Patentcloud vs PatentSight+: how they compare in 2026
Patentcloud and PatentSight+ are both patent analytics platforms for portfolio valuation, due diligence, landscaping and litigation work, built on curated global patent data with AI layered on top. PatentSight+, from LexisNexis, leads on contract and governance. Its general terms bar training any large language model on subscriber inputs, require notice before compelled disclosure, and defend customers against infringement claims outside the liability cap. Its Protégé assistant returns the full query behind every answer so the analysis can be rerun. Patentcloud's lead is what a buyer can verify before calling sales. It offers its ISO 27001 certificate for download, with a scope naming all six applications, names data centers in Oregon, Tokyo and Taipei, and publishes bundle plans with entitlements. Its terms let it analyze a client's searches and notes to improve its services. PatentSight+'s own ISO 27001 certification is described as forthcoming.
Which one fits
Choose Patentcloud if
- Your security review wants the certificate itself. Patentcloud offers its ISO 27001 certificate for download on its trust page, with the scope naming all six applications and the company's internal systems, and names its hosting in AWS data centers in Oregon and Tokyo and Taiwan Mobile data centers in Taipei.
- You want to test a patent's validity quickly. Patentcloud's Quality Insights pulls file wrappers, supports claim construction and compares prior art to the claims, and its Semantic Prior Art returns up to 300 references across six jurisdictions, starred where similarity exceeds a stated average.
- You want to buy only the scenario you need. Patentcloud sells five bundles built around due diligence, portfolio analysis, litigation, freedom to operate and an all scenario plan, with published entitlements, monthly or annual billing and free trials.
Choose PatentSight+ if
- You need the training bar and disclosure notice in the contract. LexisNexis's general terms warrant that subscriber inputs to its AI services will not train any large language model and require advance notice so you can seek a protective order before any compelled disclosure.
- You want to rerun any AI answer yourself. PatentSight+'s Protégé explains each step, displays the full query it built, and attaches that query to every answer so the analysis can be reproduced inside the platform.
- You value portfolios against competitors. PatentSight+ covers more than 90 million patent families with manually checked ownership normalization and the published Patent Asset Index, and Siemens describes tracking patent quality across US, German and Chinese markets.
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.
A curated global patent database, Patent Search as a Boolean and bibliographic research tool, and Patent Vault as a portfolio workspace holding up to 100,000 patents with folders, projects and up to twenty collaborators would all work without the models. Semantic Prior Art runs on the vendor's own machine learning to predict relationships between a patent and potential prior art and return ranked references across six jurisdictions. A generative AI Patent Summary condenses each reference and highlights terms that align with the claims at issue; it reached Due Diligence in June 2023, Quality Insights in October 2023 and Patent Vault in February 2024. Design Search matches design patents from an uploaded image, and Quality Insights generates prior art references automatically with a calculated claim disclosure rate. The platform is sold as six applications that can be bought separately, and several do not depend on the models. InQuartik's own framing puts high quality patent data first and analytics over it second.
The models power named capabilities on a platform that works without them. Four AI capabilities are published. Protégé, a generative assistant that turns plain language business questions into structured visual answers, has been generally available since May 2026. AI-Powered Features explain charts and speed analysis, the AI Classifier builds custom technology views, and TechDiscovery, added in October 2024, allows patent search in ordinary words. Underneath sits a platform with its own longer history: a harmonized database of more than 90 million patent family records, manually checked ownership data, legal status tracking, more than 100 attributes and measures including the Patent Asset Index, full text and field search, similarity search, saved search history, and the visualization tools the product was first known for. Remove every model and the analytics platform remains complete. The vendor positions Protégé as changing who can use the platform rather than what it does, replacing complicated filters with simple questions so business leaders and others outside IP can reach the same data.
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.
Every output a user acts on is a patent document that can be opened and checked. Semantic Prior Art returns up to 300 references from six patent authorities. Quality Insights surfaces file wrappers and supports claim construction, and Prior Art Analytics compares references against the claims at issue and calculates the share of claim elements already disclosed. References are ranked by relevance and starred where semantic similarity exceeds the overall average similarity between all patents and their family members and section 102 prior art. A post about a model upgrade reports a pairing success rate for novelty prior art rising from 77 to 86 percent, with the error rate down 40 percent, and marketing claims prior art search time cut by over 50 percent. Those figures measure an internal classification improvement on two third party portfolios rather than the accuracy of the product's output. No failure modes are named. Clause 11 disclaims liability for errors or omissions and places that risk on the client.
Grounding is real and documented, and there is no measured accuracy figure. The grounding goes beyond citation to reproducibility. Every Protégé answer comes with the full search query the assistant built, stated to be fully reproducible within PatentSight+, so a user can rerun the analysis and get the same result. The assistant also explains each step, shows its queries, puts results in context and suggests next steps. Answers rest on the curated harmonized dataset and on published metrics, including the Patent Asset Index method, so the logic can be inspected as well as the data. The assistant's own accuracy is not measured. No precision, recall or error rate is published for Protégé, no test set is described, and no failure mode is named. The figures the vendor does publish measure effort, not correctness, and come from users: reductions in manual analysis effort of up to 70 to 90 percent and up to three times more output. An on demand session is advertised on independently validated accuracy for AI patent classification, but no result is published.
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.
