Pactly vs ThoughtRiver: how they compare in 2026
ThoughtRiver is centered on reviewing contracts with Lexible, a specialized legal model combined with generative AI, while Pactly combines review with contract operations and a separately priced analysis table. ThoughtRiver accepts agreements through email, upload or Word and supports shared issues, redlines and portfolio reporting. Pactly's Word playbooks define preferred positions and fallbacks, and Projects exposes the support behind each extracted result. For repeated portfolio work, AI Legal Index identifies Pactly's protection of human corrected values as a practical distinction from a general promise of faster review. Their commercial entry points also differ: ThoughtRiver's Professional plan begins at £15,000 annually in the UK with unlimited users, whereas Pactly offers a small standalone Projects package before a broader CLM commitment. The two prices cover different workloads and capabilities.
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 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.
Machine learning is the mechanism the customer pays for. A model reads the contract, answers the Lexible question set, scores the answers against a playbook and produces the risk rating, issues list and suggested redlines. Remove the models and there is no review, no issues list and no redlines, only a document store. The vendor has sold this as an AI product since 2016 and describes the current engine as a proprietary generative model on several large language models.
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.
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.
Lexible uses lawyer labeled concepts to identify contract provisions and assess them against a playbook. Its accuracy explanation reports 97% F1, 96% precision and 97% recall, with testing three times weekly against 750,000 verified data points. Legal specialists verify training examples, and sampling covers different contract types and domains. These figures concern classification and do not measure every generated redline or answer. The underlying dataset, current model version and detailed failure results are not available for independent reproduction. The terms acknowledge that training can reduce accuracy, especially with incorrect labels, and that mistakes remain possible.
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.
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.
The platform reads an agreement, identifies issues against a configured playbook and presents suggested redlines in Word. Users can share issues and changes with colleagues, while Lexible Assistant supports questions and remediation. The customer sets its risk policies and remains responsible for decisions based on the resulting analysis, including automated decisions. Terms expressly warn that output is not legal advice and may contain mistakes. These features provide a review surface and organizational standards. The system does not specify when it can approve an agreement without review or how it must escalate and correct an incorrect conclusion.
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.
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.
A named customer gives figures, without a date or method. Joe Stephenson, partner and head of technology at Shoosmiths, is quoted on the demo page saying the platform reviewed complex supply agreements in under three minutes at above ninety percent accuracy, where lawyers took four hours at 86 percent. A second, unnamed customer calls ThoughtRiver a clear winner for reviewing its appointments. No date, sample size or method accompanies the Shoosmiths figures.
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 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.
The agreement treats customer contract data as confidential and restricts disclosure by staff and subcontractors, with confidentiality continuing after termination. Customer accounts have separate encryption keys and segregated contract data. Anonymization removes sensitive information before model processing. The same agreement grants continuing use of training data and anonymized contract text, and the DPA includes machine learning training among processing purposes. This is permission to reuse specified material, rather than a promise never to train. Internal matter walls, direct privilege handling and a complete account of every underlying language model provider are not specified.
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.
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.
The customer terms expressly say that output is not legal advice and must not be relied on as advice. They also warn that predictive technology makes mistakes and that incorrect training can worsen accuracy. Customers remain responsible for results, conclusions and automated or manual decisions. The license allows both internal business work and integrated managed services for legal clients, so law firms and other business users share that responsibility. Product review surfaces support human checking, but jurisdiction specific practice limits and an explicit treatment of lawyers' competence and supervision duties are not set out.
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.
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.
ThoughtRiver describes lawyer verification of training examples, annotation that accounts for contract context and sampling across contract types and legal domains. Its evaluation program runs three times each week against 750,000 verified data points and reports separate precision, recall and F1 measures. Customers can set playbooks for their own risks and review proposed changes before further use. These are concrete training and evaluation practices. The description does not identify an accountable AI governance owner, a mandatory release approval threshold or findings about uneven output across jurisdictions or populations. Its regulatory position is separate from those operating tests.
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.
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.
The DPA names infrastructure, authentication, document conversion, email and support providers, and requires equivalent safeguards for subprocessors. Personal data breaches must be reported without undue delay, with cooperation in mitigation. Customer data is encrypted in transit and at rest, separated by account and protected by a dedicated encryption key. Authentication supports single sign on and multifactor controls. At termination, personal data must be deleted or returned, with backup and legal exceptions. A defined in use retention period for prompts, a backup deletion deadline and an explicit list of the language models processing contract text are not specified.
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 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.
ThoughtRiver indemnifies customers against claims that permitted use of the platform infringes third party copyright, subject to control of the defense and exclusions for unapproved combinations. It can replace or modify the platform to address infringement. General liability is limited to the order term's fees, or £1,000 during a trial, with the copyright indemnity excluded from that cap. Death or injury caused by negligence, fraud and other legally unavoidable liabilities also remain outside the limitation. Output errors carry no warranty or accepted liability, so the software indemnity does not amount to a guarantee of correct legal analysis.
