Jurimesh
Jurimesh runs legal due diligence on a corporate transaction from the data room end to the report. A seller's data room usually arrives as an unsorted heap; Jurimesh recognises each document, classifies it, maps it against the buyer's request list and shows what is missing, so the gap analysis happens before anyone starts reading. It then runs agents across the whole set, checking every clause against a library the company describes as more than a thousand expert-authored legal checks, surfacing change-of-control provisions, uncapped indemnities, automatic renewals, expired insurance and drafting defects, with each finding cited back to the clause and schedule it came from. The output is a legal due diligence report the deal team can work in together, with assigned reviewers, review states and comments, rather than a document that has to be assembled by hand afterwards. It connects directly to the systems deal teams already use, naming Ansarada, Virtual Vaults, HighQ and iDeals among virtual data rooms and Google Drive and SharePoint for file storage, so a firm keeps its existing data room rather than migrating. The company publishes a first-pass review of a data room in under twenty minutes and reports customers seeing sixty to eighty per cent less manual review. It sells to M&A law firms, private equity and corporate development teams, and it holds ISO 27001 certification with all data stored and processed inside the EU. Pricing works in Transactions, each covering the documents for one corporate deal. Jurimesh is the product of Artificieel BV, an independent company based in Ghent, Belgium.
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.
Remove the models and nothing remains to sell. The agreement itself defines the Solution as a proprietary software platform that leverages artificial intelligence to facilitate and accelerate legal due diligence by enabling customers to upload, analyse and extract insights from legal and other business documents, so the AI is the definition of the product rather than a feature of it. Every published function is inference over an uploaded set: document recognition and classification against a request list, gap analysis identifying what the seller has not provided, agents running more than a thousand authored legal checks across the data room, extraction of change-of-control provisions, uncapped indemnities, auto-renewals and expired insurance, and generation of the due diligence report. There is no document management layer underneath, by design: the product connects to the customer's existing virtual data room rather than replacing it, so what is left without the models is a connector to somebody else's repository. Checked 5 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.
Grounding is documented as a mechanism rather than claimed as a quality, and none of it is measured. The stated architecture is that every clause in the data room is checked against expert-authored risk guides with every finding cited back to the source, and the product material carries that through: findings are displayed against the clause and schedule they rest on, and the company describes its check library as authored by named practitioners whose reports it publishes separately. For a diligence product that pairing, an authored rule set plus a citation to the source text, is the substantive answer to fabrication, and it is more than most in this lane publish. What is absent is any test of it. No accuracy figure, evaluation, test set, error rate or failure-mode statement appears anywhere, and there is no accuracy or benchmark page. The agreement runs the other way and is recorded here because a buyer should weigh both: article 3.5 expressly disclaims any warranty that the Solution will perform error-free and places on the customer the obligation and responsibility to verify the accuracy and validity of any and all output. The published figures are throughput rather than accuracy.
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.
Review is built into the artifact and the threshold at which the agents act alone is unstated. The oversight surfaces are real and specific: findings are cited to the clause so a reviewer can open the source, the workspace carries per-item review states with named reviewers and timestamps covering reviewed, waiting for review and modified, and the security page commits that every user action is recorded in full audit trails. The agreement adds the obligation rather than leaving it implied, article 3.5 making verification of all output the customer's responsibility and article 4.1.3 requiring the customer to cease use immediately and notify Artificieel on observing any deficiency. What is missing is the machine's own account of itself. Nothing states what the agents do unattended, what routes a finding into review as against straight into the report, what happens when a check misfires, or whether generated text is marked as generated. The product is marketed as handling the entire diligence process, which makes the unstated boundary the live question rather than an academic one.
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 roles and firms, published figures, and no join between them. Three testimonials carry full attribution and each links to its own customer story: Bas Mees, Partner M&A at Rutgers and Posch; Christopher Tournis Gamble, Managing Partner at WAD Capital, whose account is the most operational, reporting work a legal team would take months over completed in a couple of hours; and Hans Kayaert, General Counsel at Aikido. The company's own funding release adds Davy Gorselé, managing partner at Quorum. Eleven organisations appear as logos including Andersen, Van Benthem and Keulen, Vriman, One Peterson, Around Partners, Vybros, 9Corporate and Lighthouse. Separately the site publishes sixty to eighty per cent less manual review attributed only to customers generally, a first-pass data room review in under twenty minutes, four thousand contracts screened and more than a thousand authored checks. None of those figures is tied to a named firm, none is dated, and no method is published. One coincidence belongs on the record because a reader will find it: the name Hans Kayaert appears as a customer General Counsel here and, in the company's own funding announcement, as the representative of Syndicate One, the lead investor.