Clause 11 of the Terms of Use states that no legal advice is intended or offered, that the vendor disclaims all liability for any decision taken in reliance on the content, and that the client assumes the risk of possible errors or omissions. That allocates responsibility and says nothing about how the system is supervised. No published material describes what the system does unaided, what constrains it, what review surface a professional works through, or how an output returns to human judgment, and no mode or setting is documented. The starred relevance threshold on Semantic Prior Art tells a reviewer which references exceed average semantic similarity, a single indicator a professional can act on. The platform retrieves, ranks and summarizes patent documents for a professional to assess rather than drafting or acting on a matter.
A written commitment that the model works alongside the user is backed by specific review features, but not by a full control structure. Protégé is said to keep professionals in the driver's seat, and human oversight is one of the five RELX principles the product page says govern all its AI. The review features are concrete. The assistant explains every step of its analysis, shows the full queries it built, puts results in context and suggests next steps, and each answer carries its query so the user can reproduce and inspect it. Support documentation gives guidance on prompting and on validating AI generated insights. Vendor material quotes a named customer valuing the chance to see how the assistant reasons. Missing are any threshold at which a capability acts without review, any distinction between modes with different levels of automation, any confidence signal on an answer, and any account of what happens when an output is wrong or how to report it. Nothing is published about the AI Classifier or the enrichment models, whose outputs enter the dataset rather than arriving as answers a user inspects.
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 post about a model upgrade reports the pairing success rate for novelty prior art on an Nvidia portfolio rising from 77 to 86 percent, with a 40 percent cut in the error rate, and works through a second example on a Masimo portfolio. Marketing claims prior art search time cut by over 50 percent. Those examples name the portfolios analyzed, not customers who deployed the product, so they show the tool working on public patent data rather than use by a buyer. The About page adds more than 440,000 patents handled over 35 years, which describes leadership experience rather than deployment. No named customer, case study or attributed testimonial appears in InQuartik's blog or About page, or in coverage of the company.
Named customers say specific things, but no measured figure is tied to them. Siemens describes using the platform to track patent quality over time against competitors, accounting for acquisitions and divestitures. It notes that the quality indices reflect differences between the US, German and Chinese markets. Christopher Hauke, Head of Strategic IP and Innovation at Schott Pharma AG and Co. KGaA, values seeing how Protégé reasons through a problem, saying it makes the analysis transparent and gives him confidence in the results. The AI Insider Program is said to have developed Protégé with hundreds of participating organizations, with early access feedback shaping its reasoning. The figures are the weak part. Reductions in manual analysis effort of up to 70 to 90 percent and up to three times more output are attributed to users, not measured by the vendor. They are given as ranges with an upper bound and carry no method, baseline or sample. No figure is tied to either named customer.
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.
Section 9 of the Terms of Use binds both parties to hold confidential the contents, terms and all information related to the Agreement for ten years after termination. That protects the deal, not the client's matter material. Nothing in the Terms commits InQuartik to hold in confidence the searches a client runs, the portfolios it assembles, the notes it takes or the reports it generates. Elsewhere the vendor publishes a security posture, not a confidentiality commitment. Three clauses concern the client's search activity, which for a patent professional can itself be privileged work product. Clause 3.2 records that the vendor collects the client's searches, browsing history, notes and other platform activity, clause 3.11 adds the terms, phrases and choices made while searching, and clause 3.4 reserves the right to analyze and compile statistics from that information to improve services and develop new ones. Privilege and work product are not addressed. No position is stated on what any model provider may retain, none being named.
Published commitments are substantive on most points and fall short on two. The product page excludes training in express terms: queries and usage data are never used to train AI models, and customer data is never used to train AI models. Data is not shared outside the customer's organization. A commitment across products is also published: data entered into Protégé is not shared with other LexisNexis products unless explicitly communicated and authorized, which matters because the vendor runs seven adjacent IP products a buyer might assume share data. Retention is addressed as policy and as a control: the vendor cites retention and deletion policies, and users can turn off automatic saving of queries and compare, combine, export or delete saved ones. Personal data is handled under a published Privacy Policy and Data Processing Addendum, and the General Terms return Subscriber Files on request within sixty days of termination. Privilege and work product are not addressed by name. No model provider is named, so nothing says what a third party sees of a query, which matters for strategic questions about unannounced acquisitions and licensing positions.
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.
Clause 11 of the Terms of Use, the customer agreement, states that no legal advice is intended or offered by InQuartik in making any of the content available, and that the vendor disclaims all liability for any decision taken by any party in reliance on the content. The surrounding sentence adds that the client assumes the risk of possible errors or omissions, so the allocation is explicit. The vendor names IP professionals, attorneys, patent counsel, brokers and analysts as its audience, and clause 5.5 contemplates institutional subscriptions for law firms, corporations and government entities, so this is a professional tool sold to professionals rather than a consumer product. Nothing addresses how the product supports a practitioner's competence or supervision duties, and no jurisdiction limit is named, despite a database spanning six patent jurisdictions and validity analysis built for US patents.
A contractual scope limit sits in the terms, while the marketing speaks in decision terms and widens the audience. The General Terms grant a nonexclusive, nontransferable, limited right to use the online services and materials for research purposes, which frames the product as research rather than advice, and the terms address legal professionals separately. The marketing, though, speaks of decision ready insights and high value strategic decisions, with worked examples that are professional questions, such as identifying top acquisition targets in a sector and finding licensing partners for a technology. The vendor openly positions Protégé as widening access to patent data across the organization and letting business leaders reach insights without complex filters. So people who are not lawyers are an intended audience for output that feeds licensing, acquisition and portfolio decisions. Nothing published says what a business user should not do with a Protégé answer, or where a patent attorney's judgment must come in.
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.
