Clarilis
Clarilis automates the drafting of whole suites of transactional documents, not single templates. A lawyer answers one dynamic questionnaire and the platform returns a complete first draft in Word, together with every ancillary document the matter needs, formatted in the firm's house style. The questionnaires are rules-based and built to follow how lawyers actually reason about a deal, and the automation behind them is designed and maintained for the customer by Clarilis' own professional support lawyers rather than configured by the firm, which is why there are no templates to set up and no legal engineers to hire. Coverage is deep and jurisdictionally specific: over seventy automated templates for commercial real estate in England and Wales, more than fifty from the Property Standardisation Group for Scotland, nearly two hundred corporate documents covering share purchase agreements, early-stage investments, share reorganisations and business purchase agreements, banking work from leveraged and real estate finance facilities to legal opinions and APLMA-based agreements for Asia Pacific, wills and estate planning, and engagement letters. Pre-automated suites exist for Ireland, the United States and Canada, the Canadian content following the CVCA model forms and maintained in line with them. AI Draft is the generative layer on top. Where the automation takes a draft roughly ninety per cent of the way, AI Draft writes the remaining deal-specific content: definitions, clauses, schedules, ancillary documents and covering correspondence, placed in the right position and in house style. It is deliberately confined, unable to alter the rules-based drafting, and every clause it produces is highlighted in the delivered document beneath a notice that AI content requires review. Firms that do not permit generative AI can switch it off. Clarilis Limited is independent and based in Birmingham.
Capability grades
All 15 axes, graded from public sources on the date shown. 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.
The models are a feature layer on a product whose value plainly stands without them, and the vendor says so in its own words. Clarilis describes deterministic, template-based automation as remaining the gold standard for legal drafting, positions AI Draft as augmenting rather than replacing it, and quantifies the split: the automation takes a draft roughly ninety per cent of the way and AI Draft exists to assist with the remaining ten. The architecture confirms the framing rather than merely asserting it. AI Draft is confined so that it creates novel content without changing the logic-generated content, and the FAQ records that AI Draft can optionally be disabled in an automation for firms that do not permit generative AI, with the rest of the platform unaffected. What remains when it is switched off is the entire product: questionnaire-driven assembly of complete document suites, hundreds of maintained templates across four practice areas and five jurisdictions, house-style formatting and the managed service behind it. Graded on that evidence rather than on the quality of the vendor's AI disclosure, which is strong and belongs on other rows.
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.
Nothing is measured, and the vendor publishes its known failure modes with unusual candour. There is no accuracy figure, no evaluation, no test set and no error rate anywhere on the estate, and the ninety per cent figure that recurs throughout is a time-saving claim about the automation rather than an accuracy measure. The limbs about linked primary sources and citation status do not apply and are named rather than counted: AI Draft generates novel contractual language, so there is no authority to cite. What the vendor does publish instead is a specific list of what its own AI gets wrong, telling users that AI content must be reviewed for cross-references because the AI does not yet automatically match references to other clauses, for definitions used but not defined elsewhere, and for legal and commercial effectiveness, closing with the instruction to always treat AI-generated content as a first cut. Naming a concrete limitation of one's own product is rare in this corpus and it is why this sits at the top of the band rather than the bottom. Grounding is described in terms of matter context and codified practice-area knowledge from in-house lawyers, without any account a reader could test.
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.
All four limbs are published, and the controls are mechanisms rather than promises. What the system runs alone is bounded by design: AI Draft produces novel content only where a user invokes a named task, and it is confined so that it cannot change the logic-generated drafting the automation produced, so the boundary between machine and rules is architectural. How a lawyer checks it is built into the artifact rather than left to a dashboard, and this is the distinguishing feature: every AI-generated clause is highlighted in the delivered Word document, and any document containing AI content carries a notice at the top stating that the AI content requires review. The route back to human judgement is stated explicitly and with specificity, the vendor publishing that AI content is novel and has not been reviewed in advance, unlike automated content, and setting out what to check, being cross-references, use of definitions, and legal and commercial effectiveness, before concluding that AI-generated content is a first cut that still needs expert review. A firm that does not permit generative AI can disable the layer entirely and keep the automation. Marking machine-generated text inside the document that leaves the building is a stronger form of oversight than an in-platform review state, because it survives the export.
