Claren vs Summize: how they compare in 2026

C
Claren profile
S
Summize profile
Last verifiedSeptember 25, 2026

Claren and Summize are both UK AI contract assistants for in house legal teams, working through the tools a team already uses. Summize sits in the top two bands on ten of fifteen axes and Claren on nine of fifteen, and each leads on a different half of the grid. Claren leads on professional responsibility and training. Its terms require review by qualified counsel before any output is relied on, warn non lawyers about unauthorized practice, and bar using customer data to train models. Summize's terms permit machine learning on aggregated, anonymized customer data, and carry no statement on legal advice, although it sells answers to sales, finance and HR teams. Summize leads on contract terms and reach. It indemnifies against intellectual property claims and caps liability at the greater of 100,000 pounds or 150 percent of charges. It runs inside Outlook, Teams, Slack, Word, Salesforce and HubSpot, and holds ISO 27001 certified by ISOQAR. Claren caps liability at the higher of 100 pounds or a year's fees and holds no certification of its own.

At a glance

Category
ClarenContract Review & Drafting
SummizeContract Review & Drafting
Founded
Claren2024
SummizeNot published
Headquarters
ClarenLondon, United Kingdom
SummizeNot published
Last verified
ClarenSep 4, 2026
SummizeSep 4, 2026

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.

Claren
AA on AI CentralityThe artificial intelligence is the product. Remove the models and there is nothing left to sell.

The artificial intelligence is the product and there is nothing underneath it. Every function Claren sells is a model output: redlining a contract in seconds with wording edited to the team's stated position, extracting key terms, and answering questions about a document with citations. There is no repository, no workflow engine, no matter system and no document management layer that would survive the models being removed; the terms of service describe the thing being licensed as a software solution utilising artificial intelligence, and the product page markets an AI editor that goes from upload to redline with no setup and no plugins. Even the tier structure is model-shaped, with Pro capped by chat and file upload volume and higher tiers adding AI playbook generation and custom term extraction. Remove the models and a buyer is left with an upload form. Reported here with its located evidence per the standing discipline on A rows. Checked 4 September 2026.

Summize
BB on AI CentralityThe models are the engine of a core capability, layered on a product that would still function without them as a document or workflow system.

The models are the engine of a core capability layered on a product that stands without them. Summize publishes its own three-layer architecture and only the third is AI: a Knowledge Layer holding playbooks and policies, a Contract Operations Layer running the lifecycle from first request to signature inside existing tools, and an agentic AI layer, SIA, described as surfacing that knowledge as instant answers. Remove SIA and a working contract request, repository and operations system remains, embedded in Outlook, Teams, Slack and Salesforce. The vendor's own framing of the layers as distinct, each one powering the next, is what settles this. Checked 4 September 2026.

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.

Claren
CC on Citation Accuracy and Hallucination DisclosureAccuracy is asserted without measurement, or grounding is claimed while output cites sources the reader cannot open and verify.

Limitations are disclosed with unusual candour and accuracy is never measured. Clause 3.4 of the terms is the most forthcoming accuracy statement located in this pull: the solution may contain outdated or inaccurate information, is trained on historical data with specific knowledge cutoff dates, may not reflect recent legal developments or changes in statute or case law, and its outputs may contain errors, omissions or misinterpretations of legal concepts requiring correction by qualified professionals. Clause 3.4.3 disclaims any representation as to accuracy, completeness or adequacy. Against that, the marketing asserts what the agreement declines to warrant, describing the product as built on trusted legal sources and understanding contracts like a lawyer does, and offering answers with citations. No accuracy figure, test set, evaluation, error rate or retrieval method appears anywhere, and the trusted legal sources are never named, so a reader cannot tell what the citations resolve to beyond the customer's own uploaded document. Grounding is claimed, limitations are published, and nothing is testable.

Summize
CC on Citation Accuracy and Hallucination DisclosureAccuracy is asserted without measurement, or grounding is claimed while output cites sources the reader cannot open and verify.

Accuracy is asserted without measurement. SIA is described as providing instant, reliable answers grounded in the customer's own knowledge and standards, which identifies the grounding source as the Knowledge Layer of playbooks and policies but describes no retrieval method behind it. The security page states that on a consistent basis Summize evaluates the effectiveness, quality and security of its AI models, which is an assessment practice asserted with no published result, no test set, no cadence and no scope. No accuracy figure appears anywhere. No failure mode is named on any surface: hallucination is not discussed, and the published performance figures are all speed and volume rather than correctness. Searched the home page, the security page, the AI layer page, the website terms and the SaaS terms on 4 September 2026.

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.

Claren
BB on Autonomy and Oversight ModelA written commitment that the models work alongside a supervising lawyer, with real review surfaces, short of the full control structure: commonly the threshold at which the system stops or what happens after it is wrong.

The requirement for a lawyer to review sits in the contract rather than in a disclaimer, and the control structure around it is not described. Clause 3.3.1 provides that all information, documents, analyses and other outputs must be reviewed by qualified legal counsel before being relied on, implemented or used as the basis for any decision or action, and clause 3.3.3 has the customer acknowledge that Claren has expressly informed it of that requirement. Clause 5.2.10 goes further for one category, prohibiting submission of Claren-generated documents to courts in criminal proceedings without independent attorney review. The product design supports it, with the model producing a redline the lawyer accepts, rejects or edits rather than writing to anything itself. What is absent is the structure: no threshold at which the system acts alone, no confidence or certainty signal surfaced against an individual suggested edit, no abstention state, and no description of what a reviewer sees to distinguish a high-confidence extraction from a marginal one.

Summize
CC on Autonomy and Oversight ModelAutonomy is claimed and oversight is asserted without a mechanism. Human in the loop appears as a phrase rather than a described control.

Oversight is asserted as a slogan rather than described as a mechanism. The positioning is explicit that the business becomes more self-sufficient while legal remains in full control, and that queries which used to reach legal's inbox are answered instantly by the people who needed them. Nothing published says what SIA answers alone versus what a lawyer approves, no threshold is stated, no review surface is described, and nothing addresses what happens when an answer is wrong. The phrase legal remains in full control is the whole of the oversight position, which is the case this band describes. Searched the home page, the AI layer page, the security page and the SaaS terms on 4 September 2026.

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.

Claren
BB on Operational and Outcome EvidenceReal deployment evidence with substance, short of full attribution or measurement: a named customer without figures, or figures without the named customer.