No governance position is published for a system whose output informs patent validity and freedom to operate decisions. Nothing identifies who inside the vendor is accountable for the models, no testing regime before release is described as governance, no policy or principles statement exists, and no certification such as ISO 42001 is claimed. Nothing addresses uneven output across jurisdictions, technology fields, filing languages or portfolio sizes, which is where bias would matter on a patent analytics product. A post about a model upgrade does publish a before and after evaluation of classification performance on two named portfolios. That is measurement, not a governance framework, an accountability structure or a testing regime that could be audited. The ISO 27001 certification covers information security management.
A published governance framework, defined outside the product and expressly applied to it, without testing results or a named owner. The framework is the RELX Responsible AI Principles. The product's AI page says all AI in PatentSight+ is governed by them, and the TechDiscovery release says that module was built in line with them. The five principles are listed on the product page: real world impact, minimizing bias, transparency in how insights are generated, human oversight, and governance with strong privacy and security practices. A Responsible AI page on the IP site argues the case for self regulation rather than only claiming compliance. Structured feedback exists: the AI Insider Program gives participating organizations early access, focus groups and feedback channels to surface problems before general release. No person, committee or function is named as accountable for model behavior, and no testing regime before release is described. Bias minimization is named as a principle, and an on demand session advertises independently validated classification accuracy, but no evaluation result is published.
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.
Clause 3.7 lets the client request export, update, correction or deletion of personal information and require the vendor to stop collecting, processing and using it, with a commitment to comply in a timely manner. Clause 3.8 commits to systematic deletion of identity documents once identity is confirmed. Clause 3.5 requires third party processors to comply with data protection regulation, and clause 3.6 acknowledges transfer across borders with security safeguards. Access control and infrastructure protection sit inside the ISO 27001 scope. No retention period is stated for searches, notes, projects or generated reports, and clause 3.1 says instead that the vendor may at all times receive and store such information. Nothing describes what happens to a client's Patent Vault projects on termination; clause 9.4 covers return or destruction of confidential information, which section 9 defines as the agreement's own terms. No subprocessor is named, clause 3.5 referring only to trusted third party processors and service providers. No incident or breach notification practice is published.
Published policy covers most of the ground. Training on customer data is excluded in express terms, and repeatedly. Encryption is stated for data at rest and in transit, with privacy by design named as a development practice. LexisNexis cloud environments, products and security programs are audited annually, and the audit scope is listed: encryption, backup, disaster recovery, access controls, data destruction, breach prevention and confidentiality safeguards. Incident practice is published and tiered, with technical, administrative, business and executive escalation. Subprocessors are handled well. The Data Processing Addendum points to a maintained public subprocessor list, commits to updating it at least fourteen days before any change, and gives the customer fourteen days to object with reasons. Retention and deletion policies are said to exist, and users control their saved search queries directly. Two gaps remain. No retention period is stated anywhere. Access control at product level is thin: single sign on across LexisNexis applications is described as being introduced, not available, and no role or permission model is published.
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.
Clause 11 disclaims liability for errors or omissions throughout the services, states that the client assumes that risk as a subscriber, and disclaims all liability for any decision taken by any party in reliance on the content. Clause 15 is the only indemnification article. It obliges the client to indemnify, defend and hold harmless InQuartik under five heads, including breach, third party IP claims arising from client submissions, and the client's activities in connection with the database and reports. There is no vendor indemnity of any kind. The warranties at clause 10.1 are corporate rather than performance warranties: that the services contain no libelous matter, that the vendor operates lawfully and holds necessary permits, and that it has capacity to contract. Nothing warrants the accuracy, completeness or fitness of the analysis, and no insurance is referenced. Section 12 is headed Limitation of Liability, Cap and Force Majeure.
A published agreement with a real indemnity, and AI output left to the user to verify. The LexisNexis General Terms and Conditions (effective 5 June 2026), which the product links through the LexisNexis terms hub, have LexisNexis defend and indemnify the subscriber against third-party patent, copyright, trademark and trade secret infringement claims arising from use of the service, with that indemnity excluded from the twelve-month liability cap. The AI Services clause says AI output may not be accurate and users must verify it, so nothing stands behind a wrong AI insight. The terms also give 30 days to cure a change that materially degrades the service, failing which the subscriber may terminate, and return of subscriber files on request within 60 days of termination.
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.
No integration into practice systems is published, and the vendor's own position is that none is needed. The bundle FAQ states that the plans let a team work on the Patentcloud platform without introducing additional third party tools, a claim that the platform stands alone rather than a claim of interoperability. No docketing system, document management system, IP management platform or patent office filing interface is named as a connection, no API is documented or referenced, and no integrations page is listed. Export and sharing exist inside the platform's own boundary. PatentMatrix dashboards and Due Diligence and Quality Insights reports can be shared with colleagues and partners, and the KEEP function saves findings into a Patent Vault project for team members. Those move work between the vendor's own applications and users, not into the systems a firm already runs.
Integration is claimed and partly named, without a published catalog or configuration detail. Most of what is established sits inside the LexisNexis family. Single sign on across LexisNexis applications is described as letting users move between products without logging in again, but the vendor says it is being released over time rather than available now. Data can leave the platform: search queries and results can be exported, and a separate product, IP DataDirect, provides a data feed; an older factsheet mentions a developer portal and proof of concept access. TechDiscovery and the AI Classifier are modules within the platform, not integrations. No connector catalog is published, no external system is named as supported, no API documentation for this product was reached, and nothing describes the direction of data flow or the setup required. That matters for a corporate IP department that runs a docketing or IP management system alongside its analytics, since nothing says whether portfolio data can move between them.