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.
Named customers with attribution, and the figures live somewhere else. Two customers are quoted with organisations attached, Miri Stickland, Head of Knowledge at Forsters, on risk management benefits from updates being made quickly and consistently behind the scenes, and a Head of Knowledge Management at TLT, by role rather than name, saying the solution exceeded expectations on delivery. Both link to individual customer pages, and CMS is named in a first-party blog post about faster drafting for its Scottish real estate team. Separately the platform material publishes that the system reduces the time taken to produce suites of documents by around ninety per cent, and that firms draft suites ninety per cent faster, with no firm attached to either figure, no date and no method. So the named customers carry no measurement and the measurement carries no named customer, which is this band exactly. A customers section and a case studies section both exist in the navigation and neither was opened in this pass; they are named here as the limit and are the cheapest available upgrade on this record.
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.
Substantive commitments published where a buyer can read them before signing, with two limbs missing. The AI-specific position is unusually complete: neither user inputs nor AI responses are used to train the models, processing runs through zero data retention endpoints, and data is processed in-region. Around it sits a detailed platform position, with encryption at rest and in transit, protected links time-limited and encrypted to 256-bit AES, all requests logged and verified including IP addresses, user-level authority checks restricting access to particular document suites and drafts, SAML 2.0 single sign-on, optional IP lockdown, separate development, testing and production environments, criminal record and eligibility checks on all staff, least-privilege access that is recorded and auditable, and no outsourcing of system development at all. Two things hold the grade. No privilege or work product treatment appears anywhere, on a platform holding transactional drafting for named clients. And no customer agreement, master services agreement or data processing addendum is published, so every commitment above sits on a product page rather than in a contract a firm could enforce.
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.
A real but narrow position on where the product stops, published outside any agreement. The vendor states that AI Draft does not replace professional legal judgment, that AI-generated content should always be treated as a first cut that still needs expert review, and that automated content is carefully reviewed in advance while AI content is novel and has not been. That is a genuine statement about the relationship between the product and the lawyer's own responsibility, and it is more than the boilerplate this band usually describes. What is absent is the advice line itself. Nothing states that Clarilis is not a law firm or that its output does not constitute legal advice, no jurisdiction limit is drawn despite pre-automated content spanning England and Wales, Scotland, Ireland, the United States, Canada and Asia Pacific, and nothing addresses a firm's supervision or competence obligations. There is also no terms of service on the estate in which such a statement could sit, so the position rests entirely on a product FAQ and a blog post. Searched the AI Draft page, the security page and the full footer inventory on 5 September 2026.
AI Governance and Bias Disclosure
Published governance over model behaviour: who owns it inside the vendor, what is tested before release, and what is disclosed about disparate output across matter types, parties, or populations.
A published commitment to an external framework, short of anything audited or owned. Clarilis states that it has signed the Litig AI Transparency Charter, links to it, and describes it as setting out commitments for organisations developing and providing legal AI solutions, promoting responsible innovation while safeguarding ethical and professional standards. That is a named, checkable external instrument rather than a self-authored principles page, which is why this sits above the floor. The security page adds a responsible AI section with four specific commitments: clear content indicators distinguishing AI from rules-based drafting, in-region processing through zero data retention endpoints, no use of data for model training, and adherence to third-party intellectual property rights. What is missing is everything the band above asks for. No management system such as ISO 42001 is claimed, no independent audit of AI governance is published, no accountable owner or function is named, no pre-release evaluation regime is described and no results are given, and nothing addresses uneven output across practice areas or jurisdictions. The ISO 27001 certification is information security and is credited on the certification row rather than here.
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.
