Legartis
Legartis is a legal AI workspace for contract work, sold to in-house legal departments and to the procurement and sales teams around them rather than to law firms. It reviews contracts against playbooks the customer defines, drafts and edits from those playbooks, answers legal questions and translates through a Legal Agent, and surfaces risks, deadlines and critical clauses across a whole contract portfolio through dashboards. A Playbook Creator Agent builds a playbook for a contract type in hours rather than weeks, and an AI Quality Score shows, for each individual requirement, how reliably the system currently detects it; customers steer that by correcting the system's work inside test sets. It runs in the browser and inside Microsoft Word, offers a REST API and an MCP integration, and supports every European language. Hosting is in Switzerland and Europe, and the company states it is ISO 27001 certified. Pricing is published in full: a free tier covering two NDAs a month, Professional from CHF 250 per user per month, Team from CHF 300, and custom Enterprise terms. The ability to opt out of model training is offered only on the Team and Enterprise plans. Legartis Technology AG is based in Zurich.
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.
Every capability the buyer pays for is an agent. The product is sold as a Legal AI Workspace built on an agentic framework, and the named components are the Review Agent, the Legal Agent and the Playbook Creator Agent. The conventional software around them, contract repository, version control, e-signature via DocuSign, approval workflows and negotiation, is marked Coming soon across the pricing matrix, so what a customer can buy today is the model layer. Remove the models and there is no document management or workflow system left underneath. 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.
Grounding is real, documented, and unusually candid about failure. The AI Quality System page describes the mechanism directly: the AI works against legally validated requirements rather than free prompts, what counts as correct is defined by legal experts rather than the algorithm, and every requirement in a playbook carries its own quality score derived from test sets. Unusual-clause detection is described as catching clauses that fall outside expected patterns even where the playbook does not define them. The FAQ names four error types the vendor says occur most often, and identifies hallucination among them as particularly critical because it occurs unpredictably, which is a franker statement than most records on this axis carry. What is missing is a published accuracy figure an outsider can test: the quality score is a per-customer, in-product instrument rather than a measured result, the test sets are named as the mechanism but never described, and the 85 per cent figure quoted throughout is a speed claim rather than an accuracy one. Grounding to primary authority does not bite on a contract review product and is not counted either way.
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.
The control structure is published rather than asserted. What constrains the system is stated: it works against legally validated requirements and company playbooks, and what counts as correct is defined by legal experts rather than the model. The review surfaces are named and specific: an AI Quality Score visible per requirement in a dashboard, test sets in which the user reviews and corrects how the system understood a requirement, unusual-clause detection, and a full audit trail. The route back to human judgement is stated twice and in terms: a human is kept as the final checkpoint before any decision is made on an AI classification, and accountability stays with the organisation rather than the AI when agents draft, review or flag clauses. The misclassification path is documented end to end, from detection through correction in the test set to the system applying that correction to comparable cases. No numeric threshold at which an agent stops and hands back is published; the per-requirement quality score is the surface that does that work in this product's own idiom, and it is named here rather than treated as equivalent.
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.
Real deployment evidence with substance, short of verified measurement. Two customers are named with dedicated case study pages, dormakaba and TUEV NORD, and seven more appear as logos: Uniklinik, Emmi, Fiege, Oechsler, Framatome, Zuercher Kantonalbank and Arabelle Solutions. Figures are published and specific, including a DPA first review falling from 45 to 60 minutes to under 10, contract review up to 85 per cent faster, playbook creation effort down up to 98 per cent, and cost reductions above 90 per cent on portfolio-wide risk analysis. Testimonials carry personal names, including Kim Weiler, Dr Marc Hansmann, Cedric Ruepp, Gordian Berger and Juerg Sommer. Two things hold this at B rather than A. The named individuals carry no organisation on the pages read, so a reader cannot tie a quoted figure to a named customer. And the two case studies were not opened in this pass, so they are credited for existing and named as unread rather than counted for their contents, which would be crediting a document by its title.
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.
Confidentiality is asserted in general terms across marketing surfaces and is not supported by any readable commitment about contract content. The home page and pricing page state no data sharing with third parties, GDPR compliance, ISO 27001 certification and hosting in Switzerland and Europe, and the pricing page uses the narrower phrase no uncontrolled data sharing. Behind those claims, the only published data document is a privacy policy last updated 6 November 2019, which addresses website and account data and never addresses uploaded contracts, prompts or outputs at all. Nothing published addresses training on contract content except the pricing matrix line offering opt-out of model training, which is available only on the Team and Enterprise plans. Nothing addresses segregation between customers or between matters, nothing states a retention or deletion position for contract content, no model provider is identified, and privilege, professional secrecy and work product are not mentioned on any surface. Searched the home page, AI Quality System page, pricing page, privacy policy and legal notice on 4 September 2026.