Deployment Model and Data Residency
Where the software runs and where the data sits. Multi tenant cloud, single tenant, private deployment, on premises, and whether region of residence is a published option or an enterprise conversation.
The platform runs on a hybrid cloud infrastructure in named locations: Amazon Web Services data centers in Oregon and Tokyo and Taiwan Mobile data centers in Taipei. The vendor states the AWS facilities are certified to ISO 27001, PCI DSS Service Provider Level 1 and SOC 2, and that the Taipei facilities carry Tier III certification in design, facility and operations. Physical and environmental security sits inside the ISO 27001 scope. No tenancy model is stated, so whether the deployment is single tenant or multi tenant and how customers are separated is not known. Processing location is not distinguished from storage location, and which site runs the analysis is not stated. No region choice is offered. The geography is the vendor's architecture rather than a customer election, and clause 3.6 confirms that information collected in one jurisdiction may be moved to servers in another under unspecified safeguards.
Cloud delivery is evident, and neither the tenancy model nor the region is stated. The product is a browser based subscription platform reached through LexisNexis online services, and the General Terms define it as access to online services rather than installed software. Hosting is described only in general terms: the vendor partners with trusted, enterprise grade cloud providers and monitors and improves its infrastructure. That describes a class of provider without naming one or giving a location. Nothing names a data center region, a country of processing or an option to choose one, a real gap for a platform sold across Europe and Asia to customers with residency obligations, and an odd one beside the detailed data protection material the same vendor publishes. Tenancy is not addressed: nothing says whether saved searches, exports and Protégé history sit in a shared or isolated environment, and no single tenant or private option is offered or refused. The annual audit covers backup and disaster recovery, which is resilience practice, not a residency statement.
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.
InQuartik's Trust and Security page states that InQuartik is ISO 27001 certified and sets out the scope: all six Patentcloud applications listed individually, Quality Insights, Due Diligence, SEP OmniLytics, Patent Search, Design Search and Patent Vault, together with internal systems covering development, maintenance, physical security, and the management of application systems, data protection systems and network communications. The certificate is offered for direct download rather than through an account executive or an NDA. The page also names the hosting estate and the certifications those facilities hold. The latest certification announcement is a renewal in the second year rather than a confirmation for the current year. No SOC 2 report of the vendor's own is claimed; the SOC 2 reference belongs to AWS and its infrastructure.
Certification is mentioned without a named standard held for this product, and the one standard named is promised rather than held. The product support documentation says Protégé in PatentSight+ follows the same enterprise security framework used across LexisNexis products and will be ISO 27001 certified. That is future tense: as of this check, the product is not certified on its own account. The vendor says it undergoes regular third party audits to maintain industry leading certifications, without naming any. LexisNexis cloud environments, products and security programs are audited annually, with the scope listed: encryption, backup, disaster recovery, access controls, data destruction, breach prevention and confidentiality safeguards. Audit practice and its coverage are described, but the resulting attestations are not named, dated, scoped or obtainable. No trust center with reports is published for this product.
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.
Semantic Prior Art is described as powered by Patentcloud's machine learning technology, a claim of ownership rather than an identification. The Patent Summary feature is described as generative AI without naming a model, a provider or an architecture, and a model upgrade is discussed in terms of classification performance without saying what was upgraded. No foundation model or model provider is named anywhere, and nothing states whether the generative component, which sends patent text to a model, is built in house or supplied by a third party. The Terms of Use are silent on the point. Amazon Web Services and Taiwan Mobile are named, but as infrastructure: naming a cloud host says where a model runs, not whose model it is. The vendor does disclose that machine learning and generative AI sit behind named features. Nothing is named that a change notice could cover.
The vendor describes purpose built AI without saying what sits underneath. Protégé is described as purpose built for patent intelligence, as going beyond what general large language models and AI powered IP workflow tools can provide, and as having agentic reasoning refined through early access feedback. TechDiscovery, the AI Classifier and the enrichment models are each described by function. None is attributed to a model, version, architecture or provider. The comparison with general large language models suggests the assistant is more than a wrapper without saying what it is, and nothing separates models built in house from models licensed and fine tuned. Nothing says where inference runs, what any provider keeps of a query, or whether a customer would be told if the model changed. The data is described in great detail, down to 90 million patent families, ownership data and more than 100 named attributes, while the models reading it are described only by purpose. The reference to trusted, enterprise grade cloud providers names a class of infrastructure supplier, not a model supplier.
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.
Five bundle plans are named: Premium, Patent Due Diligence, Patent Portfolio Analysis, Patent Litigation and Freedom to Operate, each built around a stated patent scenario with a feature comparison table showing what it includes and excludes. Separate pricing pages exist for the individual products. The unit of charge is one account per plan, with additional seats on request. Entitlements are quantified: storage for 100,000 patents, up to 1,000 customizable folders and up to twenty collaborators. The bundle discount is stated as up to 79 percent against standalone subscription. Billing is monthly or annual, charged automatically to a credit card at the start of each cycle, and plan changes and cancellations take effect from the next cycle. Free trials include seven day trials and two free validity analysis reports. Custom bundles and additional seats go through a sales conversation. Plan figures are displayed in the comparison tables on the pricing pages.
No pricing information is published at any level, including the unit of charge. The product pages, AI pages, Responsible AI page, resources and news, support centers and the LexisNexis legal and terms pages were all checked. There is no pricing page and no figure, band or unit on the vendor's own pages; the routes offered are a demo request and a contact form. The terms confirm that pricing is negotiated rather than public. The Subscription Agreement is defined as the General Terms plus Supplemental Terms plus the rates in the Price Schedule, and the terms distinguish transactional pricing plans from fixed price and fixed term arrangements without publishing either. A buyer can learn that two charging shapes exist, and nothing about what either costs. Third party listings describe customizable pricing by quote and subscription term pricing, which confirms the absence rather than adding structure.