Most of the ground is covered in real detail, with retention and incident practice the gaps. Published: encryption at rest and in transit, protected links time-limited and encrypted to 256-bit AES, servers behind a firewall with all access over encrypted communication, separate development, testing and production environments, all data stored on encrypted file systems and backed up daily at minimum, horizontal scaling with active resource monitoring, all requests logged and verified including IP addresses, user-level authority checks limiting access to particular document suites and drafts, SAML 2.0 single sign-on with optional IP lockdown and configurable lockout, pre-employment criminal record and eligibility checks on all staff, least-privilege access that is recorded and auditable, and no outsourcing of development. Hosting is named as AWS and Azure, and the AI layer runs zero data retention endpoints in-region. Regular penetration testing is stated. What is absent is a retention period, since the only statement is that the customer has complete control over platform storage and deletion of data without any period or process described, and any incident notification commitment, which appears nowhere on the readable estate and has no agreement to sit in.
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.
Nothing published addresses who bears the loss when the product is wrong. The footer was inventoried across two pages on 5 September 2026 and carries exactly two entries, a privacy policy and a sitemap. There is no terms of service, no master services agreement, no customer agreement and no data processing addendum anywhere on the estate, so no indemnity, liability cap, warranty position, disclaimer of warranties, service level commitment or insurance statement can be read before entering a sales process. The gap is more visible here than on most records because of what surrounds it: this vendor publishes a certificate number for its ISO certification and a specific list of what its own AI gets wrong, so the absence of any published commercial terms is a choice rather than an oversight. The exposure is real on a product that produces complete suites of transactional documents through a managed service, where the question of who carries a defect in a maintained template is a live commercial issue. The band above requires a standard limitation clause and there is no clause of any kind.
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 the systems a firm runs was located, on a product whose entire output is documents that must then be filed somewhere. The platform is web-based and delivers finished drafts in Word in the firm's house style, which is a format and a delivery convention rather than a connection. Two named third parties appear and both are identity rather than practice systems: SAML 2.0 single sign-on for authentication, and Certivox M-PIN offered as an optional additional security element. No document management system is named anywhere, so nothing addresses iManage or NetDocuments, and no matter management, e-billing, CRM or e-signature counterparty appears. No API, developer documentation or integrations page exists in the navigation, which carries platform, AI Draft, security, managed service, partners and working globally. The absence is notable rather than neutral for a drafting product used at volume in large firms, where the return path into a matter file is the workflow question a buyer asks first. Searched the AI Draft page, the security page, the platform page and the full navigation on 5 September 2026.
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.
Residency is committed rather than described, and tenancy is not addressed. The AI Draft page states that data is hosted in the customer's region via Azure, and the security page makes the same commitment for the AI layer specifically, that data is processed in-region using zero data retention endpoints. That is a regional commitment tied to a named provider, which is more than most records in this lane offer, and it matters on a platform serving firms across England and Wales, Scotland, Ireland, the United States, Canada and Asia Pacific. Infrastructure is named for the platform as a whole, hosted on Amazon Web Services and Microsoft Azure. Against that, nothing states whether the platform is single or multi-tenant, no dedicated or isolated instance is described at any tier, and no on-premises or self-hosted option is mentioned. The nearest thing to a separation statement is a permission control, that user-level authority checks restrict access to particular document suites and drafts, which governs users within a customer rather than the boundary between customers.
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.
The most complete certification statement located in this pull, missing only the period. The security page states that Clarilis is ISO/IEC 27001:2022 certified by BSI across the entire company, and gives the certificate number as IS 677941. That is four of the five things a buyer needs: the standard, the current revision rather than a superseded one, the certifying body, and a scope stated as company-wide, plus an identifier that can be checked against the certifier's own register. Regular penetration testing is stated separately on the AI Draft page. What is absent is the coverage period: no certification date, expiry or surveillance cycle is published, so a reader cannot tell how current the certificate is without looking it up. No report, statement of applicability or summary is published, and there is no trust portal on the estate, so nothing is gated and this is an absence of publication rather than a retrieval limit. No other certification is claimed, and no badge stands unsupported anywhere on the site.
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.
Three limbs answered plainly in a customer-facing FAQ, which is where a buyer would actually look. The provider is named, the vendor stating that it prefers OpenAI's model, and the hosting arrangement is named with it, hosted in Azure, with the AI Draft page adding that data is hosted in the customer's region via Azure and processed through zero data retention endpoints. The vendor also discloses that it uses a range of different models depending on the drafting task and configures them with practice-area knowledge from its in-house lawyers, which tells a buyer that the supply chain is plural rather than single. What fails is model naming and change notice, and the same sentence causes both: the answer says OpenAI's model without naming which model or version, and adds that Clarilis is always exploring the latest models to ensure the best outputs, which is a statement that the set will change and the opposite of a commitment to notify when it does. No subprocessor register is published, though AWS and Azure are named as platform infrastructure on the security page.