Attribution is unusually complete and measurement is entirely absent. Eight customer logos are published and five testimonials carry a full name, a role and an organisation: Alan Owens, Head of Legal at H&M V Engineering; Arvinder Mangat, General Counsel at Encompass; Carl Dunton, General Counsel at Peak Energy; Chantal Schofield, Knowledge Manager at Telecom Infrastructure Partners; and Jamie Todd, Commercial Counsel at ScreenCloud. Three of the five are the senior legal officer of the named company, which is stronger attribution than a logo strip and stronger than most records in this lane. The quotes are also substantive rather than generic, with one describing the product as helping spot what a reviewer might have missed when working at the edge of their knowledge, and another reporting a lawyer asking after one week that it never be taken away. What holds this at B is that not one figure attaches to any of them: nothing is dated, no cycle time, volume or cost is given, and the corporate claims run to unquantified language about hours saved and backlogs cleared. A case studies section and an ROI calculator exist and were not opened.

Summize
BB on Operational and Outcome EvidenceReal deployment evidence with substance, short of full attribution or measurement: a named customer without figures, or figures without the named customer.

Real deployment evidence with substance, short of measurement tied to a named customer. Named customers carry attributed quotations and dedicated case study pages: Steven McGeagh at Huel on ease of adoption, Julia Trius at Edpuzzle on receiving agreements already in the required format, and Derek Ihnen at Boon Edam on reduced review time. Logos include Revolut, SeatGeek, Miami Heat, Matillion, Sigma Computing, CodeRabbit, KSE and IPC Systems. Figures are published and specific: three times faster contract creation, 40 per cent reduction in deal length, 50 per cent reduction in processing time, six times more contracts reviewed, and two minutes against two hours for an NDA. One figure carries an independent method, a 4,062 per cent ROI attributed to Nucleus Research, which is a named analyst firm rather than an internal claim. Held at B because none of the figures is tied to any of the named customers, none carries a date, and the case study pages were not opened in this pass, so they are credited for existing rather than for their contents.

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.

Claren
BB on Privilege and Confidentiality PostureSubstantive published commitments on confidentiality and training use, short of the full picture: commonly silence on segregation between users or matters, or on what the underlying model provider may retain.

Most limbs are met and the two that are not are both worth a buyer's attention. Training is prohibited in the agreement itself at clause 4.2.4, which is the strongest form this commitment takes. Segregation is documented rather than asserted: each user has a private and segregated data store on Neon, authentication and row-level security for organisation roles run through Clerk, and the security page states there is no cross-contamination between client matters or organisations. The model provider limb is answered squarely, with zero data retention agreements named as in place with OpenAI and Anthropic and each provider's own terms linked. Encryption is AES-256 at rest and TLS 1.2 or higher in transit. Two things hold it below the top band. Privilege is addressed only as data being treated with attorney-client privilege in mind, which is a posture rather than the express privilege and work product treatment the top band requires, and work product is never mentioned. And the contractual confidentiality obligation at clause 12.1 reaches only information clearly labelled or identified as confidential, which is a narrower net than uploaded matter material would ordinarily fall into.

Summize
BB on Privilege and Confidentiality PostureSubstantive published commitments on confidentiality and training use, short of the full picture: commonly silence on segregation between users or matters, or on what the underlying model provider may retain.

Substantive published commitments, and the agreement is readable, which is why this sits above the assertion band. Clause 6.1 grants Summize a licence to store, transmit and process Customer Data solely as necessary to provide the services and states that nothing in the agreement grants any other rights in it. Clause 6.2 requires physical, technical and organisational measures aligned with good industry practice, clause 6.5 imposes confidentiality with named exceptions, clause 6.6 requires daily encrypted backups available to the customer on request, and clause 9.2 requires prompt deletion or return of all Customer Data at the customer's option on termination. The position on the model provider is explicit rather than inferred: customer prompts, completions, embeddings and training data are stated to be exclusive to each customer and not available to OpenAI or used to improve OpenAI models. Three limbs are unmet. Training is permitted rather than prohibited, because clause 6.4 reserves the right to use Customer Data in aggregated, anonymised form to improve the software through machine learning analysis. Segregation is asserted as siloed AI with no published detail on enforcement. And privilege and work product are not addressed anywhere, which is defensible for a product whose buyer is a corporate department rather than a firm but is still absent.

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.

Claren
AA on UPL and Professional Responsibility PostureThe vendor states plainly what the product is and is not, who may use it, and how it supports a lawyer’s competence and supervision duties. Jurisdiction limits are named and any consumer facing surface carries a clear disclosure.

The most complete professional responsibility treatment located in this pull, and it sits in the agreement rather than a footer. Clause 3.1 states plainly that the solution provides information of a general nature, is not a substitute for licensed legal counsel, does not provide legal advice, and creates no attorney-client relationship. Clause 3.3 supplies the competence and supervision limb directly, requiring that all outputs be reviewed by qualified legal counsel before reliance and having the customer acknowledge it was expressly told so. Clause 3.3.2 does what almost no vendor does and names the doctrine: users who are not licensed attorneys are specifically cautioned that use may constitute unauthorised practice of law if used to provide legal advice to others. Clause 3.2 carves out an entire category, stating the product must not substitute for representation in criminal matters, active court proceedings or any matter where liberty is at stake, and will not draft court filings in criminal proceedings without independent attorney review. Clause 3.5 names jurisdictional limits explicitly, identifying variation between the United States and United Kingdom and among states, territories and localities, and placing compliance responsibility on the user. The product has no consumer-facing surface, being sold to in-house legal teams.

Summize
DD on UPL and Professional Responsibility PostureNothing published on the advice line for a product that produces legal work, including where it is sold to people who are not lawyers.

Nothing published addresses the advice line for a product explicitly sold to people who are not lawyers. Summize markets contract answers to sales, finance, HR and procurement teams, states that queries which used to find their way to legal's inbox are taken care of, and gives the example of a salesperson checking renewal terms and a CFO querying payment performance without involving legal. Against that, no statement anywhere says what the output is and is not, no disclaimer distinguishes information from legal advice, no competence or supervision language appears, and no jurisdiction limit is stated despite customers in both the UK and the US. This grade rests on a document that was read rather than on a gap that could not be tested: the SaaS terms and conditions were retrieved in full on 4 September 2026 and contain warranties, indemnities and liability caps but no advice-line provision at all. The website terms of use likewise disclaim only the website. The nearest thing to a position is the marketing line that legal remains in full control, which is about workflow rather than about advice.

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.

Claren
DD on AI Governance and Bias DisclosureNo governance position published for a system whose output affects legal outcomes.

