysis of service information involving customer data during the term and use of anonymized aggregate customer data for lawful business purposes afterward. Public marketing says contracts never train AI models, without the same express restriction in the agreement. Sensitive groups can hide contracts from nonmember administrators, but deliberate sharing and project membership can widen access. The provider list explains where contract data travels. No specific attorney client privilege, work product or accidental disclosure protection is stated for lawyers using these features.
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.
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.
Pactly's agreement says the company is not a law firm, use creates no attorney client relationship and the service does not solicit legal advice. It separately warns that AI answers may be wrong and makes the customer responsible for comparison with the source. Product guidance describes the reviewer accepting edits and resolving uncertain playbook findings, and the company explicitly rejects a fully automatic robot lawyer role. Corporate legal departments are its principal audience, with business users working through forms and approvals. The material does not map the controls to named bar guidance or publish jurisdiction specific professional responsibility limits.
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.
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.
Published AI guidance explains how customers verify results, handle uncertain findings and correct extraction mistakes. Release notes describe feature changes, and security materials identify a data protection officer and engineering responsibilities for incidents. These do not establish an AI governance program with an accountable model owner, release testing criteria or results on uneven behavior across languages, populations or contract categories. Positive and negative playbook examples help customers configure review, rather than disclose Pactly's own evaluation program. No formal bias assessment, model card or governance framework accompanies the descriptions of Assist, Projects and playbook review.
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.
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.
Pactly describes encrypted storage and transport, monitoring, backups, vulnerability testing and separate production and test environments. Administrators can require two factor authentication, and high criticality incidents trigger notice to affected customers or all customers when the affected group cannot be identified. A public supplier register details processing functions and regions with advance change notice. The terms provide sixty days to retrieve data after termination, followed by requested deletion with an anonymized aggregate exception. Assist attachments expire after seven days, but ordinary chat history, backup deletion and underlying AI provider retention lack a complete fixed schedule. No definite breach notification deadline is stated.
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.
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.
The service agreement includes an indemnity for third party claims involving patents, copyright or trade secrets infringed by the service, subject to stated exclusions and control of the defense. Available remedies include replacement, modification, a license or termination with unused fees returned. General liability is capped at fees paid in the preceding twelve months and excludes data inaccuracies and several categories of loss. AI answers are expressly described as potentially incomplete or wrong, with verification assigned to the customer. There is no separate output accuracy warranty or AI insurance promise. Availability remedies have separate claim deadlines and exclude beta features.
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.
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.
The Word plugin uploads an agreement for playbook review, displays matched clauses and proposed fixes, inserts approved language as tracked changes and records review decisions between rounds. The MCP connection exposes eight read only tools for contract text, metadata, parties, playbooks, clauses and account information to external clients such as Claude and Cursor. Public instructions specify API key or OAuth authentication, administrator consent, filters, returned fields and request limits. Separate APIs can generate contracts from templates and support webhooks. DocuSign and Adobe Sign support execution, while the Ultimate plan's SharePoint connection is described as backup only rather than general document synchronization.
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.
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.
Core hosting, compute and Bedrock inference use AWS in Singapore by default, with Malaysia for specified Malaysian customers. Structured data in MongoDB Atlas remains in Singapore for all customers. The supplier table separately identifies United States processing for document conversion, OCR, Cerebras inference and fallback Anthropic or OpenAI services, plus Langfuse monitoring in Germany and Cloudflare's global edge. Those routes make regional hosting different from exclusive regional processing. The SLA also recognizes fully managed private deployments, without a standard public price for them. Singapore and Malaysia have separate service entry points, and the published provider map identifies functions as well as locations.
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.
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.
Pactly identifies ISO 27001 certification in its product, pricing and trust materials and offers its certificate, security whitepaper and penetration test results on request. The public trust FAQ describes Amazon's certified data centers when explaining ISO coverage, so infrastructure attestations need to be distinguished from Pactly's own claim. No openly supplied certificate names its current auditor, validity period and exact company scope. SOC, PCI and FISMA references in the infrastructure section concern AWS rather than a separate Pactly audit. Security practices include vulnerability scans, access logging, staff training and incident response, without resolving that certification scope question.
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.
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.
Pactly names AWS Bedrock for core inference, Cerebras for tasks requiring low latency, and Anthropic and OpenAI as fallback providers when Bedrock is unavailable. The supplier register identifies processing locations and also lists Langfuse for AI monitoring. Customers can subscribe to at least thirty days' written notice before a new subprocessor is engaged and raise an objection during that period. Exact production model families and versions are not supplied for each feature, nor is there a promise to notify every model version change within an existing provider. External MCP clients bring their own model relationship in addition to Pactly's built in AI.