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.
The buyer segments are named individually: IP professionals, attorneys, dealers, brokers, scientists, engineers, financiers and designers, and clause 5.5 of the Terms contemplates institutional subscriptions for law firms, corporations and business, charitable or government entities. The five bundle plans are named practice scenarios, each mapped to the work it supports: due diligence before buying or licensing, portfolio analysis at any scale, litigation response by finding weaknesses in the patent at issue, freedom to operate by clearing products in target markets, and an enterprise plan covering every scenario. A dedicated application serves standard essential patent work, naming 5G and 6G claim charting and FRAND issues, and another serves design patent clearance. US, European, Japanese, Chinese, Korean and WIPO documents are named as the semantic prior art scope. The limits are not stated. Nothing says which jurisdictions fall outside coverage, and the validity and file wrapper analysis in Quality Insights is described for US patents without saying what is unavailable elsewhere.
Data coverage is quantified: more than 90 million patent family records, harmonized and enriched with manually checked ownership data, legal status tracking and more than 100 attributes and measures. Buyers named range widely: corporations, law firms, regulators and academic users. The vendor says the assistant is meant to widen access from IP specialists to business leaders and others in the organization. Uses are listed concretely, with worked example questions on acquisition targets in a named sector, how a named technology landscape has changed, finding licensing partners and cutting portfolio fees. Benchmarking, due diligence, competitive analysis, litigation risk and identifying nonpracticing entities are also listed. A named customer describes quality indices that account for differences between the US, German and Chinese markets. No limits are stated. No technology area is named as better or worse covered, no jurisdiction is out of scope, nothing says what the AI Classifier handles poorly, and nothing separates this platform's coverage from the adjacent LexisNexis IP products.
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?
No provision of the published agreement addresses training, model improvement or machine learning. The Terms of Use, last updated 1 May 2022, run to twenty one articles, and none mentions the models the product ships, though the vendor describes Semantic Prior Art as running on its own machine learning and Patent Summary as generative AI. The quoted clause is the closest. It permits analysis and statistical compilation to improve and develop services, and names neither training nor machine learning.
Its subject matter is broader than a typical usage statistics clause. Clause 3.2 says the vendor collects the client's searches and browsing history, notes and other platform activity, and clause 3.11 adds the terms, phrases and choices made while searching. What may be analyzed under the quoted clause therefore includes a patent professional's search strategy and working notes, not telemetry alone. Clause 3.4 also permits sharing analysis or statistics publicly or with third parties in aggregated form that does not identify individuals. Nothing published states that client material is not used to train.
The LexisNexis General Terms and Conditions (effective 5 June 2026), which the product links through the LexisNexis terms hub, warrant that subscriber inputs and files submitted to the AI services will not be used to train any large language model and will be treated at least as confidential information. The product page says the same as policy, adds that data is not shared outside the customer's organization, and commits that data entered into Protégé is not shared with other LexisNexis products unless explicitly communicated and authorized.
Prompt and Output Retention
How long does the product keep what a lawyer typed, and can that be set to zero?
The agreement says material is stored and does not say for how long. The quoted clause says the vendor may at all times receive and store usage information. Clauses 3.2 and 3.11 list what is stored: IP address, software and hardware attributes, searches and browsing history, the client's notes, and the terms, phrases and choices made while searching, configuring alerts or bookmarking. No retention schedule, deletion cycle or maximum period appears in the Terms of Use or the privacy policy, and nothing gives the client a retention setting.
The client does have a route by request over personal information rather than over the work. Clause 3.7 lets the client require export, update, correction or deletion of personally identifiable information and require the vendor to stop collecting, processing and using it, with a commitment to comply in a timely manner, though the vendor may charge a reasonable cost. Clause 3.8 commits to deleting any identity document once identity is confirmed. Nothing addresses what becomes of Patent Vault projects, saved reports or search history on termination.
Retention of the user's own queries is under the customer's control as a product feature. Search queries are saved by default, saving can be turned off, and the user can compare, combine, export or delete saved queries. That turns retention from a policy a buyer must trust into a setting the buyer can operate. On a platform where a query can reveal an unannounced acquisition target or a licensing strategy, turning off saving and deleting history is the control that matters.
Policy commitments sit around it. The vendor says it keeps retention and deletion policies, its annual audit covers data destruction, and the General Terms provide a file of Subscriber Files on request made before or within sixty days after termination. Two limits remain. No retention period is stated for anything, so a buyer cannot tell how long an undeleted query or a Protégé conversation persists. The control is described for search queries; nothing says whether Protégé conversation history can be turned off and deleted the same way.
Ethical Walls and Matter Segregation
Does retrieval respect the firm’s ethical walls, or can the model read across them?
Patent Vault organizes work into projects with customizable folders and up to twenty collaborators per account. Project members must be authorized to edit before they can save findings into a shared project through the KEEP function, and reports and dashboards are shared deliberately with named colleagues rather than being open by default. The quoted clause restricts an institutional subscription to individuals designated as subscribers at purchase, so access is by named user rather than open to the whole firm.
The firm configures and maintains that permission structure, which is a collaboration model rather than a segregation mechanism. Nothing addresses walls between matters or between a firm's clients inside one account, nothing describes what stops a colleague on one engagement seeing work saved from another, and no conflicts or screening capability is published. The product holds its own repository and searches a public patent database rather than a customer document system, so there is no source access model to inherit.