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.
No pricing information is published at any level, including the unit of charge. There is no pricing page in the navigation, which carries what we do, solutions, customers, about us and resources, and none in the footer, which carries only a privacy policy and a sitemap. Every commercial route on the estate is the same call to action, book a demo. Nothing states whether the platform is licensed per user, per template, per document suite, per matter or per firm, and nothing addresses how the managed service is charged, which is a material question on this product because the automation is built and maintained for the customer by the vendor's own professional support lawyers rather than configured in-house, so implementation is a service engagement rather than a setup task. No tier names, minimum commitment or term length appears, and because no terms of service or master agreement is published either, the payment provisions that would ordinarily disclose a structure are unavailable. No pricing row is owed on this record.
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.
Coverage is documented with more specificity than any other record in this lane, and the boundary is never drawn. Four practice areas carry their own product lines with counts and named content: real estate with over seventy automated templates for commercial investment and letting in England and Wales plus more than fifty Property Standardisation Group documents for Scotland; corporate with nearly two hundred documents covering share purchase agreements, early-stage investments, share reorganisations and business purchase agreements; banking and finance covering leveraged and real estate finance facilities, simplified lending, security documents, legal opinions and APLMA-based agreements for Asia Pacific; and private client covering wills and estate planning. Engagement letters and in-house legal are addressed separately. Jurisdictional reach is stated product by product rather than as a claim, with pre-automated suites for Ireland, the United States and Canada, the Canadian content based on CVCA model forms. What is absent is the limit: nothing states which practice areas or jurisdictions are not served, no firm size band is given, and nothing identifies a document type the platform handles poorly.
Legal Signals
What each signal meansA signal records what public sources say on the date shown. It is not a grade and it is not a recommendation. Where a signal reads Not addressed, it means the index did not locate the material in public sources on that date, which is a statement about disclosure rather than about the product.
Client Data in Training
Can material a lawyer puts into this product be used to train a model?
A public policy or trust page states no training on customer content, with no matching term located in the published agreement.
A clear and unqualified commitment, published on a product page rather than in an agreement. The AI Draft FAQ answers the question directly, stating that neither user inputs nor AI responses are used to train the AI, and the same page repeats it as a headline security property, that no AI models are trained using customer data. The security page states it a third time under responsible AI, that no data is used for AI model training, and pairs it with two supporting facts: processing runs through zero data retention endpoints, and it is performed in-region. The agreement search this value requires was run against a full footer inventory on 5 September 2026, and produced the shape this record takes: there is no terms of service, master services agreement or data processing addendum on the estate at all, so no improvement right is granted and none is withheld, and nothing in a contract carries the commitment. No opt-out is needed because the position is absolute, and AI Draft can be disabled entirely at automation level for firms that do not permit generative AI.
Prompt and Output Retention
How long does the product keep what a lawyer typed, and can that be set to zero?
The customer sets the retention window and no retention is an available setting.
Retention at the model layer is zero and retention at the platform layer is the customer's to set, and the two are stated separately. For AI processing the vendor publishes zero data retention as a named property, and the security page describes the mechanism rather than the outcome, that data is processed in-region using zero data retention endpoints, which is a specific configuration at the model provider rather than a general assurance. For the platform itself the AI Draft page states that the customer has complete control over platform storage and deletion of data. That is customer-controlled retention, and it is the limit on this row as well as its strength: control is asserted without any period, process or interface being described, nothing states what happens to stored drafts on termination, and no agreement exists on the estate to carry a return or destruction obligation. Searched the AI Draft page, the security page and the footer inventory on 5 September 2026; the privacy policy was not opened and is the rebuttal route.
Ethical Walls and Matter Segregation
Does retrieval respect the firm’s ethical walls, or can the model read across them?
Segregation is asserted in public materials with no published detail on how it is enforced.