No governance position was located for a product whose entire output is model-generated legal work. There is no responsible AI page, no principles statement, no named owner accountable for model behaviour, no pre-release evaluation or testing regime, no red-teaming description and nothing at all on bias, including nothing on whether redlining or risk flagging performs evenly across contract types, counterparty positions, languages or jurisdictions. That last gap has weight because the product is marketed as operating across multiple languages and jurisdictions. The security page is detailed and entirely about information security, which the axis definition treats as a separate subject and which is graded on the stewardship and certification rows rather than counted twice. Clause 3.4 of the terms discloses accuracy limitations frankly, but disclosing that a model may err is a product warning rather than a governance framework, and it is credited on the accuracy row instead. Searched the home page, the security page, the terms of service and the site navigation on 4 September 2026.

Summize
CC on AI Governance and Bias DisclosureResponsible AI principles are published without a mechanism, a testing regime, or anything a buyer could audit.

Principles are published without a mechanism a buyer could audit. The security page sets out four AI commitments: siloed AI practices, regular assessments of effectiveness, quality and security, ongoing updates to AI capabilities, and a customer feedback loop. Each is a sentence. No owner inside Summize is named as accountable for AI outcomes, no pre-release testing regime is described, no assessment result is published, and there is nothing whatever on bias or uneven output across contract types or counterparties. The company publishes an EU AI Act explainer written by its own General Counsel, which is regulatory commentary for the reader's benefit rather than a disclosure of Summize's own governance. ISO 27001 is an information security standard and does not answer this axis.

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.

Claren
BB on AI Safety and Data StewardshipSubstantive published policy covering most of the ground, short of the full set: commonly no named subprocessor list or no stated incident practice.

Substantive across most of the set, with the specifics thinning at the edges. Retention and deletion are stated in the agreement rather than in marketing: clause 11.6 commits to deleting all content of the customer and its users within 30 days of the contract expiring, and the security page adds that the terms and pilot agreements specify a right to delete data at any time. Access control is described concretely, with authentication and user management through Clerk, account-specific sessions, authenticated API endpoints, row-level security for organisation roles, multi-factor authentication available for administrative access, production access restricted on a need-to-know basis, background checks for staff with access to sensitive systems, and security awareness training at onboarding and ongoing. Suppliers are named rather than gestured at: Neon for data stores, Clerk for authentication, and OpenAI, Anthropic and Google for models. Incident practice exists and is the softest limb, with defined incident response procedures said to carry SLA targets for acknowledgement, escalation and resolution, but no target is published and no customer notification commitment or timeframe appears anywhere. No formal subprocessor register with locations exists; DPAs are available on request.

Summize
BB on AI Safety and Data StewardshipSubstantive published policy covering most of the ground, short of the full set: commonly no named subprocessor list or no stated incident practice.

Substantive published policy covering most of the ground. Deletion is contractual and specific: clause 9.2 requires Summize to promptly delete or return all Customer Data at the customer's option on termination, with retention only where law requires and continuing confidentiality obligations over anything retained. Clause 6.6 requires backups no less frequently than daily, secure and encrypted, in a commonly used machine-readable format and available to the customer on request. Access control rests on ISO 27001 with DevSecOps practices and internal password, equipment and data confidentiality policies described, and clause 3.2 gives an annual audit right over user and password compliance. Regular third-party penetration testing is stated. Two elements of the set are missing: no retention period is stated for the term of the agreement, only for its end, and no subprocessor list is published, with Appendix 3 referenced in clause 8.4 as defining Sub-Processors but not rendered in the published document.

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.

Claren
CC on AI Liability and RecourseLiability is addressed only through a standard limitation clause that disclaims the exposure the product creates.

Liability is addressed through a limitation clause that disclaims precisely the exposure the product creates. Clause 10.1.2 caps total liability at the higher of 100 pounds or the fees paid in the twelve months preceding the claim, and the floor figure is worth naming: for a customer in its first months the ceiling on a claim may be a hundred pounds. Clause 10.1.1 excludes special damage, lost profits, lost savings, lost business opportunity, lost contracts, goodwill, corrupted data and wasted expenditure. Clauses 10.3, 10.4 and 10.5 then address output directly and disclaim it, stating that outcomes are for general information only, are not intended to meet professional requirements, carry no representation or warranty that they are accurate, complete or up to date, and that Claren has no liability for the accuracy of customer content. Clause 9 runs the indemnity one way only, from customer to Claren, and no vendor indemnity of any kind appears. Clause 10.2 preserves liability for death, personal injury caused by negligence and fraud. No insurance position was located. The whole picture is published, dated 11 April 2026 and readable before signing, which is what keeps it off the floor.

Summize
AA on AI Liability and RecourseWhat the vendor stands behind when its output is wrong is published and specific: indemnity scope, caps, carve outs, and any insurance or warranty a buyer can actually invoke.

The strongest liability position located in this pull, and all of it readable before signing. Clause 7.2 gives the customer an intellectual property infringement indemnity covering claims, liabilities, losses, damages and reasonably incurred costs, with a single named carve-out at 7.3 for unapproved combinations, and 7.4 sets out the conduct-of-claim mechanics including that Summize may not settle without unconditionally releasing the customer. The caps are set as a floor rather than a ceiling, which is unusual and materially better for a smaller buyer: clause 8.3 caps general liability at the greater of 100,000 pounds or 150 per cent of total charges, and clause 8.2 sets a separate super-cap for breach of the security and data protection obligations at the greater of 500,000 pounds or 500 per cent of total charges. Clause 8.1 preserves liability for wilful misconduct and anything not excludable by law, and 8.4 makes Summize liable for its subcontractors and sub-processors as if their acts were its own. Warranties are real and invocable: clause 3.6 warrants the software will comply with its specification in all material respects and be free from material errors and defects, 3.5 requires reasonable skill, care, diligence and foresight, 3.8 warrants against malicious code on an ongoing basis, and 7.1 warrants Summize holds the rights needed to supply the service. No insurance position was located. Notably there is no disclaimer of output accuracy in this agreement, unlike several peers.

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.

Claren
CC on Practice Systems Integration DepthIntegrations are listed as logos or marked as coming, with no documentation an implementer could use.

Two integrations are named with real contractual detail and the rest is a number. Slack and Microsoft Teams are named and their behaviour described in the agreement rather than in marketing: clause 2.4 states the solution is designed to be integrated into an organisation's internal communication and workflow system such as Slack or Teams, that Claren may require the customer to hold an active account with one, and that Claren may access the customer's Slack or Teams account and the channels it is instructed to access and deliver content or outcomes through those channels. That is direction of travel and required configuration stated plainly. Beyond it the disclosure stops: the Pro plan lists 15 or more data integrations without naming one, enterprise single sign-on and SAML appear at the tier above, and no document management system, contract lifecycle system, matter management platform or e-signature product is identified anywhere. For a contract review product the absence of any named DMS or CLM is the material gap, since that is where the agreements being reviewed already sit. No integrations page, API reference or developer documentation exists in the site navigation.