Separation is claimed specifically at one boundary, and no permission model is documented within a customer. The claim is that data entered into Protégé is not shared with other LexisNexis products unless explicitly communicated and authorized. That draws a wall inside the vendor's own family, which matters because LexisNexis publishes at least seven adjacent IP products and a large legal research estate. The vendor also says data is not shared outside the customer's organization, and the annual audit covers access controls.
The internal model is not documented. No roles are listed, nothing describes how access to saved searches, exports or Protégé history is granted or restricted between colleagues on the same subscription, and no administrator capability is published. The concern is concrete. A corporate IP department may need to wall off an analysis for an unannounced acquisition, and a firm running analyses for competing clients has an ordinary conflicts problem. Single sign on across LexisNexis applications is described as being introduced, not available.
Third Party Request and Subpoena Notice
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
Compelled disclosure is addressed and notice is not mentioned. Clause 9.1.2 carves compelled disclosure out of the confidentiality obligation on the quoted terms, and clause 9.1.3 adds an exception for disclosure required in connection with litigation, arbitration or administrative or other investigations and proceedings. Both permit disclosure, and neither commits the disclosing party to tell the other in advance, to give it a chance to seek a protective order, or to notify it afterwards.
Disclosure is limited to the extent of the legal obligation, which constrains scope but is not notice. Clause 14.6 states that InQuartik may cooperate with legal authorities and third parties in investigating any suspected or alleged crime or civil wrongdoing, again with no notice commitment. The terms do not reserve discretion over notice either; they do not reach the question. Section 9 defines the confidential information it protects as the contents, terms and information related to the Agreement, so the client's searches, projects and notes are not obviously covered by the article that contains these exceptions.
The confidentiality clause of the LexisNexis General Terms and Conditions (effective 5 June 2026), which the product links through the LexisNexis terms hub, allows disclosure required by law, regulation or court order only on advance notice to the other party so it can seek a protective order to prevent or limit the disclosure. Subscriber inputs and files submitted to the AI services are held to that same confidentiality standard.
Primary Law Corpus Provenance
Where does the law in this product come from, and does the vendor have the right to use it?
Coverage is described by jurisdiction, and the source of the underlying data is not identified. Semantic Prior Art returns US, European, Japanese, Chinese, Korean and WIPO documents, Quality Insights validity analysis is described against US patents, and the platform is presented as holding global patent data. No data supplier, feed, national office agreement or open data source is named, no update schedule or currency date is published, and no license or rights basis is stated for any part of the database.
The nearest the terms come is clause 2.5, which excludes from the vendor's service commitments any restrictions imposed by the database source, such as a jurisdiction's patent office, naming a category of source without identifying one. Clause 5.7 asserts that all right, title and interest in the Database and the Content belong exclusively to InQuartik and bars the client from mining it or building a searchable database from it, which asserts the vendor's rights downstream without addressing how the underlying records were obtained.
The data source is named, its makeup is described in detail, and the basis on which the vendor holds it is clear. Protégé draws on the PatentSight+ harmonized global database of more than 90 million patent family records, enriched with ownership data, legal status tracking and more than 100 attributes and measures, including the Patent Asset Index, a proprietary metric whose method the vendor publishes. The underlying material is public patent documentation from national and regional offices.
What the vendor owns and licenses is the harmonization, the manually checked ownership data, the enrichment and the metrics built on top. Support documentation adds that Protégé uses PatentSight+ data and public information to generate responses. Two limits remain. Public information is not defined, so a buyer cannot tell what material other than patents may enter an answer, which matters when the assistant is asked business questions about companies and markets. No individual data supplier is named, so the inputs behind ownership data and legal status tracking cannot be audited.
Good Law Verification
Does the product tell you when the authority it just cited has been overruled?
For a patent rather than a case, whether an authority still stands is a question of validity and legal status, and Patentcloud computes that itself. Quality Insights is described as a one click solution giving consolidated data to evaluate the validity and quality of a US patent, surfacing file wrappers, supporting claim construction and generating prior art comparisons. It generates prior art references that bear on validity, and Prior Art Analytics compares references against the claims of the patent at issue and calculates the share of claim elements already disclosed in the file wrapper.
A semantic similarity ranking stars references above a threshold defined against the average similarity between all patents and their family members and section 102 prior art. The method is only partly described. No third party citator or commercial treatment service is named; the computation is the vendor's own, and the product performs the analysis rather than telling the user to check elsewhere.
The vendor publishes its own status signal and shows it inline. On a patent platform, the good law question is whether the right still stands rather than how a case has been treated. Legal status tracking is a core enrichment of the database and one of the more than 100 attributes a user can filter and analyze on, so status is a property of every record in a result set, not a separate lookup. Ownership data answers the related question of who holds the right now, resolving assets to their true corporate owner through manual checks rather than the assignee as filed.
Third party listings describe real time legal status validation. Two limits remain. Nothing published says how often legal status is refreshed; an older factsheet describes weekly updates with a two working day lag, and whether that still holds was not established. No accuracy or confidence information comes with the status or ownership determinations, which bear directly on freedom to operate and licensing conclusions.
Refusal and Uncertainty Behavior
What does the product do when the answer is not in the corpus?
Semantic Prior Art ranks every reference it returns by relevance between the patent at issue and the abstract and first claims of the reference. It stars references whose semantic similarity exceeds the overall average similarity between all patents and their family members and section 102 prior art, and the user can narrow the search by adding selected claim text or keywords. Nothing describes what the product does when it cannot ground a result.