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 position is published on tooling versus advice, and it sits in FAQ prose rather than in any agreement. Asked who is liable if the AI makes a mistake, the vendor answers that when a lawyer sends a signed document it makes no difference how it was created, that they remain liable, that the AI is an assistive tool, and that legal responsibility stays with the person who approves the result. A companion answer states that accountability stays with the organisation rather than the AI. That is a genuine advice-line position. Two limbs are open. No jurisdiction limit is stated anywhere despite the product being sold across every European language and legal system. And the product actively invites non-lawyers to work in it, with procurement and sales teams reviewing contracts independently in line with legal standards and a dedicated FAQ confirming it, which is the professional-responsibility surface that most needs a published scope-of-use statement and does not have one.
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 governance framework with real substance. The AI Quality System is set out as three named layers with a described mechanism for each: playbooks and Legal Best Practices with Agent Memory as the knowledge base, AI Quality Scores with feedback loops and targeted user tuning, and detection of clauses falling outside expected patterns. It is supported by three published deep-dive articles on auditable AI, explainable AI, and governing agentic legal AI, and the vendor draws a distinction most do not, that explainable AI shows how a decision was reached while auditable AI verifies whether the output meets a defined standard. What is absent is what separates this band from the top: nobody inside Legartis is named as accountable for AI governance, no pre-release testing regime is described, no testing results are published, and nothing at all is published about uneven output across matter types or populations despite bias appearing in a section heading. The ISO 27001 certification is a security management 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.
The governing document is a privacy policy last updated 6 November 2019, on a product now sold as agentic AI, and it covers website and account data without ever addressing what happens to uploaded contracts, prompts or generated output after processing. That is this band in its own words. No retention period is stated for contract content; the retention section speaks generally and states that aggregated, anonymised or pseudonymised information may be retained indefinitely. No deletion position is published. No incident or breach practice is published. Third-party data processors are named for Application users as Turicode, VSHN and LinuxFabrik, all Swiss infrastructure and operations suppliers, with no AI model provider among them. Access control appears only as paid features in the pricing matrix, with advanced role management, document-level permissions and audit logs reserved to Enterprise. Personal data is stated to be stored on servers in Zurich. Searched the home page, AI Quality System page, pricing page, privacy policy and legal notice on 4 September 2026.
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.
No customer agreement is published at all. The footer's legal section offers exactly two documents, a legal notice and a privacy policy, and neither is a contract for the service. The legal notice is a website disclaimer: it disclaims the accuracy of information on the website, excludes liability for losses caused by use of that information, and states that reliance is at the reader's sole risk. It governs the website rather than the Application, which is the distinction drawn where a website terms of use was held not to grade the platform. No indemnity, no liability cap, no warranty on the service or its output, and no insurance position was located. The only statement located about who bears the loss is an FAQ answer on the AI Quality System page saying the lawyer who signs remains liable and that accountability stays with the organisation, which is marketing prose allocating risk to the customer rather than a term a buyer can hold the vendor to. A buyer cannot read the allocation of loss before signing because there is nothing published to read. Searched the home page, AI Quality System page, pricing page, privacy policy, legal notice and site footer on 4 September 2026.
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.
Real integrations exist and are named, short of documented depth. The Word add-in is the substantive one and its prerequisite is stated: if the customer already runs Microsoft Office 2019 or Office 365, the Legartis Word app can be installed. An open REST API is published as allowing Legartis to run as a standalone web app combined with any contract management solution, and the pricing matrix lists API and MCP integrations on all paid tiers, with custom integrations reserved to Enterprise. What is missing is depth: no integrations page, no developer documentation and no description of what actually moves between systems or in which direction. Three further connections are listed but marked Coming soon, DocuSign e-signature, sign-in with Google and Microsoft, and approval workflows, and are not credited, since a capability a customer cannot use today is intent rather than evidence.
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 stated clearly and repeatedly and is the same on every tier: hosting in Switzerland and Europe on the product and pricing pages, and personal data stored on servers located in Zurich per the privacy policy. That publishes the region limb and clears the band below, where neither tenancy nor region is stated. What is not addressed is processing location as distinct from storage location, which matters more here than usual because no model provider is named anywhere, so where inference actually runs is unknown to a buyer. Tenancy is not addressed either: nothing states whether the platform is single or multi-tenant or how customers are separated, and the only related published detail is document-level permissions offered as an Enterprise feature. No deployment options or tiers vary the hosting arrangement.