Summize
AA on Practice Systems Integration DepthDocumented, verifiable integrations into the systems legal work already lives in, with the depth described: what syncs, in which direction, and what a firm must configure.

The integration set is the product's central claim and it is documented rather than listed. Named targets are Outlook, Microsoft Teams, Slack, Gmail, Microsoft Word, Salesforce, HubSpot and Jira, plus Summize Sign for e-signature and a Claude integration, each with its own dedicated page. What each integration surfaces is described concretely rather than as a logo: a salesperson checking renewal terms inside Salesforce, a CFO querying payment performance across the supplier base, contract context and assistance available in the tool without a new login to manage. The positioning is explicit that there is no separate platform to adopt, which is a statement about direction of travel between systems. Configuration effort is published too: implementation runs in sprints of three to four weeks under a named HERO methodology with in-house implementation staff, typically fully rolled out within twelve weeks. The individual integration pages were not opened, so the grade rests on the named set, the described in-tool behaviour and the published implementation model rather than on their contents.

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.

Claren
BB on Deployment Model and Data ResidencyDeployment model is stated clearly with partial residency detail, or residency is offered without the processing location being addressed, or the tenancy model is stated on its own with no residency detail published.

Region options are published and the processing half is not. The security page states that cloud infrastructure is hosted in United States, United Kingdom or European Union data centres, with data residency options for enterprise customers, and adds that all data including read replicas can be stored in a data centre located in a specific region on request. That is a genuine three-region choice with the tier it attaches to identified, which is more than most records in this lane offer. Tenancy is described functionally through the data layer, with each user given a private and segregated data store on Neon and row-level security for organisation roles, though the platform is never characterised as single or multi-tenant in terms. What is missing is where processing happens as distinct from where data sits: models are called through the OpenAI, Anthropic and Google APIs and no location is stated for any of them, so a customer selecting European Union residency cannot establish from published material that the inference leg stays in region.

Summize
CC on Deployment Model and Data ResidencyCloud delivery is implied and neither the tenancy model nor the region is stated.

Neither limb is stated for the platform. The only hosting location published anywhere is in the website terms of use, which state that the Website is hosted on servers located in the United Kingdom; that governs the marketing site rather than the software, and a website term does not grade the platform. For the platform itself the home page says data never leaves your environment and the FAQ says it is built on Azure enterprise-grade infrastructure, which names the infrastructure provider without naming a region and without stating where customer contract data is stored. Tenancy is not addressed: siloed AI describes the handling of prompts and embeddings rather than a tenancy model, and no material states whether the platform is single or multi-tenant. Searched the home page, the security page, the website terms and the SaaS terms on 4 September 2026.

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.

Claren
DD on Security Certifications and Trust CenterNo independent security attestation located.

No independent attestation is held, and the site contradicts itself about that. The security page states that Claren is currently pursuing SOC 2 Type II and ISO 27001 certification, expected Q2 2026, and separately that Claren uses SOC-2 compliant vendors and third party software providers. Both sentences are careful and both say the same thing: the certifications belong to suppliers and to the future, not to Claren. The home page says something different, listing SOC 2 compliant among the reasons to choose the product with no qualification. Those cannot both be right, and the specific statement governs the general one. Two further facts belong on the record. The expected certification date, Q2 2026, had passed by the date of this check with no published update either way. And the supplier certification that is evidenced is Clerk's, with SOC 2 Type II and ISO 27001 and a link to its trust page; under the standing rule a supplier's attestation does not travel to the vendor without a scope connector, and none exists. A trust centre is said to be available on request and no report, auditor, scope or period is published.

Summize
BB on Security Certifications and Trust CenterCertification is real and stated, short of accessible evidence: a named standard without scope, date, or a way to obtain the report.

Certification is real and stated, and better identified than most records in this band: the ISO 27001 badge names ISOQAR as the certification body and UKAS as the accrediting body, so a buyer can in principle verify the claim against a third party's register rather than take the vendor's word for it. That is the limb most records on this axis miss. What is missing is the rest of the accessible evidence: no certificate number, no scope or statement of applicability, no issue or expiry date, no trust portal, and no route to obtain a report. Penetration testing is described as regular and third-party with no firm named and no dates. A security whitepaper authored by named CTO Richard Somerfield is offered behind an on-page form, which is a request flow rather than open publication. One point stated plainly because the page states it plainly: **SOC 2 is not held.** Summize says it audits infrastructure in line with standards including SOC II and that it intends to investigate and work towards SOC II accreditation in the future, which is intent and is credited to nothing.

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.

Claren
BB on Model Supply Chain DisclosureThe supply chain is partly disclosed: providers named without change notification, or architecture described without the providers.

The providers are named, evidenced and linked, and the models are not identified. The security page states that Claren uses OpenAI, Anthropic and Google's models through their APIs, and the latest open source models on request, and it does not stop at naming them: each provider's own no-training position is cited with a link, to OpenAI's enterprise privacy policy, Google's Gemini API additional terms and Anthropic's privacy terms, and OpenAI's abuse-monitoring retention of up to 30 days is disclosed. Claren adds that it has established zero data retention agreements with OpenAI and Anthropic. That is a fuller account of who touches customer content, and on what terms, than most records in this corpus manage. Three limbs fail. No model or version is named, only the provider, so a buyer cannot establish which model performs a redline. Where inference runs is never stated. And no commitment to notify customers if a provider, model or arrangement changes was located, which matters given the open source option is offered on request.

Summize
BB on Model Supply Chain DisclosureThe supply chain is partly disclosed: providers named without change notification, or architecture described without the providers.

Providers are named without change notification, which is this band's first limb. OpenAI is identified explicitly and in a form that tells a buyer something useful: customer prompts, completions, embeddings and training data are stated not to be available to OpenAI or used to improve OpenAI models, which both names the provider and states what it may not do. The FAQ adds that SIA is built on Azure enterprise-grade infrastructure, which locates the deployment. What is absent is the rest: no specific model or model version is named, no commitment to notify customers when a model or provider changes was located, and no subprocessor register is published, with Appendix 3 referenced in the agreement as defining Sub-Processors but not rendered in the published text.

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.