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 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.
Agreements enter through email, file upload or a Microsoft Word add in, with issues and redlines available for team collaboration. Microsoft 365 supports work in Word, Outlook and Teams, while Power BI receives contract data for analysis. HighQ and iManage are named connections for legal projects and document workflows. The platform also exposes the same public APIs used by its web application and follows the OpenAPI specification. These connections have identifiable purposes, but per connector field mappings, authentication setup, permission inheritance and error recovery steps are not described in the integration overview.
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.
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.
Region and processing location are stated, and tenancy is described as segregation. The security page says data resides in Azure data centers managed and secured by ThoughtRiver in a single specified region, and the subprocessor table places Azure hosting in the United Kingdom. Each customer's data is held separately under its own key. Whether a customer may choose a region other than the UK, and whether infrastructure is shared, are not stated, and where the language models run inference is not addressed.
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.
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.
ISO 27001 certification is stated and identified by number, without a route to the report. The security page gives certificate number 21188-ISMS-001 alongside encryption at rest and in transit. No certifying body, coverage period or route to the certificate or any SOC report is published, and no trust center is published.
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.
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.
Lexible combines a proprietary legal model with general purpose language models for contract interpretation and generated responses. ThoughtRiver describes supervised learning from expert labeled concepts, legal validation of examples and repeated evaluation. An anonymization layer protects sensitive text before analysis, and a private model option is offered. The hosting environment is Microsoft Azure. External foundation model providers, versions, routing decisions and processing locations for each model are not named. The subprocessor register covers infrastructure and support functions but does not resolve the generative model chain or commit to notice of each model substitution.
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.
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.
Professional starts at £15,000 a year in the United Kingdom for teams reviewing fewer than 50 contracts a month; Enterprise starts at £30,000 for higher volume. Outside the United Kingdom, the page displays starting rates of $20,000 and $35,000 respectively. Both list unlimited users, a private database instance, Word access, Lexible Assistant, single sign on and dedicated success and professional services. A trial lasts 28 days. The agreement bills order fees in advance and permits separate professional services charges. The published starting amounts therefore do not settle every implementation charge, volume adjustment or negotiated order term.
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.
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.
Corporate legal, procurement and business teams use ThoughtRiver to review incoming agreements, and the license also allows managed services delivered to legal clients. Configurable playbooks apply the customer's negotiation standards to recurring contracts. Professional and Enterprise packages distinguish teams below and above 50 reviews per month, with unlimited users in both. Named examples include complex supply agreements and professional appointments. The current site gives different totals for its trained concept library on different pages, so that total does not define a reliable coverage boundary. A complete jurisdiction matrix and unsupported contract types are not stated.
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?
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.
The agreement licenses training data and anonymized contract text for use in the platform by ThoughtRiver and other customers, while excluding customer risk policies from that licensed material. Its DPA expressly lists machine learning training and feature enhancement among processing purposes. These permissions continue beyond the subscription and are separate from customer ownership of uploaded contracts. The public agreement does not provide a general option to exclude those uses.
Prompt and Output Retention
How long does the product keep what a lawyer typed, and can that be set to zero?
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.
The DPA requires deletion or return of personal data at termination, except for backup copies and legally required retention. Trial data is deleted when a customer properly ends the trial. The general agreement separately preserves rights over licensed training data and anonymized contract text. None of these provisions gives prompts or generated answers a defined retention period during an active subscription, and the backup exception has no stated deletion deadline.
Ethical Walls and Matter Segregation
Does retrieval respect the firm’s ethical walls, or can the model read across them?
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.
Contract text and derived data are separated from other customer accounts and encrypted using a key specific to each account. Organization access can use single sign on with multifactor authentication. These are organization level protections. Although iManage and HighQ are named integration options, a mechanism that inherits their per user permissions during retrieval or separates opposing matters within one customer environment is not specified.
Third Party Request and Subpoena Notice
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
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.
When law requires ThoughtRiver to process personal data contrary to customer instructions, the DPA requires notice to the customer unless law prohibits it. That protection covers compelled processing of personal information in uploaded material. The agreement also permits legally required disclosure of confidential information, without a broader notice procedure for nonpersonal material. A public report of government demands and the response to them is not specified.
Primary Law Corpus Provenance
Where does the law in this product come from, and does the vendor have the right to use it?
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.
The engine applies a lawyer developed concept library to customer agreements and risk policies. ThoughtRiver describes millions of labeled concepts and legal verification of training examples, while the agreement defines training data and anonymized contract text available for broader platform use. These identify the main categories behind contract interpretation. The underlying external legal collections, their licenses and the refresh schedule for any legal authority are not specified.
Good Law Verification
Does the product tell you when the authority it just cited has been overruled?
