Pactly vs Robin AI: how they compare in 2026
Contract operations and a broader legal assistant lead to different choices here. Pactly combines Word playbooks, contract generation, approval routing and signature workflows, with Projects available for separate portfolio analysis. Robin AI combines cited contract answers and drafting with legal research, related agreement context and obligation management. For teams seeking help beyond their own contract collection, AI Legal Index identifies Robin AI's legal research capability as a scope difference from Pactly's contract centered review. Pactly offers a more explicit structure for repeated analysis: each Projects column poses a question, cells carry reasoning and source excerpts, and human corrections survive reruns. Robin AI also offers managed services alongside software. The useful comparison is which work the legal team wants inside the product and which work it wants people to perform.
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.
Models interpret agreements, answer questions, extract metadata, compare precedents and generate proposed edits across Robin's legal intelligence platform. Pinpoint citations lead from an answer to the underlying contract, and legal research can reach public authorities. These are central reasons to use the software. The current platform also manages a corpus of contracts and their relationships, tasks, reminders and obligation dashboards. Those record and workflow functions can still organize legal work without generating a new answer. The separate managed services offering adds human contract work, while the platform combines model driven analysis with continuing contract operations rather than only a standalone drafting assistant.
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.
Robin connects generated answers to pinpoint citations that open the underlying primary contract. Corpus analysis draws on the customer's agreements and precedents, with relationships among contract families available for comparison. A separate legal research feature reaches public authoritative sources. This gives reviewers a way to inspect the basis of a contract answer, rather than accepting an unsupported response. No reproducible accuracy study, hallucination rate or evaluated language set accompanies the current platform. The claimed coverage of more than 200 languages describes availability, not equivalent reliability across them, and no automatic subsequent treatment check for cited legal authority is specified.
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.
Robin supports live contract editing against the customer's precedents and returns answers with citations that a reviewer can open. Its Word workflow presents proposed changes and comments for a lawyer to consider, while the managed services offering adds human legal professionals as a separate service. Obligations can be organized into tasks and reminders, and structured metadata can be tailored to business requirements. These surfaces make review and follow up possible. A precise boundary at which the system must decline a task, stop a proposed action or escalate an unsupported conclusion is not specified for the current legal intelligence platform.
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.
Robin advertises faster contract review and shows customer, media and investor names alongside its platform. The detailed speed claim in its earlier product material came from the vendor's own legal team testing its add in, rather than a defined external customer study. Its current platform describes corpus review, metadata extraction and obligation management, but does not attach a dated evaluation protocol to those outcomes. Press coverage and financing explain the company's visibility; they do not establish how a particular customer's review process changed. The headline efficiency claim therefore remains distinct from a measured deployment with an identified workload and baseline.
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 service terms impose confidentiality duties on people and subcontractors who need customer material. The DPA requires customer instructions for personal data and supports deletion, audit and prior notice of legally compelled disclosure where permitted. Tenant identifiers, role controls and authorization for support access separate customers and restrict staff access. The security page requires express consent for model training, but the service terms authorize training and improvement using inputs, outputs and user content. The DPA gives personal information narrower processing protections. Privilege and work product are not expressly addressed, and organization isolation does not establish ethical walls between matters within a firm.
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.
Robin's terms distinguish the software from legal advice and from legal services requiring professional authorization. Users remain responsible for deciding whether generated material is suitable and for checking mistakes. The platform gives lawyers pinpoint contract citations and editable proposals, while a separate managed services line adds people to contract review. These are distinct delivery arrangements rather than an assurance that every automated answer has received legal advice. The general software terms do not define a jurisdiction specific practice boundary or map the tool to a lawyer's competence obligations. Business customers may use it across jurisdictions unless a separate agreement narrows that scope.
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.
Robin's DPA commits to designing and testing software so its operation is sufficiently transparent for customers to understand and use. The current platform supports verification through primary contract citations, and the security program includes testing and corrective action for data protection controls. Those commitments do not set out an AI governance framework with named responsibility, a release evaluation process or results on uneven output across languages, matter types or populations. The advertised language breadth makes the distinction relevant: supporting an interface or producing an answer in a language does not establish tested reliability for legal work in that language.
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.
Robin's DPA specifies four access roles, single sign on, multifactor authentication, tenant identifiers and permission checks on API requests. It names eight processors, including AWS, Anthropic, Bedrock, SageMaker, Snowflake and operational analytics services. Customer data incidents require notice within 72 hours of awareness, with investigation assistance and costs allocated by responsibility. Backup recovery keeps 30 days of history, while requested deletion receives confirmation within 60 business days. Those periods cover particular copies or deletion handling, not an ordinary retention limit for every prompt and output. Logs, support access and model processing remain subject to the DPA's confidentiality and access controls.