Claren
CC on Commercial TransparencyPricing is gated behind a demo request while tier names and feature splits are published, so the shape is visible and the number is not.

The shape is visible and the number is not. Three plans are published with names and contents: Pro carries unlimited chats, 100 chat file uploads, 100 data room uploads, AI-powered redlines, a legal-tuned prompt library, 15 or more data integrations and a Slack community; Scale-Up adds enterprise single sign-on and SAML, a dedicated support manager, AI playbook generation, custom contract term extraction and data partitions; Enterprise adds biweekly AI training sessions, enterprise permission and access controls, managed onboarding, direct access to the AI team and priority input on the roadmap. No figure appears at any tier and every call to action is a demand for a demo. The unit of charge is gestured at rather than defined, with a closing note that plans are based on average document usage and that final packages and pricing vary by workflow and document volume, which tells a buyer that volume drives the bill without saying what a unit costs or how many are included beyond the upload caps. An ROI calculator is published and was not opened.

Summize
BB on Commercial TransparencyReal pricing is published for part of the range, with enterprise tiers withheld, or the unit and structure are stated without the figure.

The unit and structure are stated without the figure, and unusually the evidence sits in the published agreement rather than on a pricing page, because there is no pricing page anywhere in the navigation or footer. The SaaS terms define the Order Form as setting out user numbers and type of software licence, which publishes the unit of charge as per-user by licence type. The term structure is published: an initial term with automatic renewal for successive twelve-month periods and 90 days written notice to prevent renewal. So is the escalation: clause 2.2(b) caps any renewal increase at 10 per cent over the preceding twelve-month term for the same plan, tier and package unless a higher cap is agreed, which is a real commercial protection a buyer can read before contracting. Payment terms are 30 days from a valid invoice, fees are exclusive of VAT and sales tax but inclusive of other taxes, and expenses require prior written approval. No figure, band, tier name or feature split is published anywhere.

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.

Claren
BB on Firm and Practice CoverageSegment and practice coverage is described with substance, short of the boundaries: what is supported is clear, what is not is left open.

The work is described with substance and one boundary is drawn sharply while others are left open. What is supported is clear: contract review, redlining, key term extraction and document question and answer for in-house legal teams, across multiple languages and jurisdictions, with named customers spanning energy, telecommunications, retail, technology and drinks. The exclusions are unusually explicit for this axis and come from the agreement rather than marketing: clause 3.2 places criminal matters, active court proceedings and any matter where liberty is at stake outside the product entirely, and clause 3.5 states that the product may not account for specific jurisdictional requirements or recent changes in local law, naming the United States and United Kingdom and variation among states and localities. What is missing is the rest of the picture. No firm segment or size is stated, law firm use as against in-house is never addressed, government legal is not mentioned, and no contract type is identified as unsuitable, so a buyer knows what the product will not touch in criminal work and not where else it stops.

Summize
BB on Firm and Practice CoverageSegment and practice coverage is described with substance, short of the boundaries: what is supported is clear, what is not is left open.

Segment coverage is described with substance and the boundary is left open. Five buying teams each carry a dedicated page: Legal, Sales, Finance, HR and Procurement. Eight sectors each carry their own page: Software, Sports, Finance, Manufacturing, Business Services, Media and Internet, Retail and Telecommunications. Four use cases are published as request, review, repository and analytics, and NDAs are named as a specific contract type with a stated handling time. The buyer is a corporate in-house function rather than a law firm, and law firms are neither claimed nor excluded. What is missing is the edge: no organisation size is stated, no contract types beyond NDAs are enumerated as supported, government use is not addressed, and nothing says where the product stops.

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?

Claren
Never, in the contract

The prohibition is in the agreement and it names the thing. Clause 4.2.4 of the terms of service, effective 11 April 2026, provides that Claren does not use customer data, inputs or any information provided by the customer to train artificial intelligence models or for any other commercial purpose unrelated to providing the services. The security page reinforces it downstream, stating that neither Claren nor its LLM providers train on customer data and that zero data retention agreements are in place with OpenAI and Anthropic, with each provider's own no-training terms linked.

Two qualifiers belong on the record rather than in a footnote. The same terms grant Claren, at clause 7.4, a non-exclusive, worldwide, sublicensable and non-revocable license to use and reproduce customer material for purposes including improving the operation of the solution and the services, which is a product-improvement right sitting alongside a training prohibition without either clause reconciling them. And the security page carves out an exception, stating that data is not used to train models except for updating the company's own Claren Memories or playbooks, which is intra-tenant personalization rather than model training but is a use of the content.

Summize
Permitted, in the contract

Clause 6.4 of the published SaaS terms expressly reserves the right, notwithstanding the security and data protection clauses that precede it, to use Customer Data in aggregated, anonymized form to improve the Services or Software by automated decision processing or machine learning analysis. The clause names machine learning and operates on Customer Data, which is what this value turns on, and the de-identification qualifier is recorded here rather than treated as removing the permission.

Both sides are recorded because they are reconcilable rather than contradictory on a careful reading: the home page promises a contractual guarantee that data is never used to train external models, and the security page states that customer prompts, completions, embeddings and training data are not available to OpenAI or used to improve OpenAI models. Those statements are about third-party models. Clause 6.4 permits Summize's own machine learning analysis on aggregated, anonymized Customer Data.

A buyer reading only the marketing would not expect clause 6.4, and a buyer reading only clause 6.4 would not know the external-model position is stronger.

Prompt and Output Retention

How long does the product keep what a lawyer typed, and can that be set to zero?

Claren
Disclosed fixed window

Periods are stated at both layers rather than left to inference. At the model layer the position is zero: Claren states it has established zero data retention agreements with OpenAI and Anthropic, and discloses the one exception it does not control, that OpenAI may retain API data for a maximum of 30 days for abuse monitoring before deletion or where subject to legal requirements. At the platform layer clause 11.6 of the terms commits to deleting all content of the customer and its users within 30 days of the contract expiring, and the security page states that the terms and pilot agreements specify a right to delete data at any time.

What is not published is a retention position during the subscription itself: nothing states how long an uploaded contract, a generated redline or a chat exchange is held while the account is live, and the Claren Memories and playbooks that the security page says are updated from customer data have no stated lifespan.

Summize
Disclosed without a period

Retention is acknowledged in the published agreement without a stated period. Clause 6.6 requires Summize to perform and maintain backups of all Customer Data no less frequently than daily, secure and encrypted, in a commonly used machine-readable format and available to the customer on request. Clause 9.2 addresses the end of the relationship, requiring prompt deletion or return of all Customer Data at the customer's option on termination, with retention permitted only where and for as long as law requires and continuing confidentiality over anything retained.