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.
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.
Standalone Projects starts at $69 a month for one user, fifty documents and 250 monthly runs, or $690 annually with 3,000 runs available immediately. Larger packages, additional documents and extra runs have published charges. The wider CLM starts at $99 per user monthly on an annual plan; Growth is $139 with five users minimum and Ultimate $179 with ten. Their monthly AI review allowances are ten, fifty and one hundred respectively. Growth and Ultimate include Projects under fair use without a numerical allowance. Enterprise, migration and some implementation services require a quote. Projects has a fourteen day trial, while the CLM trial lasts thirty days.
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.
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.
Pactly primarily serves corporate legal departments, including solo counsel and small teams across Southeast Asia and other Asia Pacific markets. Larger organizations can configure approval routes, business intake and administrator controls. Supported examples include NDAs, services, procurement, leases, employment and software licenses; Projects extends analysis to loan agreements, insurance and related portfolios. Sales, HR, finance and procurement can participate without turning the product into a consumer legal advice service. The company explicitly describes most customers as internal legal departments rather than firms. No measured language coverage or comprehensive jurisdiction matrix defines where AI interpretation is most reliable.
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 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.
The agreement permits analysis of service information involving customer data during the subscription for improvement and development. It also allows anonymized customer data to enter aggregate datasets used for lawful business purposes during and after the term, with safeguards against reidentification. Marketing separately promises that contracts never train AI models. The published agreement does not repeat that prohibition or exclude model improvement from its permission.
This records the contractual scope, not a claim that Pactly actually feeds every raw agreement into a shared training process.
Prompt and Output Retention
How long does the product keep what a lawyer typed, and can that be set to zero?
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.
Contract data remains retrievable for sixty days after termination. The standard terms then provide deletion on written request, excluding anonymized data already combined into aggregate datasets; online plans may delete after the same access window. Assist attachments expire after seven days, but a complete schedule for normal chat history, backups and provider copies is absent. The upcoming standalone Word generation description gives a thirty day file expiry, which should not be treated as the lifetime of all current AI outputs or contracts saved to the repository.
Ethical Walls and Matter Segregation
Does retrieval respect the firm’s ethical walls, or can the model read across them?
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.
Pactly uses its own groups and roles rather than inheriting a document management system's matter walls. Sensitive groups hide contracts even from nonmember administrators, but an authorized person can deliberately share a contract outside the group. Projects creates another boundary: every project member sees all present and future project documents, even when the normal repository link is unavailable. Administrators can see all projects.
This is a described access model with important widening rules, not a promise that an original contract restriction automatically follows every AI analysis surface.
Third Party Request and Subpoena Notice
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
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.
The service agreement incorporates Pactly's law enforcement request policy for compelled disclosure of customer data. That policy requires evaluation of governmental requests and notification to the customer where legally permitted, allowing an opportunity to seek protective measures. It applies to hosted and fully managed deployments, while excluding self hosted or customer managed solutions. Foreign authorities are directed through applicable legal and diplomatic channels.
No report of request volumes or outcomes accompanies this commitment, and the general privacy notice's legal disclosure permissions do not replace the more specific customer data policy.
Primary Law Corpus Provenance
Where does the law in this product come from, and does the vendor have the right to use it?
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.
The analysis context is the customer's agreements, playbooks, approved clauses and related files. Projects reads each row's main contract and supporting amendments or schedules; Word review uses configured positions and fallback language. These are customer supplied materials rather than a catalog of primary law or licensed legal commentary. Pactly does not name an external research corpus, describe the source rights behind general model knowledge or supply an update process for legislation and case law. The public subprocessor list identifies processing suppliers, not a legal content licensing arrangement.
Good Law Verification
Does the product tell you when the authority it just cited has been overruled?
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.
A source passage in Projects establishes where a contract value came from, and playbook review identifies the agreement language relevant to a configured rule. Neither function determines whether a case remains good law or legislation has changed. No licensed citator, subsequent history service or independent treatment signal is described. The legal team maintains its own clause positions and decides whether they remain appropriate.
Contract source highlighting and a verified cell marker therefore support review of supplied material without establishing the continuing validity of an external legal proposition.
Refusal and Uncertainty Behavior
What does the product do when the answer is not in the corpus?
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.
Playbook review includes an Uncertain result when a clause cannot be conclusively assessed, directing a person to decide. Each position also defines what happens when no relevant clause is found: compliant, not compliant or uncertain, according to the customer's chosen rule. Projects treats placeholders such as an unfilled name as not found and explains common interpretation failures. These are described negative and uncertainty states rather than a general guarantee of refusal. A wrong configuration of the absent clause rule can still produce a misleading result.