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.
A published agreement that engages professional secrecy by name, which is rare, and stops short of treating it. Article 10.2 records that Artificieel acknowledges Confidential Information may be covered by the customer's professional secrecy, and article 10.4 commits that the AI models are not trained on the customer's Confidential Information unless explicit consent is given. Article 9.3 is tighter than most improvement clauses in this corpus: anonymised and aggregated data may be collected to improve the Solution provided that data does not include or reference any User Content unless the customer expressly authorises it in writing, so customer content is carved out rather than carved up. Article 9.2 licences User Content solely to provide the Solution, and the security page states that documents, findings and data rooms never leave the tenant they belong to, alongside SSO and full audit trails, with the data processing policy binding personnel to written confidentiality agreements and limiting access to those performing the assignment. Two limbs hold it here. Professional secrecy is acknowledged rather than given any handling treatment, and no matter-level separation inside a customer is described. The confidentiality obligation also expires three years after termination.
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.
Nothing published addresses the advice line, on a product that produces the due diligence report a transaction is priced on. No statement that Jurimesh or Artificieel is not a law firm, no disclaimer that output is not legal advice, no description of the professional judgement a lawyer must apply before a finding reaches a client, no jurisdiction limit and nothing on supervision or competence was located. The agreement is the natural home for such a clause and has none: article 3.5 requires the customer to verify accuracy and validity, which is a statement about correctness rather than about advice, and articles 4.1.6 and 4.1.7 allocate responsibility for input and for regulatory compliance without touching the question. The exposure is specific rather than formal, since the product classifies contractual risk, flags uncapped indemnities and change-of-control triggers, and generates the report itself. The band above does not fit because it describes a boilerplate disclaimer sitting in the terms and there is no such clause. Searched the home page, the security page, the terms and conditions, the data processing policy and the subprocessor page on 5 September 2026; the product and solutions pages were not opened and are named as the limit.
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.
No governance position was located. There is no responsible AI page, no principles statement, no accountable owner or function named for model behaviour, no pre-release evaluation regime and no AI management system such as ISO 42001, and nothing addresses uneven output. The omission is more pointed here than on most records for two reasons. The vendor is established in Belgium and sells into EU legal transactions, and nothing published engages the EU AI Act at all, in a policy set that is otherwise fastidious about EU regulation and cites the GDPR, the Belgian Privacy Law and the ePrivacy Directive by name. And the product's distinguishing asset is an authored check library, so who authors a check, how it is reviewed, and how a firm would know when one is wrong or out of date is a governance question the estate raises and does not answer. ISO 27001 is an information security standard and is credited on the certification row rather than counted here. Site navigation and footer inventoried 5 September 2026.
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 with real specificity, and the technical annex sits behind a portal that was not opened. Retention and deletion are stated as periods rather than principles: on termination live data is deleted within thirty business days and backup data fully overwritten within a maximum of ninety days after that, with a twenty-day export window before deletion begins, and the processing annex sets one year after termination for account and support data. Access is bounded, with SSO, full audit trails recording every user action, personnel under written confidentiality agreements and access limited to those performing the assignment. Incident practice is committed rather than asserted, requiring notification without undue delay with the information the GDPR requires and assistance with the customer's own reporting duty. The subprocessor position is the strongest element and is graded on its own row. What is missing from the readable surfaces is the technical detail: no encryption standard, key management or tenancy architecture is stated anywhere on the site, because Annex II of the data processing policy defers all technical and organisational measures to the trust centre, which was not opened in this pass and is named here as the limit.
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.
A real two-sided position, published and readable before signing, short of anything warranting the output. Article 8.5 commits Artificieel to indemnify, defend and hold harmless the customer for direct damages arising from its own breach of the agreement and from infringement of third-party intellectual property rights in connection with the Solution, which is a vendor-side indemnity on both limbs and is uncommon in this corpus. Article 8.2 sets a remedy ladder rather than a bare cap, requiring renewed performance first and, where that is no longer possible or reasonable, compensation for direct damage limited to the fees paid in the preceding twelve months. The data processing policy mirrors it, with mutual indemnity for breach of the policy or the privacy legislation and the same twelve-month ceiling. Against that, article 3.4 provides the Solution as is, article 3.5 disclaims any warranty of error-free performance, article 8.1 excludes indirect and consequential loss including data loss, and article 8.3 carries a long list of exclusions. Nothing warrants the correctness of a finding, no service credit exists and no insurance position is published.
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.