Nothing states how long prompts, outputs or uploaded contracts are held during the term, and no configurable retention window is described.

Ethical Walls and Matter Segregation

Does retrieval respect the firm’s ethical walls, or can the model read across them?

Claren
Own model, documented

A separation model is described at both the customer and the matter level, with the mechanism named. The security page states that Claren uses Neon and ensures each user has their own private and segregated data stores isolating data from other users, that there is no cross-contamination between client matters or organizations, and that audit trails are maintained for user activities. Access control is attributed to a named supplier, Clerk, with account-specific login sessions, authenticated API endpoints and row-level security protocols for organization roles.

The claim to separate matters and not merely organizations is the part that distinguishes this from ordinary tenancy language and is what the value records. What is not described is the administration of it: nothing states who configures a restriction, whether a matter can be walled from named users inside the same legal team, what a restricted user sees, or how a conflict is handled. The claim is at the level of architecture rather than of a control a general counsel could operate.

Summize
Claimed, not documented

Segregation is asserted in public materials without published detail on how it is enforced. The security page describes siloed AI practices under which customer prompts, completions, embeddings and training data are available exclusively to that customer and not to other customers, and the home page FAQ repeats it as a siloed AI approach keeping each customer's prompts, data and outputs exclusive to them. No material describes the isolation mechanism, the tenancy model, or how access is administered beyond the agreement's user and password provisions, and nothing addresses separation between matters or contract sets inside a single customer.

Third Party Request and Subpoena Notice

If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?

Claren
Notice committed

Notice is committed in the agreement, on the ordinary conditions. Clause 12.4 of the terms permits disclosure of confidential information where required by law, by a governmental or regulatory authority or by a court of competent jurisdiction, but conditions it: to the extent legally permitted the disclosing party gives the other as much notice of such disclosure as possible, and where notice is not prohibited it takes into account the other party's reasonable requests as to the content of the disclosure.

The obligation is mutual, binding Claren as receiving party of the customer's material. Two limits belong on the record. There is no reporting half, with no transparency report, no statistics on requests received and no periodic disclosure of the types of demand, which is what separates this from the value above it. And the confidentiality obligation the clause sits inside is itself narrowed by clause 12.1 to information clearly labeled or identified as confidential, so the reach of the notice commitment over ordinary uploaded contract material is not certain from the face of the agreement.

Summize
Disclosure addressed, notice absent

Clause 6.5 of the SaaS terms requires both parties to keep the other's confidential information, expressly including Customer Data, confidential and not to disclose it to any third party unless required by applicable law or regulation, permitted in writing by the other party, or the information has become public without default. Compelled disclosure is therefore addressed directly. No commitment to notify the customer of such a request was located anywhere, and no discretion over notice is reserved either.

Searched the SaaS terms, the website terms of use and the security page on 4 September 2026; the agreement notes that a separate confidentiality agreement, if the parties have one, takes precedence over clause 6.5, and no such template is published.

Primary Law Corpus Provenance

Where does the law in this product come from, and does the vendor have the right to use it?

Claren
Not addressed

A corpus is claimed and never identified. The home page states that Claren is built on trusted legal sources and understands contracts like a lawyer does, which asserts that something beyond the customer's own upload informs the output, but no source, publisher, dataset, clause bank, license basis or jurisdiction coverage is named anywhere on the site or in the agreement. The operational description points the other way, with redlines produced against the customer's own stated position and playbooks built from the customer's own material, and the security page confirming that company data updates the company's own Claren Memories and playbooks.

So a buyer cannot establish whether the trusted legal sources are licensed third-party content, the models' general training, or the customer's own precedent. Recorded as the absence with the unnamed claim carried, since crediting an unnamed corpus would be the inference the method exists to prevent. Searched the home page, the security page, the terms of service and the site navigation on 4 September 2026.

Summize
Not addressed

No located public material identifies an external corpus, and the product's design makes the question narrow. Summize grounds its answers in the customer's own Knowledge Layer of playbooks and policies and in that customer's contract repository, rather than retrieving primary law. No external database, publisher or content license is named on any surface and no jurisdictional coverage is claimed. Searched the home page, the three layer pages, the security page and the SaaS terms on 4 September 2026.

Good Law Verification

Does the product tell you when the authority it just cited has been overruled?

Claren
Not addressed

Nothing on any located surface addresses checking authority for subsequent history, and the product does not retrieve or present primary law. Claren redlines contracts, extracts key terms and answers questions about uploaded documents; no case, statute or regulation is surfaced to a user in the published workflow, and the citations the product offers resolve into the customer's own document rather than to authority. The question does not bite on this product class and the value records the honest absence rather than a shortcoming.

The one adjacent disclosure is clause 3.4.2 of the terms, acknowledging that the models are trained to a knowledge cutoff and may not reflect changes in statute, regulation or case law, which is an accuracy limitation rather than a citator position and is graded on the accuracy row. Searched on 4 September 2026.

Summize
Not addressed

Nothing on any located surface addresses whether authority is checked for subsequent history. The product does not retrieve primary law: it operates on the customer's own contracts, playbooks and policies to answer contract questions and run the contract lifecycle. The question therefore does not bite on this product class and the honest value is the absence rather than a penalty. Searched the home page, the three layer pages, the security page and the SaaS terms on 4 September 2026.

Refusal and Uncertainty Behavior

What does the product do when the answer is not in the corpus?

Claren
Not addressed

Limitations are disclosed and behavior is not. Clause 3.4 of the terms is candid about what can go wrong, acknowledging that outputs may be outdated or inaccurate, that the models carry knowledge cutoffs, and that outputs may contain errors, omissions or misinterpretations of legal concepts requiring correction by qualified professionals. Clause 3.3.1 supplies the human backstop by requiring review by qualified counsel before any reliance.

Both are recorded here as what exists and both are more forthcoming than most vendors offer. Neither describes what the system does when it cannot ground an output. No confidence or certainty score is surfaced against a suggested edit or an extracted term, no abstention or no-answer state is described, and nothing addresses the ordinary failure conditions for a contract assistant, such as a scanned or badly formatted agreement, a clause with no counterpart in the playbook, or a question the document does not answer.

Summize
Not addressed

No located public material addresses what the product does when it cannot ground an answer. SIA is described as providing instant, reliable answers grounded in the customer's own knowledge and standards, which is a claim about the normal case rather than the failure case. No abstention path, no no-answer behavior and no confidence or grounding score visible to the user is described, and hallucination is not discussed anywhere including on the dedicated security page. Searched the home page, the AI layer page, the security page and the SaaS terms on 4 September 2026.