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.
ISO 27001 is stated consistently rather than decoratively: it appears in the trust block on the home page, in the security section of the AI Quality System page, as a line item available on all four tiers in the pricing feature matrix, and as a certification badge in the site footer. That is more than an unsupported badge, which is what separates this from the band below. It stops short of the top on every accessible-evidence limb. No certifying body is named, no certificate number is published, no scope statement or statement of applicability is offered, no issue or expiry date appears, there is no trust centre or portal of any kind, and no route to obtain a report exists at any access tier. Applying the third-party verifiability test, a buyer cannot check the claim against the certifying body's register without contacting Legartis, so the loop does not close. No penetration testing is mentioned. Checked 4 September 2026.
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 vendor describes its own layer and never identifies what sits underneath it. Marketing distinguishes the agentic AI framework from generic language-model output and contrasts Legartis with ChatGPT, which tells a reader that third-party models are in use without naming one. No model is named, no model provider is named, and no notice of change to either is committed. The third-party data processors published for Application users, Turicode, VSHN and LinuxFabrik, are Swiss infrastructure and operations suppliers rather than model providers, and infrastructure never answers this axis. Where inference runs is not stated; hosting in Switzerland and Europe describes where the platform sits. The clearest evidence that third-party or self-hosted training occurs at all is indirect, in the pricing matrix line offering opt-out of model training on the two upper tiers.
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 most complete pricing disclosure in this pull. Four named plans are published with rates, units and volume entitlements: Free at one seat and two NDA reviews a month; Professional at CHF 250 or 250 euro per user per month, or CHF 2,500 or 2,500 euro per user per year excluding VAT, covering 120 contracts a year from one seat; Team at CHF 300 or 300 euro per user per month, or CHF 3,000 or 3,000 euro per user per year, covering 250 contracts a year from five seats; and Enterprise at custom pricing for 500 or more contracts a year from ten seats. A full feature matrix runs across all four tiers, and the FAQ restates the numbers in prose. Both a monthly and an annual rate are given for each paid tier, currencies are stated in both Swiss francs and euros, and VAT treatment is explicit. Free and Professional are purchasable self-serve without contacting anyone. What implementation adds is named as a set of add-ons rather than priced: additional reviews, seats, custom playbooks, custom dashboards, and Best Practice Playbooks for NDA, DPA, SaaS, purchase and commercial lease agreements are each listed On request.
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 described with substance and its outer edge is left open. The buyer is identified precisely and is not a law firm: legal departments together with the procurement and sales teams around them, each with a dedicated solutions page, plus a construction industry page. Contract type coverage is evidenced rather than claimed, with Best Practice Playbooks published for NDA, DPA, SaaS agreement, purchase agreement and commercial lease agreement, and all contract types available on paid tiers against NDA only on the free tier. Twelve industries are listed. Language coverage is stated per tier, German, English and French on Free and all European languages on paid plans. What is not stated is where the product stops: coverage is claimed for companies of any size and industry with no boundary given, law firms as a segment are neither claimed nor excluded, and government use is not addressed.
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 unless the customer turns it off.
The pricing feature matrix lists opt-out of model training as a product feature, and the security FAQ on the same page confirms it: Team and Enterprise plans offer opt-out of model training. The entitlement is tiered, so customers on the Free and Professional plans have no opt-out available to them. No agreement, policy or trust page states what the default is, what is trained on, or whose models are involved; the privacy policy last updated 6 November 2019 does not address contract content at all. The commitment located is a paid product setting rather than a published term.
Prompt and Output Retention
How long does the product keep what a lawyer typed, and can that be set to zero?
No located public material states how long prompts and outputs are retained.
No located public material states how long prompts, uploaded contracts or generated output are retained. The privacy policy, last updated 6 November 2019, addresses website and account data only; its retention section states generally that information is kept as long as necessary and that aggregated, anonymised or pseudonymised information may be retained indefinitely, but nothing in it applies to contract content. The pricing matrix lists a contract repository with storage and version control, marked Coming soon, without any retention period. Searched the home page, the AI Quality System page, the pricing page, the privacy policy and the legal notice on 4 September 2026; there is nothing to quote because the position is absent rather than adverse.
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.
The pricing matrix asserts advanced role management, described as team-based access control with document-level permissions, as an Enterprise-tier feature, and lists user management on paid tiers. No published material describes how any of it is enforced, and no surface addresses separation between customers or between matters. The marketing trust blocks state no data sharing with third parties and, on the pricing page, no uncontrolled data sharing, neither of which speaks to segregation inside the platform. Segregation is therefore asserted as a purchasable feature with no published detail behind it.