It does not say what a user sees when no reference passes the threshold, whether an empty or weak result is distinguished from a failed search, or what happens where coverage in a jurisdiction is thin. No path for declining to answer is documented. The agreement addresses the same ground only by allocating risk, with clause 11 stating that the client assumes the risk of possible errors or omissions, which is a disclaimer rather than a description of behavior.
A response to ambiguous input is described, though only in general terms. The vendor says the platform gives clear guidance when facing complex or ambiguous input, helping teams ask better questions and get structured, contextualized answers. So an unclear question is said to produce guidance rather than a confident answer. Support documentation gives guidance on prompting and on validating AI generated insights, and every answer carries the full query the assistant built, so a user who suspects a misreading can see how the question was interpreted before relying on it.
That reproducibility is the practical uncertainty control here. No threshold is stated at which input counts as ambiguous, no confidence signal comes with an answer, nothing describes the assistant declining or reporting that it cannot answer, and no failure mode is named. The claim sits on a marketing page rather than in documentation of observable behavior.
Fabricated Citation Record
Does a public court record exist addressing fabricated or hallucinated legal citations in output from this product?
The AI Hallucination Cases database maintained by Damien Charlotin records no case naming Patentcloud or InQuartik, and general search returns no filing, sanction, order or judicial finding involving either. The product does not draft legal argument or generate citations to case law. It retrieves patent documents from a database and ranks and summarizes them, and every reference it surfaces is a real patent record the user can open, though the generative Patent Summary feature does produce synthesized descriptions of those documents. This is a statement about the public record rather than a finding about the product.
The AI Hallucination Cases database kept by Damien Charlotin holds no entry naming PatentSight, PatentSight+ or LexisNexis Intellectual Property Solutions as the tool used. PatentSight+ analyzes patent data and produces business insights rather than citations to legal authority, and returns the full query with every answer.
Bar Guidance Alignment
Has the vendor engaged in public with the ethics opinions its buyers are bound by?
Clause 11 of the agreement states in the quoted terms that no legal advice is intended or offered. It adds that the vendor disclaims all liability for any decision taken by any party in reliance on the content, and that the client, as a subscriber, assumes the risk of possible errors or omissions. The product is sold to patent attorneys whose validity analysis informs opinions. No named authority appears. No bar ethics opinion is cited, no guidance from a patent bar or an office of enrollment and discipline is discussed, no regulator is named, and nothing maps the product against the professional conduct obligations of the practitioners it is sold to in any jurisdiction. The disclaimer sits in terms last updated in May 2022.
Professional duty is engaged in general terms, and no bar or regulatory authority is named. A Responsible AI page on the IP site makes an argument rather than a disclaimer. It considers AI in a regulated profession, notes that many users of IP analytics are lawyers and draws consequences for how principles should be framed. It argues that in a period of rapid change self regulation is often the better path, with principles clear enough to build confidence and flexible enough to adapt.
Human oversight is one of the five RELX principles stated to govern all AI in the platform. No bar association, rule of professional conduct, patent office code of practitioner conduct or ethics opinion is cited or mapped to the product, in any jurisdiction. That matters because patent practice has its own professional rules, including the duty to disclose material prior art, and because the vendor widens the audience for its output to business leaders who are not bound by any of them.
Billing and Fee Posture
Does the vendor address what happens to the bill when the work takes an hour instead of six?
The savings claims are quantified and aimed at cost. Prior art search time is said to fall by over 50 percent, and the pitch is that a user will never again collect patent data by hand or outsource a prior art search, a claim about displacing outside spend. The bundle material adds savings of up to 79 percent against standalone subscription, a pricing discount rather than a claim about matter economics. Nothing addresses what happens to the bill when a task that took six hours takes one.
No record of AI assisted work is produced for each matter, nothing exists that a firm could show a client about what the analytics contributed, and no guidance on fee or disclosure treatment is published. The buyer may be a corporate IP department, a law firm or a broker, and the claim about displacing outside counsel is addressed to the client side.
Nothing published addresses what happens to the bill when AI assisted work takes an hour instead of six, and the vendor's own claims make the question hard to avoid. Users are reported to have found that Protégé cuts manual analysis effort by up to 70 to 90 percent and allows up to three times more output. Patent analytics work is done both in house and by law firms billing clients, so that is a direct claim about billable time.
No record of AI assisted analysis by matter is described, nothing marks an output as generated by Protégé rather than built by an analyst, and no guidance is given on fee or disclosure treatment for a firm passing analytics work to a client. With no pricing published, a firm also cannot establish the platform cost of a piece of work. The platform's portfolio fee analysis concerns the client's renewal costs, not the bill for AI assisted work.
Outside Counsel Guideline Readiness
Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?
No subprocessor list is published, and nothing suggests one is available on request. The quoted clause refers only to trusted third party processors and service providers as a category, committing that they will protect the information and comply with data protection regulation, and names no party. No statement identifies which model providers, if any, see client content. No foundation model or provider is named anywhere, while the vendor describes its machine learning as its own and its Patent Summary feature as generative AI.
Amazon Web Services and Taiwan Mobile are named as data center operators, but naming a host says where a model runs, not whose model it is. Clause 20.1 makes both parties data controllers, so there is no processor relationship, and therefore no data processing addendum, subprocessor annex or disclosure pack for clients.