Named connections into the systems the work actually lives in, with the object of the connection stated, short of implementer documentation. Six counterparties are named on the home page and treated as the product's premise rather than as a badge strip: Ansarada, Virtual Vaults, HighQ and iDeals among virtual data rooms, and Google Drive and SharePoint for file storage, under a claim of direct integrations with every major VDR. What moves is described at workflow level, the platform reading the seller's data room, recognising every document and mapping it to the buyer's request list, and the commercial pitch is explicit that the product works alongside the VDR a firm already uses rather than requiring migration. For a diligence tool the data room is the integration that matters, and it is the one that is named. What is absent is depth: no field mapping, sync direction, trigger condition or permission model is described, no API or developer documentation was located, and nothing addresses document management, matter management or billing systems. The dedicated integrations page was not opened in this pass and is named here as the limit.
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 answered more completely than anywhere else in this pull, and tenancy is asserted rather than described. The security page states that all data is stored and processed exclusively within the EU on ISO 27001-certified infrastructure, and the data processing policy makes it contractual at article 7.1, with article 7.2 setting out the safeguards that would govern any transfer outside the EEA, naming adequacy decisions, the 2021 standard contractual clauses with a transfer impact assessment, binding corporate rules and certification mechanisms. The subprocessor register carries it down to each provider, naming the contracting entity and the hosting location for every one, so a buyer can see that Google Cloud EMEA, Microsoft Ireland and AWS EMEA SARL all host in the EEA. On tenancy the estate offers one sentence, that documents, findings and data rooms never leave the tenant they belong to, which asserts that tenants exist and are isolated without describing the model, and no dedicated, single-tenant or self-hosted option is offered at any tier. The technical architecture sits in the unopened trust centre.
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.
A named standard claimed as achieved, a second claimed as in progress rather than implied, and no scope behind either. ISO 27001 is stated as certified on the home page, the security page and every page footer, the CTO's signed note repeats that the certification is maintained, and the company states that regular third-party audits and penetration tests validate its controls. The handling of SOC 2 is the detail worth crediting: it is labelled implementing, so a buyer is told plainly which standard has been achieved and which has not, where most vendors in this corpus display an undifferentiated badge. A trust centre exists at a published subdomain, is linked from the footer of every page and from the data processing policy as the home of the technical and organisational measures, and a public status page is published alongside it. What is absent is what an assessor would need: no certification body is named, no certificate number or expiry is given, no scope or statement of applicability is published, and no audit or penetration test summary is offered. The trust centre was not opened in this pass, so its contents and whether it is self-serve or gated were not established.
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.
The gap on an otherwise unusually well-disclosed record, and it is visible precisely because the rest is so complete. The vendor's own funding release states that the platform leverages large language models, and the agreement defines the Solution as leveraging artificial intelligence, but no model, version, provider or hosting arrangement for the model layer is named anywhere on the estate, and no commitment to notify customers of a change to it was located. The subprocessor register makes the absence concrete rather than inferred: it is versioned, dated 20 April 2026, and lists eight processors with contracting entity, jurisdiction, nature of processing and safeguard for each, naming Google Cloud, Microsoft Azure, Amazon AWS, ConvertAPI, HubSpot, Slack, tl;dv and Sentry. Those are cloud infrastructure and business tooling. The one AI provider named in the entire document, Anthropic, appears as the processor inside tl;dv, the vendor's meeting recording tool, not as anything touching a customer's data room. Naming where a model might run is not naming whose model reads the deal, and this is the middle band because the architecture is described while what sits under it is not.
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.
The metering model is published in more detail than most price pages manage, and no figure appears anywhere. There is no pricing page in the navigation and the only commercial route is a demo request, but the agreement sets out the unit and its arithmetic precisely. The unit is a Transaction, each entitling processing of the documents for one corporate transaction such as an acquisition, investment or restructuring, consumed on completion of the analysis. Each Transaction covers up to 1,500 documents, with a further Transaction charged per additional block of 1,500 or part thereof, a document over fifty pages counted as one document per fifty pages, and a set under 150 documents charged at half a Transaction. Use beyond the purchased allocation is charged at the per-Transaction price increased by twenty-five per cent. Unused Transactions expire at the end of a term with no carry-over or refund. Fees are stated and payable in euro excluding VAT, invoices fall due in thirty days, price changes require two months notice, and annual indexation follows a published formula tied to the Agoria wage index. A buyer can model the shape of an invoice in detail and cannot learn the rate.
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.