Access is restricted at the level of individual document suites and drafts, which is the right granularity for a firm, and no mechanism behind it is published. The security page states that user-level authority checks restrict access to particular document suites and drafts, that all requests are logged and verified including IP addresses, and that any change in access level requires authentication by key stakeholders, which is an unusual and specific control on permission escalation. Optional IP lockdown and SAML 2.0 single sign-on sit alongside it. What is absent is the architecture: nothing states whether the platform is single or multi-tenant, nothing describes how one customer's drafts are partitioned from another's, and no permission model or administrator documentation is published. The distinction matters on a product where a firm's precedents and live transaction drafts sit together, and where the vendor's own professional support lawyers build and maintain the automations, so vendor-side access is a live question the human resource security section addresses only as least privilege.
Third Party Request and Subpoena Notice
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
No located term or policy addresses third party requests for customer data.
No located term or policy addresses third party requests for customer data. The confidentiality section of a master agreement is where this evidence normally sits and no agreement of any kind is published on the estate, established from a full footer inventory across two pages on 5 September 2026 which carries a privacy policy and a sitemap and nothing else. Nothing on the security page or the AI Draft page sets out what happens when a subpoena, court order or regulatory demand reaches drafts or precedents held in the platform, and no commitment to notify, reservation of discretion over notice, or transparency report was located. The question is live rather than formal on this product, because the material held is a firm's own precedent library and its live transaction drafting for named clients. The privacy policy was not opened in this pass and is the rebuttal route on this row.
Primary Law Corpus Provenance
Where does the law in this product come from, and does the vendor have the right to use it?
Sources are identified without stating the licence or rights basis.
The drafting content is attributed to named bodies and no licensing position is published for any of it. The pre-automated suites are sourced rather than generic, and the vendor names the sources: the Property Standardisation Group for the Scottish real estate suite, the MCL drafting committee and curated content from Gowling WLG for commercial real estate, the CVCA model form documents for the Canadian venture capital suite, with the automation stated to be fully maintained in line with changes to those model forms, and APLMA for Asia Pacific facilities agreements. That is a level of source attribution rare in this corpus. What is not published is any licensing or permission position: nothing states on what basis that third-party content is reproduced and automated, and the only adjacent statement is a general commitment on the security page to compliant processing and adherence to third-party intellectual property rights. One distinction is recorded so the row is not misread: AI Draft generates novel content configured with the vendor's own knowledge lawyers' expertise rather than retrieving from this corpus.
Good Law Verification
Does the product tell you when the authority it just cited has been overruled?
No located public material addresses whether authority is checked for subsequent history.
Nothing addresses checking authority for subsequent history, and the product neither retrieves nor cites primary law. Its outputs are assembled and generated transactional documents, and AI Draft produces novel contractual language rather than authority a user would need to verify as still good. One adjacent practice is recorded because it is the nearest thing and is genuinely relevant to currency: the automations are maintained by the vendor's professional support lawyers, and the Canadian suite is stated to be fully maintained in line with changes to the CVCA model form documents, which is template currency maintained by a named team against a named external source. That is maintenance of drafting content rather than a check on legal authority, and it is credited on the coverage and corpus rows rather than here. Searched the AI Draft page, the security page and the platform material on 5 September 2026.
Refusal and Uncertainty Behaviour
What does the product do when the answer is not in the corpus?
No located public material addresses what the product does when it cannot ground an answer.
No located material describes what the system does when it cannot produce a reliable output, though the vendor is more forthcoming about limitations than most. The FAQ publishes a specific list of what AI Draft gets wrong, telling users to check cross-references because the AI does not yet automatically match references to other clauses, to check definitions used but not defined elsewhere, and to verify legal and commercial effectiveness. That is a published account of known failure modes and it is graded on the accuracy and autonomy rows. It is not an uncertainty behaviour: nothing states whether the system signals low confidence, declines a task it cannot complete, or behaves differently when the matter context is thin, and no confidence indicator or abstention path is described. The one hard constraint published is architectural rather than probabilistic, that AI Draft is confined and cannot change the logic-generated content. Searched the AI Draft page including its FAQ, the security page and the AI Draft blog post on 5 September 2026.
Fabricated Citation Record
Does a public court record exist involving output from this product?
