Juro vs Pactly: how they compare in 2026
Juro offers a collaborative contract workspace with AI review in both the browser and Word, while Pactly combines versioned playbooks with a separately packaged portfolio analysis tool. The distinction is therefore more useful than a simple browser versus Word choice. Juro's Operator supports agreement work and answers tied to contract text; Pactly's Assist proposes changes that a user must accept, and Projects preserves corrected result cells. Across these workflows, AI Legal Index identifies Pactly's explicit separation of analysis runs from full CLM users as a notable budgeting difference. Juro scopes its commercial package around contract volume and integrations with unlimited users. Pactly charges for CLM users and adds review, signature and template allowances by tier, while free business requestors can submit forms without a full account.
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.
Juro manages the complete contract lifecycle, from template creation and approval routing through negotiation, electronic signature, storage and tracking. AI Review redlines third party contracts, AI Extract captures data from signed agreements, and the AI Assistant supports drafting and summaries. Operator adds conversational access to the repository and can answer questions with source citations. The underlying contract platform also has a distinct function without those AI features. Legal teams control templates and approval processes while colleagues generate agreements within those controls. Native electronic signature and lifecycle tracking complete transactions independently of an AI response. The company began in 2016 and added AI to that established contracting workflow.
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.
Juro's AI terms warn that generated output may misstate people, facts or laws, including legal authorities. Operator connects repository answers to source citations, while AI playbooks constrain tasks with contract context and customer rules. Prompt shortcuts help users structure instructions consistently. These features provide context and a route back to source material, but no measured hallucination rate, legal accuracy benchmark or test set accompanies them. The retrieval mechanism behind Operator's citations is unspecified. Juro treats generative AI as fallible and places responsibility for identifying and correcting errors with the customer before reliance. A source citation therefore provides a review aid, without a separate guarantee that the answer is correct.
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.
Human review is required before customers use or rely on AI output. Juro also prohibits presenting generated output as human authored. Inside the product, legal teams establish approval routes and set playbook context and constraints at the template or individual contract level. AI Review explains which playbook rule supports a proposed edit, and reviewers can accept, edit or skip suggestions. The responsible AI guidance limits recommended use to tasks that the professional could perform and verify independently. These controls put the reviewer between a proposed redline and its acceptance. The circumstances that stop unattended agent activity and the escalation process after an erroneous result remain unspecified.
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.
Juro associates customer outcomes with named legal and business leaders. Talentful reports an 86 percent reduction in time to sign, Funnel an 88 percent reduction in manual contract reviews, and Luno a 91 percent time saving per contract. Paddle attributes three and a half hours saved per contract to the platform. Goldin's stated workload is 20,000 contracts annually, while Deliveroo describes eight years of use. These examples cover contract operations across multiple companies and roles. They do not establish the contribution of an individual AI feature, and the figures lack a measurement method or deployment period. Older lifecycle results cannot establish the performance of the current AI review and Operator features.
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 data cannot train an AI model serving another customer. Juro's AI terms permit a model used exclusively for the same customer, with deletion of that model within 60 days after termination. Generated output belongs to the customer and is treated as customer data. The responsible AI guidance identifies OpenAI's GPT family through Microsoft Azure and describes confidentiality obligations covering Juro and its technology providers. A data processing agreement and named subprocessors support that contractual framework. Repository separation and permission enforcement across legal, sales, HR and procurement are not explained in that material. Professional confidentiality is recognized, but attorney client privilege and work product receive no separate treatment.
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.
Juro requires human review of generated output and prohibits passing it off as human authored. Its responsible AI guidance recognizes lawyers' professional confidentiality duties and extends a related concern to HR teams handling employee information. The contracting workflow allows sales, procurement, HR and finance teams to act within legal team templates and approvals. These are operational controls around contract production, rather than a jurisdiction specific professional responsibility framework. The terms and guidance do not establish a no legal advice boundary, identify a governing bar opinion, or map product behavior to ABA Formal Opinion 512. Restrictions on which jurisdictions or categories of professional work the AI can support are also unspecified.
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.
Juro's responsible AI framework focuses on privacy, confidentiality and accuracy in contracting. Customers can obtain a data protection impact assessment template populated for AI Assistant, with separate data protection guides for AI Assistant and AI Extract. AI playbooks let legal teams specify context and constraints, while an EU AI Act guide addresses the regulatory setting. The framework acknowledges bias and intellectual property issues but treats them as less pertinent than its three principal concerns. It does not identify a person accountable for model behavior, a release testing regime or evaluation results. Those omissions leave the operational ownership of model risk and the testing of biased outputs unclear.
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.
Juro names infrastructure providers including Algolia, AWS and MongoDB, along with analytics, communications and payments providers. Salesforce, Slack and Google also appear as customer initiated integrations. A data processing agreement governs personal data, and customers have access, portability and erasure rights. Separate security and resilience guidance accompanies a status page and a 99.9 percent uptime commitment. The AI terms require deletion of customer specific models within 60 days of termination; that period is not a retention schedule for contract text, prompts or generated output. The broader content retention window and AI specific incident notification process remain unspecified in the material underlying this assessment.