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.
ThoughtRiver's review concentrates on contract provisions, risk policies, proposed edits and obligations in customer agreements. A reviewer can work through issues in that agreement and use the resulting information for negotiation or reporting. The stated workflow does not include a licensed citator or a method for checking the subsequent treatment of a court decision. Classification accuracy and contract risk ratings do not supply that authority status check.
Refusal and Uncertainty Behavior
What does the product do when the answer is not in the corpus?
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.
Lexible flags contract risks, produces proposed changes and lets a reviewer inspect issues against a playbook. Its precision, recall and F1 figures describe aggregate classification performance rather than a confidence indicator attached to an individual answer. The terms warn that predictive output can be wrong. A stated no answer response, an abstention threshold or a route triggered specifically by insufficient support for a conclusion is not described.
Fabricated Citation Record
Does a public court record exist addressing fabricated or hallucinated legal citations in output from this product?
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.
The AI Hallucination Cases database has no tool entry naming ThoughtRiver or Lexible as of October 15, 2026. The product's described work involves contract provisions, risk review, redlining and questions about agreements rather than preparing a litigation brief. That workflow context is separate from the court record: the absence of a named entry does not measure classification errors or establish that a generated answer is correct.
Bar Guidance Alignment
Has the vendor engaged in public with the ethics opinions its buyers are bound by?
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.
The contract terms distinguish software output from legal advice and leave responsibility for decisions with the customer. They allow managed services for legal clients, and product controls let reviewers apply organizational playbooks and inspect proposed changes. These are general responsibilities and workflow controls. A named ethics opinion or jurisdiction specific bar rule governing a lawyer's use of Lexible is not identified in that position.
Billing and Fee Posture
Does the vendor address what happens to the bill when the work takes an hour instead of six?
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.
The license expressly permits ThoughtRiver as part of managed services for a customer's legal clients. Marketing compares minutes of assisted review with hours of lawyer work, and the named Shoosmiths testimonial concerns complex supply agreements. Those savings can affect a client's bill as well as internal capacity. A record designed to allocate assisted work to billable time, or guidance on fees and client disclosure, is not described.
Outside Counsel Guideline Readiness
Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?
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.
The public register identifies Microsoft Azure in the United Kingdom, SendGrid in the United States, and Okta, ABBYY Vantage and Zoho Desk in Europe. It gives functions, data categories and transfer safeguards for those providers. The list supports part of a client's data handling review, but does not name the general purpose language model providers or supply a ready made client AI consent and disclosure pack.
Court Disclosure Support
If a judge’s standing order requires an AI disclosure, can the product produce one?
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 Digital Issues List preserves flagged issues, risk levels and resolution status and can be shared or downloaded. That gives a contract reviewer a record of what required attention and how the review progressed. Word changes and collaboration add further context. An export combining the exact model, retrieved sources and human verification for each generated passage is not described, so these records do not by themselves form a complete AI disclosure certificate.
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 Pactly if
- You want a small analysis subscription before wider CLM adoption.
- Versioned positions should control Word review and suggested drafting.
- Repeated analysis should preserve the values a reviewer has corrected.
Choose ThoughtRiver if
- A specialized legal review engine is the core purchase.
- Email and Word intake should feed shared issues and redlines.
- Unlimited users and monthly contract allowances fit the organization.
In summary
Pactly
Pactly combines explicit playbook positions with lifecycle workflows and portfolio question tables. Its review and analysis interfaces distinguish proposed AI work from human acceptance and corrected results.
ThoughtRiver
ThoughtRiver uses Lexible for contract risks, obligations and redlines, with email, upload and Word intake. Team collaboration and portfolio reporting sit around that review engine, and packages distinguish contract volume.
Questions buyers ask
What is Lexible's role in ThoughtRiver?
Lexible is the specialized legal model underlying contract analysis. ThoughtRiver combines it with generative and agentic functionality for questions, proposed edits and review against a team's playbook. From the AI Legal Index, based on each vendor's own published materials as of October 16, 2026. No vendor pays for placement.
Are Pactly Projects and ThoughtRiver Professional equivalent purchases?
No. Projects is a separately metered portfolio analysis product. ThoughtRiver Professional is a review package with unlimited users and a monthly contract allowance, so a comparison of their entry prices alone would omit scope. 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 if a Pactly playbook cannot decide whether language complies?
A position can return an uncertain result for human judgment. The reviewer can inspect matched language, reasoning and the position's standards instead of treating every result as a definite approval or rejection. 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 workflows turn contract text into team action?
For teams handling recurring reviews, AI Legal Index highlights ThoughtRiver's shared issues and redlines and Pactly's versioned positions with explicit acceptance. Pactly also connects the agreement to approval and signature workflows.
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.
ThoughtRiver's UK rate remains in pounds sterling; Pactly Projects allowances are not interchangeable with review package volumes.