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 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.
Damien Charlotin's AI Hallucination Cases database contained no entry naming Pactly on October 16, 2026. The database concerns reported court decisions involving fabricated AI material and does not capture every private error in contract analysis. Pactly principally supports corporate agreements rather than preparation of court authorities, which limits what that incident record can say about its usual work. Its terms independently warn that AI answers may be incomplete or incorrect. No named court incident is therefore a limited reporting observation, not a validation of model accuracy.
Bar Guidance Alignment
Has the vendor engaged in public with the ethics opinions its buyers are bound by?
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.
Pactly explains that it is not a law firm and requires people to verify AI answers against source text. Its review guidance describes accepting tracked edits, recording deviations and resolving uncertain results. These are practical controls for legal work, but the materials do not map them to a named professional ethics opinion, bar rule or regulator's jurisdiction specific AI guidance. References to Singapore privacy law and a data protection officer address data regulation rather than a lawyer's professional obligations when serving a client.
Billing and Fee Posture
Does the vendor address what happens to the bill when the work takes an hour instead of six?
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.
The principal buyer is a company's own legal department, with sales, procurement and HR using forms and approvals around that team's contracts. The Virtuos case measures internal NDA turnaround, and the product's savings claims concern corporate workloads and staffing capacity. Those examples do not involve a lawyer billing an external client for AI assisted work. Published subscription and run charges describe Pactly's software fees, without a client invoice method, pass through rule or accounting of billable legal time. Law firm fee treatment is not part of the described workflow.
Outside Counsel Guideline Readiness
Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?
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.
A public provider register identifies data categories, functions and regions, including core Bedrock inference, fallback Anthropic and OpenAI services, and AI monitoring. Customers can subscribe to change notices and object before a new supplier is engaged. The trust page offers security reports and a certificate on request, while service terms and the law enforcement policy provide additional diligence material. No dedicated client consent pack or outside counsel AI disclosure form is supplied. Counsel would still need to distinguish the contractual improvement permissions from the marketing training promise.
Court Disclosure Support
If a judge’s standing order requires an AI disclosure, can the product produce one?
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.
Projects can export values, reasoning and source references to Excel, and produce a PDF preserving the table's visual labels. Human corrections and verifications record who acted and when inside the application, but the help guide expressly says the Excel export omits that sign off marker. Word review retains tracked edits and written justifications for deviations, while account activity is available through logs. These records preserve parts of the process without a combined export of model version, exact prompts, source context and human approval for a court filing.
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
- Bar Guidance Alignment
Which one fits
Choose LegalOn if
- You want a large set of attorney written playbooks at the outset.
- Review involves translating agreements into English and redlines back.
- Matter intake and contract review should share the wider LegalOn platform.
Choose Pactly if
- Your team wants explicit versioned positions and examples.
- Portfolio questions need a table with inspectable excerpts and reasoning.
- A small standalone Projects subscription suits the initial use case.
In summary
LegalOn
LegalOn provides attorney written review playbooks, severity ranked issues and suggested redlines in Word or a browser. Its wider platform adds intake, matter management, a contract assistant and Vault for agreement information.
Pactly
Pactly reviews contracts against a team's positions and examples, with tracked edits accepted by a person. Projects applies structured questions across agreements and retains corrected values for subsequent analysis.
Questions buyers ask
Must a LegalOn customer create every review playbook?
No. More than 135 attorney written playbooks support common agreements and negotiating positions. Customers can also turn preferred language, fallback positions and risk tolerances into custom playbooks. From the AI Legal Index, based on each vendor's own published materials as of October 16, 2026. No vendor pays for placement.
What happens to LegalOn's translation during review?
Contracts in more than 28 languages can be translated into English for review, with redlines translated back. That workflow does not by itself establish equal legal reliability in every jurisdiction. From the AI Legal Index, based on each vendor's own published materials as of October 16, 2026. No vendor pays for placement.
How does Pactly preserve a reviewed portfolio answer?
A person can correct and verify a Projects cell while retaining the original AI value. Later reruns protect that human decision, and the original value can be restored if needed. From the AI Legal Index, based on each vendor's own published materials as of October 16, 2026. No vendor pays for placement.
Which playbook distinction matters for a team's first rollout?
For a team without a mature rule library, AI Legal Index identifies LegalOn's attorney written starting playbooks as a practical advantage. Pactly's positions emphasize the organization's own standards, examples, rationale and drafting choices.
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 language coverage describes its translation workflow; Pactly Projects is a different purchase from its full contract system.