Fabricated Citation Record

Does a public court record exist addressing fabricated or hallucinated legal citations in output from this product?

Claren
None located

The AI Hallucination Cases database maintained by Damien Charlotin was searched on 4 September 2026 on the current product name Claren and on the former company name WilsonAI, the name under which the company traded until its rename. No court order, opinion or disciplinary record naming either was located. This records the state of the public record on that date and is not a finding about the product. The signal also sits at an angle to this product class, since Claren redlines and analyses the customer's own contracts rather than generating legal citations, so a fabricated citation is not the failure mode it would ordinarily produce.

Summize
None located

The AI Hallucination Cases database maintained by Damien Charlotin was searched on 4 September 2026 on the product and company name Summize. No court order, opinion or disciplinary record naming the product was located. This records the state of the public record on that date and is not a finding about the product.

Bar Guidance Alignment

Has the vendor engaged in public with the ethics opinions its buyers are bound by?

Claren
Generic reference

Professional regulation is engaged directly and no specific guidance is named. Clause 3.3.2 of the terms cautions users who are not licensed attorneys that use of the solution does not substitute for legal counsel and may constitute unauthorised practice of law if used to provide legal advice to others, which names the doctrine rather than gesturing at compliance. Clause 3.5 acknowledges that legal requirements vary between the United States and the United Kingdom and among states, territories and localities, and places responsibility for jurisdictional compliance on the user.

Clause 3.2 excludes criminal representation entirely. What is absent is any authority: no bar association, no regulator, no rule of professional conduct, no ethics opinion and no jurisdiction-specific guidance is cited, and nothing maps the product's use against a named standard. So the vendor engages the concepts without pointing a buyer at the source, which is the level this value records.

Summize
Not addressed

No located public material engages with bar or ethics guidance. Summize publishes an explainer on the EU AI Act written by its own General Counsel, which is commentary on a regulation for the reader's benefit rather than engagement with professional responsibility guidance about the vendor's own product, and no bar association, law society, regulator or ethics opinion is named on any surface. The buyer is a corporate in-house function rather than a regulated practitioner in private practice, which explains the absence without changing it. Searched the home page, the security page, the layer pages, the website terms and the SaaS terms on 4 September 2026.

Billing and Fee Posture

Does the vendor address what happens to the bill when the work takes an hour instead of six?

Claren
Savings claims only

Savings are claimed and the billing question is never reached. The published claims are unquantified but plain, promising hours back every week, a slashed contract backlog and faster delivery without sacrificing quality, and an ROI calculator is offered as a separate page. Nothing addresses what happens to a bill when that work compresses. No per-matter record of AI-assisted work is described as available, no guidance on fee or disclosure treatment appears, and nothing states whether a redline produced by the model is identified as such in the document or its history.

The direction is worth recording: the buyer here is an in-house legal team, which pays external counsel rather than billing a client, so the compression this signal was written to catch does not arise in its ordinary form. The nearer question for this product, whether a contract negotiated on model-suggested wording is identified to the counterparty or to the business, is not addressed either.

Summize
Savings claims only

Public materials claim time and cost savings without addressing billing or disclosure. Published figures include three times faster contract creation, a 40 percent reduction in deal length, a 50 percent reduction in contract processing time, six times more contracts reviewed, two minutes against two hours for an NDA, and a 4,062 percent return on investment attributed to Nucleus Research. Nothing addresses what happens to a bill when AI-assisted work compresses the time it takes, and no per-matter record of AI-assisted work is described.

The buyer is an in-house department rather than a firm billing a client, which is the inverse of the direction this signal assumes.

Outside Counsel Guideline Readiness

Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?

Claren
Subprocessors listed

The model providers are named in the clear and the forwardable pack is not published. A counterparty asking who touches the data can be answered from the security page without a request: OpenAI, Anthropic and Google supply the models through their APIs, with the latest open source models available on request, and Claren states it holds zero data retention agreements with OpenAI and Anthropic. Each provider's own no-training position is linked to source.

Neon is named for data stores and Clerk for authentication, with Clerk's own SOC 2 Type II and ISO 27001 status linked. That satisfies the naming limb squarely rather than by naming infrastructure. What is missing is the third limb and the register. There is no published subprocessor list with roles and locations, and the artifacts drafted to be forwarded are gated: data processing agreements are available upon request and the trust center is available on request, so a buyer cannot hand anything to a counterparty from published material alone.

Summize
Subprocessors listed

A model provider is named openly on the public security page, which states that customer prompts, completions, embeddings and training data are not available to OpenAI or used to improve OpenAI models, and the home page FAQ adds that the system is built on Azure infrastructure. That is a statement about who touches customer content, reachable without a sales conversation. What is not published is a subprocessor register or a forwardable client-facing pack: Appendix 3 is referenced in clause 8.4 of the SaaS terms as defining Sub-Processors but is not rendered in the published document, no data processing agreement was located at any access tier, and the security whitepaper is offered behind an on-page form rather than published openly.

Court Disclosure Support

If a judge’s standing order requires an AI disclosure, can the product produce one?

Claren
Partial record

An activity record exists and nothing states that it distinguishes model work from human work. The security page commits to maintained audit trails for user activities, listed alongside the segregation and privilege statements, so a record of who did what in the platform is published as a feature. Nothing beyond that is described. No statement says the trail records which redlines, extractions or answers were model-generated as against lawyer-entered, no model or version is attributed to any output, no export route is described for a client, an auditor or a court, and no guidance or template for disclosing AI use is published.

The question has real weight on this product because the output is edits to a contract that the counterparty will see, and a legal team asked later whether particular wording originated with a model would need exactly the attribution the record does not describe.

Summize
Not addressed

No located public material addresses court disclosure or verification certification. No audit trail or activity export is described on any surface, the model behind a given answer is not disclosed to the customer, and no record of human verification is mentioned. The product is a corporate contract intelligence system rather than a litigation tool, so the question bites weakly, but nothing published answers it. Searched the home page, the three layer pages, the security page and the SaaS terms on 4 September 2026.

What neither one publishes

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.