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.
The service terms include a Robin indemnity for specified patent, copyright and trade secret claims against the authorized service. Customer content, modifications and unapproved combinations fall outside that protection, with modification, replacement or a proportionate refund among the available responses. Generated output is not guaranteed accurate, and Robin disclaims responsibility for errors in it. The DPA separately requires assistance and reimbursement of reasonable incident response expenses when Robin causes the data incident. A numerical general liability cap is not stated in these standard terms. The protections therefore address defined platform and data risks without promising compensation for an incorrect legal answer.
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.
Robin's Word add in opens from the ribbon after installation and connects through the user's account or single sign on. Ask reads the current agreement, Draft creates text for insertion, Edit changes a selected passage and Research adds links to legal sources. A reviewer selects the playbook and accepts, refines or rejects tracked edits in Word. Saved changes synchronize back to the Legal Intelligence Platform for portfolio reporting and later precedent use. The integration preserves the distinction between user and counterparty edits. The wider import connectors are not named on the platform overview, so these specific controls concern the Word connection.
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.
Robin uses AWS infrastructure with tenant identifiers to isolate customer data and geographically distributed storage for resilience. The DPA permits necessary processing in the United States, United Kingdom, Singapore, South Africa, Australia and Germany, and in other jurisdictions where service delivery requires it and appropriate safeguards apply. It expressly recognizes transfers for language model interactions. These are permitted processing locations, not a menu of selectable hosting regions. Anthropic Claude through Amazon Bedrock is described within isolated tenant contexts. No customer residency selector or contractual promise confining every storage and inference step to one selected country is specified.
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.
The DPA identifies SOC 2 Type II, ISO 27001:2022 and Cyber Essentials as validating Robin's security measures. It also provides for annual audits on customer request, access to relevant confidential reports and correction of exceptions. Controls include multifactor authentication, tenant segregation, immutable logging, encrypted backups and tested recovery. Report availability at the linked trust center is unknown. The accessible agreement does not identify the audit coverage period, assessor or certificate scope. Its specific standards are more informative than a general security badge, but do not independently establish the current attestation's boundaries.
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.
Robin's DPA names Anthropic as an API supplier, Amazon Bedrock for model hosting and Amazon SageMaker for model training and deployment. Its technical annex explicitly describes Anthropic Claude processing through Bedrock in isolated tenant contexts. AWS supplies the cloud environment, while separate named services handle analytics and operations. Changes to the processor list receive notice through website updates or other communication channels, with an objection route. Exact production model versions and routing by feature are not identified. A processor change mechanism does not guarantee that customers receive notice whenever a model version changes within an existing provider.
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.
Robin's service terms describe a subscription with authorized user licenses, fees governed by the service agreement and billing arrangements for access. That identifies both the commercial structure and the access unit, although the public platform sends prospective customers to a demo rather than showing a rate. A free trial is governed by separate data handling conditions and does not establish the price of a paid deployment. Managed services are an additional delivery option, with their scope and fees requiring agreement. No public subscription amount, implementation charge or complete price matrix accompanies the current legal intelligence platform.
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.
Robin's platform is organized around contract review, precedent reuse, corpus analysis and obligation management for legal operations. Teams can examine regulatory questions across their agreements, identify relationships among contract families and extract metadata tailored to their business. Managed services add human help with contract work, and the product is offered to corporate legal teams and firms. Language support extends beyond 200 languages, but the platform gives no corresponding jurisdiction by jurisdiction evaluation or reliability boundary. Its stated tasks are concrete commercial contract workflows; that breadth does not establish coverage for every specialist practice, court process or regulated advisory role.
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.
Robin's security page requires express consent before training or feature development uses customer data. The standard terms nevertheless authorize storage of inputs and outputs for training and allow user content to improve services, including models. The DPA limits personal data to instructed business purposes and permits aggregate improvement data. These provisions have different scopes; the standard terms do not supply a blanket prohibition on training with all nonpersonal customer content.
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 terms acknowledge storing inputs and outputs, including for training. The DPA calls for return or destruction at termination, subject to technical feasibility and legal retention, and confirmation within 60 business days after a deletion request. Backups retain 30 days of recovery history. Those periods concern requests and backup copies rather than a defined active lifetime for the primary prompt and output history. A configurable zero history setting is not specified.
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.
Tenant identifiers and customer specific API tokens isolate one organization from another. Four application roles, least privilege and prior authorization for support access restrict who can handle customer content. The technical annex also places model processing within isolated tenant contexts. It does not describe an internal client matter wall or an integration that preserves a legal document management system's per user restrictions when retrieving contract material.
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.