Three buyer segments are defined and differentiated by what each one wants, and the practice boundary is never drawn. Law firms, private equity and corporate in-house teams each carry a dedicated page and a distinct proposition, the law firm framing being the movement of diligence from a cost centre to a profit centre, private equity being a fast read on a target's risk profile, and corporate being diligence brought in house. Practice depth is narrow by design and stated as such: this is transactional diligence for mergers, acquisitions, investments and restructurings, and nothing pretends otherwise. Customer evidence is consistent with the claim, naming M&A practices and investment firms across Belgium and the Netherlands. What is absent is jurisdiction, and on this product that absence is material rather than cosmetic: the value rests on a library of more than a thousand authored legal checks, and nothing published states which legal systems those checks are written against, whether a Belgian check applies to a Dutch or German target, or which languages the document recognition supports. No firm or deal size band is given either.
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?
Training occurs only where the customer has affirmatively enabled it.
The commitment sits in the published agreement and is conditioned on consent, which is what this value records rather than an outright prohibition. Article 10.4 of the general terms provides that the AI models are not trained on the customer's Confidential Information unless explicit consent is given, and Confidential Information is defined broadly enough to reach the documents and personal data a customer uploads. Two provisions strengthen it rather than qualify it. Article 9.3 permits collection of anonymised and aggregated data to improve the Solution only on the express condition that such data does not include or reference any User Content unless the customer expressly authorises it in writing, which closes the improvement route most agreements in this corpus leave open. Article 9.2 licenses User Content solely to provide the Solution. The marketing is more absolute than the contract and the gap is recorded rather than smoothed: the security page states that documents never feed a model and never train a model, without the consent carve-out the agreement contains.
Prompt and Output Retention
How long does the product keep what a lawyer typed, and can that be set to zero?
A specific retention period is published and the customer cannot change it.
Fixed periods are published in the agreement and in the data processing policy, and they are consistent with each other. On termination all customer data and personal data in active production systems is deleted within thirty business days unless retention is required by law, and backup data, which cannot be deleted immediately, is fully overwritten or deleted within a maximum of ninety days after live data deletion. A twenty-day export window runs first, during which the customer may request its data back, with any assistance beyond the standard export functionality charged at the vendor's hourly rates. The processing annex adds per-activity periods, retaining account and support data for one year following termination and handling the documents processed for the core diligence function under the deletion articles. What is not separately addressed is in-service retention: nothing states how long generated findings, reports or the prompts behind them persist while a subscription is live, beyond the general statement that personal data is kept only as long as needed to provide the services.
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.
Separation between customers is asserted in a single specific sentence and no mechanism is published. The security page states that a customer's documents, findings and data room never feed a model, never train a model and never leave the tenant they belong to, which asserts both that tenants exist and that data is confined to them. Around it sit access controls rather than partitions: single sign-on through the customer's identity provider, full audit trails recording every user action, and a data processing policy that limits personnel access to those performing the assignment and binds them to written confidentiality agreements. Nothing states whether the platform is single or multi-tenant, and no permission or role model inside a customer's own workspace is documented, which matters on a product built around collaborative review where a deal team, and on the law firm side potentially conflicting deal teams, work in shared spaces. The technical and organisational measures are deferred to the trust centre, which was not opened in this pass.
Third Party Request and Subpoena Notice
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
Terms commit to notice where lawfully permitted. No transparency report located.
A notice commitment that is unusually complete, appearing twice in the published data processing policy. Article 8.1 provides that Artificieel shall not disclose or transfer personal data to third parties without the customer's prior permission, except where disclosure is required by law or by a court or other government decision of any kind, and that in such a case it shall, prior to any disclosure, inform the customer in full transparency as to the scope and manner of it. Article 9.1 goes further and commits to best efforts to inform the customer as soon as reasonably possible on four triggers, including receipt of a request for information, a subpoena or a request for inspection or audit from a competent public authority, and its own intention to disclose personal data to such an authority. Notice of an intention to disclose, as distinct from notice of a demand received, is rare in this corpus. Article 7.3 adds a further notice duty before any transfer required by EU or member state law, unless the law prohibits informing on grounds of public interest. No transparency report is published, which is what holds this below the top value.
Primary Law Corpus Provenance
Where does the law in this product come from, and does the vendor have the right to use it?
No located public material identifies the corpus behind the product’s answers.
The product's legal content is described by its method of authorship and by nothing else. The check library is the distinguishing asset, marketed as more than a thousand expert-authored legal checks and as risk guides written by practitioners, with the company publishing separate reports under the line that they come from the people who write the checks Jurimesh runs. That establishes that the content is human-authored rather than derived from an external database, which is a real statement about provenance. It stops short of what this signal asks for. No author is identified against any check, no jurisdiction is stated for the library or any part of it, no source material is named, no licensing position is published, and nothing describes how a check is reviewed or how often it is refreshed against changing law. The material the models read alongside the checks is the customer's own data room, so there is no external legal corpus behind an output. Searched the home page, the security page, the terms, the data processing policy and the subprocessor register on 5 September 2026.