Signals neither addresses in public material
  • Primary Law Corpus Provenance
  • Good Law Verification
  • Refusal and Uncertainty Behavior

Which one fits

Choose Claren if

  • You want the professional line drawn in the contract. Claren's terms require all outputs to be reviewed by qualified counsel before reliance, warn non lawyers that advising others with it may be unauthorized practice, exclude criminal and liberty matters, and name the jurisdictional limits between the US and UK.
  • You want a contractual bar on training and named model providers. Claren's terms state that customer data is not used to train AI models, and its security page names OpenAI, Anthropic and Google, with zero data retention agreements with OpenAI and Anthropic and each provider's no training terms linked.
  • You want data kept in a region you choose. Claren hosts in United States, United Kingdom or European Union data centers, offers regional residency to enterprise customers, gives each user a segregated data store, and deletes all content within 30 days of the contract ending.

Choose Summize if

  • Your business asks contract questions in Outlook, Teams, Slack or Salesforce. Summize runs inside those tools and in Gmail, Word, HubSpot and Jira, so a salesperson can check renewal terms without leaving Salesforce, and it publishes a twelve week implementation model run in three to four week sprints.
  • You want the vendor's liability to be worth something. Summize's terms give an intellectual property indemnity, cap general liability at the greater of 100,000 pounds or 150 percent of charges, set a higher cap for data breaches, and warrant the software free of material errors and defects.
  • Your procurement team needs a verifiable certificate and price protection. Summize holds ISO 27001 certified by ISOQAR under UKAS accreditation, and its published terms cap any renewal price increase at 10 percent for the same plan.

In summary

Claren

Claren, from ClarenAI Company with offices in London and founded in 2024 as WilsonAI by a former Clifford Chance lawyer, is an AI contract assistant for in house legal teams that redlines agreements to the team's position, extracts key terms and answers questions with citations, working through Slack and Teams. The AI Legal Index grades it in the top two bands on nine of fifteen capability axes, with A grades on AI centrality and on professional responsibility, where its terms require counsel review and warn about unauthorized practice. It names OpenAI, Anthropic and Google as model providers and bars training on customer data. As of 4 September 2026 the index located no held security certification and no published price.

Source: AI Legal Index, 2026

Summize

Summize, from Summize Ltd, a UK company, is a contract intelligence system for in house legal teams that works inside Outlook, Teams, Slack, Gmail, Word, Salesforce, HubSpot and Jira, with a knowledge layer of playbooks, a contract operations layer from request to signature, and SIA agents that answer contract questions across the business. The AI Legal Index grades it in the top two bands on ten of fifteen capability axes, with A grades on liability and integration depth. It holds ISO 27001 certified by ISOQAR, and its published terms carry an intellectual property indemnity and liability caps with fixed floors. As of 4 September 2026 the index located no published price, no advice line statement and no data region.

Source: AI Legal Index, 2026

Questions buyers ask

Claren vs Summize: which is better for in house legal teams?

The grid places them one axis apart: Summize sits in the top two bands on ten of fifteen AI Legal Index capability axes and Claren on nine of fifteen. Claren publishes more on professional responsibility, training and data region. Summize publishes stronger liability terms, deeper integrations and a verifiable ISO 27001 certificate. Teams whose business users will query contracts directly have more integration to read from Summize and more guardrails to read from Claren.

Does Summize train AI on customer contracts?

Its terms allow its own machine learning on customer data in aggregated, anonymized form to improve the software. Its security page says customer prompts, completions and embeddings are exclusive to each customer and are not available to OpenAI or used to improve OpenAI models. Claren's terms state that customer data is not used to train AI models, though they separately license customer material to improve its services. Graded by AI Legal Index against 15 capability axes and 12 legal signals, including privilege handling and citation accuracy, from each vendor's own published materials, verified September 25, 2026. No vendor pays for placement.

Does Claren say its outputs are not legal advice?

Yes, in its terms. They state that Claren is not a substitute for licensed counsel, gives no legal advice and creates no attorney client relationship, that every output must be reviewed by qualified counsel before reliance, and that non lawyers using it to advise others may commit unauthorized practice of law. Summize's terms contain no statement on the advice line. Graded by AI Legal Index against 15 capability axes and 12 legal signals, including privilege handling and citation accuracy, from each vendor's own published materials, verified September 25, 2026. No vendor pays for placement.

What security certifications do Claren and Summize hold?

Summize holds ISO 27001, with ISOQAR named as the certification body under UKAS accreditation, and says it does not yet hold SOC 2. Claren's security page says it is pursuing SOC 2 Type II and ISO 27001, expected in Q2 2026, and relies on certified suppliers; its home page lists SOC 2 compliance without that qualification. Graded by AI Legal Index against 15 capability axes and 12 legal signals, including privilege handling and citation accuracy, from each vendor's own published materials, verified September 25, 2026. No vendor pays for placement.

What do Claren and Summize both leave unpublished?

A price, an accuracy measure and a record of AI use. Neither publishes a figure for any plan, and neither publishes an accuracy rate, a test set or what its AI does when it cannot answer. Neither describes an export showing which answers or redlines a model produced. Neither names bar or regulator guidance on AI, although both are sold to legal teams whose colleagues query contracts directly. Graded by AI Legal Index against 15 capability axes and 12 legal signals, including privilege handling and citation accuracy, from each vendor's own published materials, verified September 25, 2026. No vendor pays for placement.

Disclosure

Three readings to weigh. Summize's terms permit it to use customer data in aggregated, anonymized form to improve its software through machine learning; its statements about OpenAI concern third party models only. Claren's home page lists SOC 2 as compliant while its security page says SOC 2 Type II and ISO 27001 are still being pursued, and no report is published. Claren's terms also grant it a license to use customer material to improve its services. Claren and Summize were both verified on 4 September 2026. Neither vendor reviewed this page.

Neither vendor paid for inclusion, placement or a grade, and neither reviewed this page before it published. Everything above comes from public material on the dates shown. How the index grades.

Contact

Correct a record, or ask how something was graded

Every grade and every signal on this index is drawn from public sources and dated. If a record is wrong, out of date, or missing an artifact the index did not locate, send the source and it will be reviewed and the record redated. Vendors are welcome to submit documentation. Nothing on this index is for sale, including a listing, a placement, or a grade.

AI Legal Index

The AI Legal Index is an independent index that tracks changes to AI vendors in legal. It holds 303 vendors across 9 categories, each graded on the same 15 capability axes and recorded against 12 legal signals, from public sources. No vendor pays for inclusion, placement, or rating.

Index Status
Last index update
September 24, 2026
The AI Legal Index is an editorial reference. It is not a regulatory body, not a law firm, and nothing published here is legal advice or a recommendation to retain or avoid a vendor. Records are verified against published sources, bar guidance and public court records. Where a record reads not addressed, the material was not located in public sources on the date shown. See the Methodology page for evaluation standards and limitations.
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