Third Party Request and Subpoena Notice
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
Published terms or policy address disclosure to authorities or in response to legal process, and no commitment or reservation regarding customer notice is located anywhere. The vendor has told the customer that data can leave and has said nothing about whether the customer hears of it.
The privacy policy states that without explicit consent Legartis will not disclose personal data to third parties other than its named processors, unless this is required by law. Disclosure under legal compulsion is therefore addressed directly. No commitment to notify the customer of such a request was located, and no discretion over notice is reserved either. Searched the privacy policy, the legal notice, the home page, the AI Quality System page and the pricing page on 4 September 2026; the legal notice separately states that data transmitted by users is treated as confidential and will not be forwarded to third parties, which addresses voluntary sharing rather than compelled disclosure.
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.
No located public material identifies the corpus behind the product's answers. The Legal Agent is described as performing legal research with references to legal sources and as being connected to relevant legal sources, but no database, publisher, jurisdiction or collection is named, and no licence or rights basis is stated. The knowledge the vendor does describe in detail is the customer's own: playbooks, Legal Best Practices and Agent Memory built from company guidelines and contract history. Searched the home page, the Legal Agent references on it, the AI Quality System page and the pricing page on 4 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 on any located surface addresses whether authority is checked for subsequent history. This is primarily a contract review and drafting product, so the question bites only through the Legal Agent, which is described as answering legal questions and researching with references to legal sources. No treatment signal, currency check or citator relationship is described anywhere, and no primary law source is named. Searched the home page, the AI Quality System page and the pricing page on 4 September 2026.
Refusal and Uncertainty Behaviour
What does the product do when the answer is not in the corpus?
The product exposes a confidence or grounding score without an explicit abstention path.
The AI Quality Score is a per-requirement reliability signal surfaced to the user in a dashboard, showing how well the system currently detects each requirement in a playbook, and the vendor states a buyer can see at any time where the AI stands. Unusual-clause detection separately flags clauses falling outside expected patterns even where the playbook does not define them. Neither is an abstention path: no located material describes the product declining to answer, marking an output as ungrounded, or stopping when it cannot support a conclusion. The vendor names hallucination as one of four error types it says occur most often and describes it as particularly critical because unpredictable, without describing a behaviour that follows from detecting one.
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 4 September 2026 on both the product name Legartis and the corporate name Legartis Technology AG. 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?
Public materials refer to professional responsibility in general terms without naming guidance.
Public materials refer to professional responsibility in general terms without naming any guidance. The AI Quality System FAQ addresses liability directly, stating that a lawyer sending a signed document remains liable however it was created, that the AI is an assistive tool, and that legal responsibility stays with the person who approves the result. No bar, chamber or regulator is named on any surface, no ethics opinion or professional code is cited, and no jurisdiction is identified despite the product being sold across European legal systems. Searched the home page, the AI Quality System page, the pricing page, the privacy policy and the legal notice 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?
Public materials claim time savings without addressing billing or disclosure.
Public materials claim time and cost savings without addressing billing. Published figures include contract review up to 85 per cent faster, playbook creation effort reduced by up to 98 per cent, a DPA first review falling from 45 to 60 minutes to under 10, and cost reductions above 90 per cent on portfolio-wide risk analysis. The return on investment FAQ goes further and names lower external law firm costs and avoided headcount growth as the direct return. 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 here is an in-house department rather than a firm billing a client, which is the usual direction this signal assumes.
Outside Counsel Guideline Readiness
Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?
No located public material supports a client side disclosure obligation.
A third-party processor list is published in the privacy policy and separates website visitors from Application users, naming Turicode, VSHN and LinuxFabrik for the latter. All three are Swiss infrastructure and operations suppliers and no AI model provider appears among them, so the list does not tell a client whose models see its content, and infrastructure alone does not satisfy this signal. The list also sits in a policy last updated 6 November 2019, so its currency cannot be established. No data processing agreement, consent pack or client-facing disclosure material was located at any access tier, and no subprocessor change notification is committed.
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.
Some elements of a record exist, short of a document-level export. A full audit trail is stated in the trust blocks on both the home page and the AI Quality System page, the vendor states that a complete audit trail documents every correction step, and that every classification is traceable via the quality score and the audit trail so misclassifications stand out. Review history is listed as part of AI contract review, and audit logs appear in the pricing matrix as an Enterprise-tier feature. No export of a per-document record is described, the model used for a given output is not disclosed to the customer anywhere, and no disclosure guidance or template for a court was located.