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.
Juro separates its AI terms from the Master Services Agreements for customers in the United States and elsewhere. Under clause 3.2 of the AI terms, any MSA indemnity for infringement of intellectual property or other third party rights excludes generated AI output. Clause 3.1 assigns the customer the duty to identify and correct output errors before relying on a result. The March 2025 AI terms retain a link to their February predecessor, making the version boundary identifiable. This arrangement defines the treatment of AI output directly, but leaves customers without the MSA's infringement remedy for that output. Human review is the customer's contractual responsibility.
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.
Juro connects contract creation and management with business systems and Microsoft Word. Word synchronizes edits, comments, redlines and versions with the contract workspace. Slack, email, Google Drive and Word are available across plans. Growth adds HubSpot, Claude, Copilot, DocuSign, Greenhouse, Zapier and Ashby; Enterprise includes Salesforce, REST API access and webhooks. Claude uses MCP to work with the repository, while the ChatGPT connection remains a beta. Pricing depends partly on integration complexity, and the pricing FAQ identifies Salesforce, HubSpot and Workday as integrations carrying additional cost. No iManage or NetDocuments connection is identified. The integration set primarily follows in house contracting and business system workflows.
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.
AWS supplies part of Juro's infrastructure, and the responsible AI guidance places GPT processing on Microsoft Azure servers. Customers use the hosted contract workspace across more than 85 countries. An EU Data Act addendum addresses a separate contractual requirement around the service. That international reach does not itself establish where an individual customer's contract data resides. The deployment material underlying this assessment does not specify a choice of regions, a residency commitment, tenant architecture or a private installation. The distinction between platform infrastructure and the model processing route is identifiable, but the customer controlled boundary for hosting location remains unclear.
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.
Juro's trust center covers privacy regulations, application security, network infrastructure, resilience, electronic signatures and responsible AI. Its security claims include SOC 2 Type 2, supported by a corresponding trust center topic and a certification badge. The platform also has a status page and a stated 99.9 percent uptime. Access to the explanatory articles does not require a form, email address or confidentiality agreement. The trust center index does not identify the auditor, attestation period, report date or tested scope. A route to the underlying report and details of a penetration test are also unspecified there. The security claim is identifiable, while its independent verification details remain incomplete.
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.
Juro identifies OpenAI's GPT family as the model behind its AI tools, delivered through Microsoft on Azure servers. That establishes a provider, model family and delivery route for the arrangement described in its responsible AI guidance. The discussion also uses GPT 4 as an example of training scale, without confirming that version as the current production model. A precise version and a customer notice commitment for model changes are unspecified. The trust center's infrastructure subprocessor list names Algolia, AWS and MongoDB but omits OpenAI and Microsoft. The named model route therefore does not resolve the complete chain of processors or how customers learn of a change.
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.
Juro charges according to monthly contract volume and integration complexity, with unlimited users, workflows and templates across plans. Volume bands range from fewer than 20 contracts per month to more than 1,000. Slack, Google Drive and Companies House are included according to the pricing FAQ, while Salesforce, HubSpot and Workday incur additional cost. Quotes also reflect implementation complexity. Billing can use USD, GBP or EUR, and nonprofit discounts are available. No numeric subscription or implementation price is stated. The pricing page supplies the main drivers of a quote without a per seat rate or an independently calculable total. A previous demo month promotion is no longer part of the current pricing offer.
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.
Juro serves legal, HR, procurement, sales and finance teams. Legal establishes templates and workflow controls, allowing other departments to produce agreements within an approved process. Contract types include NDAs, employment agreements, master services agreements, statements of work, order forms, acquisition material and supplier agreements. The company describes customers in more than 85 countries and positions the platform for businesses completing roughly ten or more contracts each month. Its industry examples include software, food delivery and marketplaces. The central setting is an in house contract operation. A dedicated law firm, government or court workflow is not identified, and the product does not function as a primary legal research service.
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?
Juro's AI terms prohibit using customer data to train a model for anyone else. A model used only to provide services to that same customer is permitted, and Juro must erase it within 60 days after the agreement ends. The responsible AI guidance also rejects training foundational models with customer data. The contract's limited customer specific exception is therefore distinct from shared model training, and the deletion deadline applies to that derived model.
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?
Juro's AI terms require erasure of a customer specific model within 60 days after termination. That deadline governs the model rather than the contracts, prompts or generated output used in the service. Customers can exercise portability and erasure rights under the privacy framework. A content retention window and a customer controlled retention setting are unspecified in the material underlying this assessment, leaving the lifetime of operational AI content separate from the model deletion commitment.
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?
Legal, sales, HR, procurement and finance can work in Juro's contract workspace. The AI terms prevent a customer specific model from serving another customer and distinguish one user's output from similar output produced for others. Those contractual boundaries do not explain permission enforcement within the repository or retrieval across teams. A technical separation model and controls for ethical walls between matters are unspecified in the material underlying this assessment.
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?