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 citations run to clauses and schedules in the customer's own uploaded documents, and its outputs are risk findings, gap analyses and due diligence reports. The adjacent question on this product is currency of the authored check library rather than currency of an authority, since a check written against one year's law may not hold in the next, and nothing published describes how that is maintained; that gap is recorded on the corpus row rather than forced into this value. The value is the honest absence rather than a finding against the vendor. Searched the home page, the security page and the published policy set 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 reach a reliable finding. There is no abstention path, no no-answer state, no confidence indicator against a finding, and nothing on behaviour where a document is unreadable, a clause is ambiguous, or a check has no clear answer on the text. Two published features sit nearby and neither answers the question, so both are recorded. Gap analysis identifies documents missing from the seller's data room, which reports an absence in the material rather than uncertainty in the model's own output. And the interface shows a brief reasoning indicator before an answer, which signals that processing occurred rather than describing how confidence is assessed or what happens when it is low. The agreement addresses the same territory as an allocation of risk, article 3.5 making the customer responsible for verifying all output, which places the burden without describing a behaviour. Searched the home page, the security page and the published policy set 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 name Jurimesh and on the corporate name Artificieel BV. No court order, opinion or disciplinary record naming the product or the company 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?
Public materials refer to professional responsibility in general terms without naming guidance.
Professional responsibility is engaged once, in general terms, and no authority is named. Article 10.2 of the general terms records that Artificieel acknowledges Confidential Information may be covered by the customer's professional secrecy, which is a direct reference to the professional obligation a European lawyer owes rather than a generic confidentiality recital, and it is why this sits above the floor. Nothing builds on it. No bar or law society, code of conduct, ethics opinion or regulator guidance is named anywhere on the estate, no jurisdiction is identified for the proposition despite the agreement being governed by Belgian law and the customer base spanning several European bars, and nothing maps what a firm must do to discharge its own supervision and competence duties when an authored check and a machine reading produce a finding that reaches a client. The regulatory material the vendor does publish is extensive but sits in data protection rather than professional conduct, citing the GDPR, the Belgian Privacy Law and the ePrivacy Directive by name.
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 selling point and never addressed as a disclosure question. The law firm proposition is published as moving due diligence from a cost centre to a profit centre, which is a direct claim about how a firm's economics change when the work compresses, and it sits alongside sixty to eighty per cent less manual review reported by customers and a first-pass data room review in under twenty minutes. Nothing follows from it. No per-matter record of AI-assisted work is described as available to a firm, no guidance on fee or disclosure treatment is published, and nothing addresses what a client is told when the diligence supporting a transaction was produced by agents running authored checks. The gap is sharper here than on most records precisely because the vendor raises the billing model itself: a product sold on the promise that diligence stops being a cost centre is selling a change in what the client pays for, and the estate is silent on whether the client learns of it.
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.
A current, versioned, ungated subprocessor register with contractual change control, missing only the model layer. The register is published as Annex III to the data processing policy, carries a version number and a date of 20 April 2026, and lists eight processors with, for each, the contracting legal entity, the jurisdiction, the nature of the processing and the transfer safeguard relied on. The policy makes maintenance an obligation rather than a courtesy: the list must be updated whenever a subprocessor changes, changes must be clearly indicated and timestamped with effective dates, the customer must be notified, and the customer may object on reasonable grounds within thirty days with a route to terminate if no solution is found. That is forwardable material a firm can send a client unaltered, alongside a published data processing policy and an annual audit right. What it does not contain is any statement of which model provider sees client content, and the only AI company named in it, Anthropic, appears as the processor inside the vendor's meeting recording tool rather than anywhere near a data room.
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.
Substantial elements of a record exist as a property of the workflow, short of anything built for disclosure. Every finding is cited back to the clause and schedule it rests on, so the basis of an assertion can be produced; the workspace records per-item review states with named reviewers and timestamps, so who looked at what and when is captured; and the security page commits that every user action is recorded in full audit trails providing transparency into activity, access and data handling. Taken together that is more of the sources-retrieved and human-verification elements than most records in this corpus can show. What is missing is the model. No model or version is identified against any finding, nothing marks which part of a report was machine-generated as against written by a reviewer, and no export is designed or described for producing the record to a client, a counterparty or a tribunal. No disclosure template or guidance is published, and the agreement, which is otherwise detailed, does not address it.