No court order, opinion or disciplinary record naming this product has been located as of the date shown. This is a statement about the public record, not a finding about the product.
The AI Hallucination Cases database maintained by Damien Charlotin was searched on 5 September 2026 on the product names Clarilis and AI Draft and on the corporate name Clarilis Limited. No court order, opinion or disciplinary record naming the product or the company was located. One point of context is recorded rather than left implicit: this tracker records hallucinated authority in court filings, and this product generates transactional drafting rather than citations to authority, so a negative result covers less of its risk surface than it would for a research or litigation product. 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?
Public materials refer to professional responsibility in general terms without naming guidance.
One external instrument is named and it is an industry charter rather than professional conduct guidance. Clarilis states that it has signed the Litig AI Transparency Charter, links to it, and describes it as reaffirming a commitment to the safe, ethical and transparent adoption of artificial intelligence within the legal sector and as setting out commitments for organisations developing and providing legal AI solutions while safeguarding ethical and professional standards. Naming a specific published instrument and signing it is more than the generic gesture this value usually records, and it is checkable. It is recorded here as a generic reference rather than named guidance because Litig is a legal technology innovation group and the charter binds vendors, not practitioners: it is not a bar, law society or regulator instrument and it does not map what a solicitor must do. No Solicitors Regulation Authority guidance, Law Society material, code of conduct or ethics opinion is named anywhere, and no jurisdiction is identified despite the product serving six.
Billing and Fee Posture
Does the vendor address what happens to the bill when the work takes an hour instead of six?
Public materials claim time savings without addressing billing or disclosure, and the product sits inside a fee relationship between a lawyer and a client where those savings would change the bill.
The billing consequence is named as a benefit and never addressed as a disclosure question. The vendor publishes that the platform reduces the time to produce document suites by around ninety per cent, and states the commercial effect plainly, that customers improve margin, increase capacity, provide superior client service, aid recruitment and retention and mitigate risk, with the law firm page adding that Clarilis improves cost-effectiveness and helps firms gain competitive advantage. Improving margin on drafting is a direct statement about what the firm keeps when the work compresses. Nothing follows from it. No per-matter record of AI-assisted work is described as available, no guidance on fee or disclosure treatment is published, and nothing addresses whether a client should be told that parts of their transaction documents were generated rather than drafted. The product does mark AI content inside the delivered document, which is the raw material for such a disclosure and is presented for the drafter's review rather than for the client's information.
Outside Counsel Guideline Readiness
Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?
A current subprocessor or model provider list is published.
The model provider is named in customer-facing material, which is the hard part of this question, and no register or pack exists. The AI Draft FAQ states that Clarilis uses a range of models depending on the drafting task and currently prefers OpenAI's model hosted in Azure, and the same page commits that neither user inputs nor AI responses train the models, that processing uses zero data retention endpoints, and that data is hosted in the customer's region. The security page names AWS and Azure as the platform's infrastructure and gives the ISO 27001 certificate number. A firm can therefore forward public pages that name who processes its content and on what terms, and can quote a checkable certificate. What is missing is the rest of the pack: no subprocessor register is published, no data processing addendum or client notification material exists, and no agreement of any kind is on the estate, so there is nothing drafted to be forwarded and nothing a client could hold the firm's supplier to.
Court Disclosure Support
If a judge’s standing order requires an AI disclosure, can the product produce one?
Some elements of the record are available, short of a document level export.
The record travels inside the document, which no other vendor in this corpus does, and it is not built for disclosure. Where a document contains AI content, the vendor publishes that a notice appears at the top of that document stating the AI content requires review, and that every inserted AI clause is highlighted. Unlike an in-platform audit trail, that marking survives export into Word and would reach anyone the draft is sent to, so a firm can show which passages were machine-generated without reconstructing anything. The security page frames the same feature as a responsible AI commitment, clear content indicators to transparently distinguish AI and rules-based drafting. What is missing keeps this below the top value. No model or version is identified against the marked content, nothing records that the required review was carried out or by whom, and no export or report is described for producing an account of AI use to a client, a counterparty or a tribunal. The marking is also plainly intended for the reviewing lawyer and would ordinarily be removed before the document is sent.