Juro's data processing agreement requires notice to the customer of government access requests under Appendix 3, paragraph 4.4(k). The commitment operates through the Standard Contractual Clauses where the corresponding transfer law applies. Notification to individual data subjects remains the customer's responsibility. An equivalent commitment is not identified in the general terms or CCPA appendix. Requests from a third party claiming to control customer personal data are directed to the customer. No transparency report or request volume accompanies these provisions.
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?
Operator answers questions from the customer's contract repository and connects responses to its sources. AI Extract captures data from signed agreements in that same customer supplied collection. The underlying model route is separately identified as OpenAI's GPT family through Microsoft Azure. Juro is not a primary law research corpus. Rights to the foundation model's training material and an update schedule for that material are not established by the repository's customer supplied provenance.
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?
Juro works with a customer's contracts rather than a primary law collection. It has no identified citator, treatment signal or process for checking the subsequent history of a legal authority. Operator's citations connect repository answers to contract sources, which serves a different purpose from determining whether a case remains good law. The AI terms acknowledge that generated output can misstate laws and legal authorities and require human correction before reliance.
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?
Juro warns that generative AI can produce errors and requires a person to review results before reliance. Playbooks provide context and constraints for contract tasks, but no defined abstention path or confidence indicator explains how the system responds when an answer lacks support. The responsible AI guidance treats accuracy as an ongoing professional review responsibility. That establishes a warning and a human control, without specifying when the AI itself declines a request.
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?
No identified court decision or disciplinary record names Juro or Juro Online Limited in connection with fabricated citations. Damien Charlotin's AI Hallucination Cases database and the sanctions material underlying this assessment contain no attributable incident. That finding does not establish an error rate or demonstrate that generated authorities are reliable. Juro primarily supports commercial contracting inside companies, a setting in which output is less likely to become part of a court filing.
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?
Juro recognizes that lawyers must protect professional confidentiality when using AI. Its responsible AI guidance connects that duty to restrictions on training with customer data, while making a similar confidentiality point for HR teams. It does not connect these controls to a named ethics opinion or regulator's requirements. ABA Formal Opinion 512, state bar guidance, and Solicitors Regulation Authority or Law Society materials are not identified as the governing framework.
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?
Juro's customer examples describe reduced contract work, including faster signing, fewer manual reviews and time saved per agreement. The commercial focus is an in house operation where legal and business teams share the platform. Those efficiency claims do not establish how a law firm should bill a client for AI assisted work. No matter based fee record, disclosure procedure or guidance on passing time savings through to clients accompanies the contracting workflow.
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?
Juro identifies infrastructure, analytics, communications and payment subprocessors, including AWS, MongoDB, Algolia, Stripe and HubSpot. Customer initiated integrations include Salesforce, Slack and Google. The contractual package includes a data processing agreement, an EU Data Act addendum and separate AI terms, with an impact assessment template available for AI Assistant. The trust center list does not include the OpenAI and Microsoft route described in the responsible AI guidance. No client consent or notification pack accompanies this material.
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?
Juro manages commercial contracts rather than court filings. Operator provides source citations for repository answers, and the AI terms prohibit representing generated output as human authored. These features support a limited record of sources and a contractual disclosure boundary. They do not create a court certification, standing order workflow or export that records the model's role and a lawyer's verification. A dedicated litigation disclosure process is not identified.
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
Which one fits
Choose Juro if
- Unlimited users fit a contract volume based purchasing model.
- Business teams should collaborate around a shared agreement workspace.
- Your lawyers want both browser and Word review surfaces.
Choose Pactly if
- User plans and stated review allowances fit the legal team's budget.
- Business requestors should submit forms without full user accounts.
- Versioned positions and protected analysis corrections are priorities.
In summary
Juro
Juro combines collaborative agreements, AI review and an Operator within its contract workspace. Word review is part of the current offering, alongside browser negotiation and workflows connecting business teams with legal.
Pactly
Pactly's playbooks define review positions and fallback language, with published versions preserved for repeat use. Projects adds a separate portfolio table, and Assist leaves acceptance of edits with the user.
Questions buyers ask
Is Juro limited to editing in the browser?
No. Its current AI review offering also works in Word. Pactly likewise supports Word review, so choosing between them requires looking at the surrounding workflow and review controls. From the AI Legal Index, based on each vendor's own published materials as of October 16, 2026. No vendor pays for placement.
How do their charging units differ?
Juro quotes by contract volume and integration scope with unlimited users. Pactly's CLM uses paid users and tier allowances, while Projects has separate document and run limits. From the AI Legal Index, based on each vendor's own published materials as of October 16, 2026. No vendor pays for placement.
Can Pactly's Assist send its draft response to the counterparty?
Assist can prepare wording, but cannot send the response on its own. A person also decides whether to apply, edit, copy or reject proposed contract changes. From the AI Legal Index, based on each vendor's own published materials as of October 16, 2026. No vendor pays for placement.
Why might Pactly's playbook versioning matter during a negotiation?
For a team revising its negotiating standards, AI Legal Index highlights Pactly's locked published versions and new versions for later edits. That structure helps keep a review round associated with the positions used at that time.
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.
Juro's quoted package and Pactly's user allowances cover different units; business requestors are not equivalent to full review users.