The DPA requires Robin to tell the customer before a law, court or regulator compels processing or disclosure of personal data, unless notice is legally prohibited. The customer must have an opportunity to object or challenge the demand. General service confidentiality permits legally required disclosure, so the explicit prior notice protection is clearest for personal data under the DPA. A transparency report listing government demands is not specified in these provisions.
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.
Robin grounds contract questions in the customer's agreements and precedents, with pinpoint links back to the underlying material. Its legal research feature also reaches public authoritative sources, but does not identify a complete inventory of those collections or their licenses. Customer agreements provide a recognizable source for contract analysis. That does not establish the provenance, update cadence or rights basis of all external legal material behind research answers.
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.
The platform gives pinpoint links to underlying contracts and can answer questions using public authoritative legal sources. Those links let a reviewer inspect cited material. A licensed citator, subsequent history signal or automated method for checking whether a judicial authority remains reliable is not described. Contract precedents and related agreement analysis concern the customer's own transactions and do not provide that separate legal treatment 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.
Robin presents linked citations and lets lawyers inspect and edit proposed contract work. Clause risk indicators concern the legal significance of a provision rather than a measured probability that an answer is correct. The current platform and standard terms do not define a no answer response or a confidence threshold that stops generation when support is insufficient. Responsibility for validating the output remains with the user.
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 contains no tool entry naming Robin AI as of October 15, 2026. The platform combines contract review and corpus questions with legal research using public authorities, so it can produce legal assertions even when its main workload is transactional. The database result concerns named court records, not the accuracy of those assertions or the reliability of every cited source.
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.
Robin's software terms distinguish the service from legal advice and regulated legal services. The platform supports checking through linked contract citations, and its educational content concerns contract workflows and adoption of legal AI. A named bar ethics opinion or regulator's professional guidance is not mapped to the product's use in the available account. These product and contractual responsibilities do not by themselves explain a lawyer's jurisdiction specific duties.
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.
Robin advertises faster review and reduced manual contract work for legal teams. The platform's tasks, reminders and obligation dashboards organize legal operations after analysis, but are not described as a client invoice record of AI assisted work. Its subscription and managed services prices are commercial charges for the product. No stated method connects the time saved by a firm's reviewers with how that firm bills or discloses the work to clients.
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 DPA lists eight processors with their functions, including Anthropic, Bedrock and SageMaker for model related services. It also states confidentiality, breach notice, deletion handling and permitted cross border processing. Those provisions give firms concrete material for a client's AI review. The DPA supplies these details even though access to further trust portal reports remains unverified. A single assembled client consent or notification pack is not specified, and standard training permissions still require attention to the agreement's scope.
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.
Contract answers include pinpoint citations that a reviewer can open, and the technical annex records input activity with tenant context. Access and processing records can support a review of what happened in the service. The platform does not describe a per passage export combining exact model version, retrieved sources and human verification. Its contract record and system logging therefore supply parts of an audit trail rather than a complete court 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.
- AI Governance and Bias Disclosure
- Good Law Verification
- Bar Guidance Alignment
Which one fits
Choose Pactly if
- Contract generation, routing and signing belong in one workflow.
- You need a defined subscription for a portfolio analysis project.
- Human corrections must remain intact when question columns rerun.
Choose Robin AI if
- The assistant should also support legal research beyond contract text.
- Related agreements and obligations form part of everyday legal work.
- Managed service support is relevant alongside a software subscription.
In summary
Pactly
Pactly provides contract lifecycle workflows and review against versioned positions. Projects makes portfolio analysis a separate, metered task with cited result cells, retained original values and protected human corrections.
Robin AI
Robin AI combines contract drafting, cited answers, agreement context and obligations with broader legal research. Its software and managed services offer distinct ways to support the legal team's workload.
Questions buyers ask
Is Pactly Projects a legal research database?
No. Projects analyzes the agreements supplied to it and ties results to their text. Robin AI extends its assistant into legal research as well as contract work, which introduces a different source and verification task. 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 make a repeated analysis result inspectable?
A result can contain a value, reasoning and a verbatim excerpt linked to the relevant page. The reviewer can correct or verify the value, retain the original AI result and protect the correction from later reruns. From the AI Legal Index, based on each vendor's own published materials as of October 16, 2026. No vendor pays for placement.
Does Robin AI's software subscription automatically include managed work?
Software and managed services are distinct parts of the offering. The scope of human service support should be distinguished from features a team operates itself. From the AI Legal Index, based on each vendor's own published materials as of October 16, 2026. No vendor pays for placement.
Which difference matters when the team wants a wider legal assistant?
For work extending beyond a supplied agreement, AI Legal Index highlights Robin AI's combination of legal research and contract assistance. Pactly concentrates on the organization's contract workflow and structured analysis of its files.
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.
Research answers and contract extraction rely on different source material; managed services have a separate delivery scope.