A maintained subprocessor list and a forwardable data pack are published, and no model provider is named. The subprocessor list sits at a public URL with the controls a firm would ask for. The Data Processing Addendum authorizes processors from that list, commits the vendor to updating the list at least fourteen days before changes, and gives the customer fourteen days to object with reasons. The pack for clients is also there and is drafted to be forwarded: a published Privacy Policy and Data Processing Addendum, both incorporated into the IP terms.
Product support documentation confirms that personal data is processed only to provide the services and that approved subprocessors are disclosed. No model provider is named for Protégé, TechDiscovery, the AI Classifier or the enrichment models, so a firm asked by a client which AI providers see its patent strategy questions cannot answer from published material. The only reference is to enterprise grade cloud providers, which is infrastructure.
Court Disclosure Support
If a judge’s standing order requires an AI disclosure, can the product produce one?
No published material addresses court disclosure or certification of verification. Nothing discusses judicial standing orders on AI, no disclosure template or guidance is published, and no export produces a record for each document of the model used, the sources drawn on and the human verification applied. The platform is marketed for patent litigation, with a bundle built around finding weaknesses in a patent at issue, and its claim charts and validity reports are prepared for disputes where an opponent or a tribunal may ask how the analysis was produced.
Reports can be exported and shared, and they list the prior art references relied on, which is a record of sources. Nothing identifies the model used, separates generative Patent Summary output from retrieved document text, or records what a person verified, and nothing describes any of this as serving disclosure. Clause 11 places the risk of errors or omissions on the client without offering anything the client could file.
A record of what the AI did exists and can leave the platform, but it is not offered as a disclosure artifact. Every Protégé answer carries the full search query the assistant built, and the vendor says the analysis can be fully reproduced within PatentSight+ on that basis, so the method behind an insight is preserved. The assistant also explains each step and puts results in context. Search queries are saved automatically and can be exported, and the Patent Asset Index method behind many outputs is published.
A customer challenged on how an analysis was produced has material to answer with. None of it is packaged as disclosure. Nothing is offered as an artifact for a tribunal, examiner, auditor or opposing party, there is no certification or declaration template, nothing marks an exported output as AI generated, and no guidance covers when Protégé use should be recorded or disclosed in due diligence, a licensing negotiation or litigation.
In summary
Patentcloud
Patentcloud, from InQuartik Corporation of Taipei, is a patent analytics and search platform sold as six applications on one patent database: Patent Search, Design Search, Patent Vault, Due Diligence, Quality Insights and SEP OmniLytics. Quality Insights assesses the validity of US patents, Semantic Prior Art uses the vendor's own machine learning to rank references across six jurisdictions, and a generative Patent Summary condenses references against the claims at issue. According to the AI Legal Index, it states ISO 27001 with a scope naming all six applications, offers the certificate for download and publishes bundle plans. Its data centers are in Oregon, Tokyo and Taipei.
PatentSight+
PatentSight+ is LexisNexis's patent analytics and IP intelligence platform, covering more than 90 million patent family records with ownership normalization and the Patent Asset Index. It benchmarks portfolio strength and value and scopes technology landscapes. It also finds licensing partners and acquisition targets and supports due diligence and litigation risk work. Its generative assistant, Protégé, answers plain language business questions and shows the query behind each answer. According to the AI Legal Index, it states that all its AI is governed by the RELX Responsible AI Principles, and it names Siemens and Schott Pharma among customers. Its terms refer to a price schedule set in each subscription, and its ISO 27001 certification is described as forthcoming.
Questions buyers ask
Patentcloud vs PatentSight+: which is better for patent analytics?
They lead in different places. PatentSight+ publishes stronger contract terms, a governance framework and a reproducible assistant. Patentcloud publishes its certificate, its hosting locations and its plan structure. Buyers who need a verifiable attestation before a sales call have more to read from Patentcloud. From the AI Legal Index, based on each vendor's own published materials as of September 27, 2026. No vendor pays for placement.
Does PatentSight+ train AI on client queries?
No, by contract. The LexisNexis general terms effective 5 June 2026 warrant that subscriber inputs and files submitted to its AI services will not be used to train any large language model and will be treated as confidential. PatentSight+ also lets users disable saving of search queries and delete them. Patentcloud's terms let it analyze collected information, including searches and notes, to improve its services. From the AI Legal Index, based on each vendor's own published materials as of September 27, 2026. No vendor pays for placement.
Is PatentSight+ ISO 27001 certified?
Not on the product's own account. Its support documentation says Protégé follows the LexisNexis enterprise security framework and will be ISO 27001 certified, which is future tense. LexisNexis states that its cloud environments and products are audited annually. Patentcloud states ISO 27001 with a scope naming all six of its applications and offers the certificate for download. From the AI Legal Index, based on each vendor's own published materials as of September 27, 2026. No vendor pays for placement.
How are Patentcloud and PatentSight+ priced?
Patentcloud publishes five bundle plans built around patent scenarios, one account per plan with entitlements such as 100,000 stored patents and twenty collaborators, monthly or annual billing and free trials. Its plan prices sit on its pricing pages. PatentSight+'s terms refer to a price schedule set in each subscription. From the AI Legal Index, based on each vendor's own published materials as of September 27, 2026. No vendor pays for placement.
Neither vendor paid for inclusion, placement or a grade, and neither reviewed this page before it published. Everything on it comes from public material on the dates shown. How the index grades.
Three points to weigh. Patentcloud's terms let it collect a client's searches and notes and analyze them to improve its services, and its only indemnity runs from the client. Those are published terms. PatentSight+ states that it will be ISO 27001 certified, which records a plan rather than a certificate held, and its AI terms say output may be inaccurate and must be verified. Neither names the models behind its AI. Neither vendor reviewed this page.