Harvey vs Qanooni: how they compare in 2026
Scale and footprint separate these two. Harvey is a platform for the largest firms and legal departments, used by more than 200,000 professionals at over 3,500 organizations in 85 countries, including more than 80 of the AmLaw 100. It runs agents for end to end legal work, Vault for bulk document analysis, Knowledge for legal, regulatory and tax research, and Spaces for work shared across organizations. It works in Word, Outlook and iManage and draws context from NetDocuments, SharePoint and LexisNexis. Qanooni is a younger product built around the matter for UK and Gulf firms. QMatters assembles the parties, facts and timeline from a matter's email and documents and sets live legal authorities beside them, and the work then happens in Word and Outlook through QCounsel, QDraft and QRedline. Its Actionstep integration suits smaller firms that already run their practice there. Harvey suits an organization that wants one platform across many offices, practice groups and clients. Qanooni suits a firm that wants its matters, precedents and the cited law of the UK, the EU and the Gulf brought into Word without a new system to learn.
At a glance
All 15 axes, side by side
The same grid applied to every vendor in the index, graded from public sources. Hover a grade to see what the letter means on that axis.
AI Centrality
How much of the product is actually AI. Whether the machine learning is the mechanism the buyer is paying for or a feature layered onto conventional software, and whether the vendor is specific about which is which.
Agents, Vault review tables, Knowledge research, Contract Intelligence review, Intake triage and Horizon Scanning all produce their output with language models. No document management or workflow system sits underneath that a firm would buy on its own. Vault stores matter documents, and its purpose is extraction, comparison and reporting across them.
Every module is model work. QMatters reads the documents, emails and files on a matter and builds a graph of its parties, facts and timeline with no manual entry, then keeps it current as new material arrives. QCounsel turns a plain English request into a plan of steps and runs it across the whole file, producing chronologies, a two page brief from a 300 page bundle, party maps and tables of dates and obligations. QDraft writes agreements, notices and client emails in the firm's tone from its precedents. QRedline reviews counterparty paper against the firm's playbook in track changes. Retrieval from more than 5,000 legal authority sources sits under all four. The product keeps no conventional workflow layer of its own. Matter records, billing and documents stay in the firm's existing systems, such as Actionstep and Microsoft 365.
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.
In the February 2025 Vals Legal AI Report, a third party benchmark set against a lawyer baseline, Harvey Assistant was tested on six tasks. Its results ranged from 65.0 to 94.8 percent, and it beat the lawyer baseline on five. Document question answering reached 94.8 percent, 24.7 points above the baseline, with responses under a minute. Answers on scanned and badly formatted court transcripts reached 77.8 percent, 24.1 points above it. That study measured task accuracy rather than citation validity, and Harvey did not enter the later Vals study of citation authority. BigLaw Bench, Harvey's own benchmark, publishes its task categories and judging criteria on a public repository, with hallucination and source results by model. It defines a hallucination as a factual claim that a source of truth can disprove and tracks reasoning errors apart. Harvey reports that its systems hallucinate less often than the foundation models on legal tasks while giving longer answers. Every agent claim links to the source passage behind it, and the full BigLaw Bench dataset is available on request.
Answers are built by retrieval rather than from the model's memory. Qanooni pulls statutes, cases and regulations from more than 5,000 legal authority sources at the moment of the request, attaches a citation to each line, and a click opens the original. The sources sit in a legal data graph hosted in Azure that maps how laws amend one another, which cases interpret a provision and how earlier versions changed. Official databases feed it, among them the UK's legislation service, the EU's official law database, the UAE Ministry of Justice and the Saudi Bureau of Experts. Matter answers cite the document on the file they came from. Qanooni states that the product cannot invent case law, and no measured accuracy rate, test set or failure analysis is published beside that statement. The source count stood at 1,000 in October 2025 and is given as more than 5,000 today.
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.
Agents show their plan before they run, so a lawyer can adjust the scope and approve the work before Harvey begins. While an agent works, Harvey brings the lawyer back in when a judgment call is needed, logs every step and cites a source for every claim. Intake applies routing rules the legal team defines to send each request to an approved agent, to Contract Intelligence or to a lawyer. Reports and reviews can run on a schedule, and admins govern access through roles and workspace permissions. The point at which an agent stops on its own, and what Harvey commits to when an agent's work is wrong, are not stated.
Lawyers stay in the loop at set points. QRedline proposes its markup as track changes in Word, so each edit is accepted or rejected by the lawyer, and QDraft returns a first draft rather than a sent document. QCounsel plans and runs multistep work end to end, then hands back the chronology, table or analysis with every point cited to the file or the law. Qanooni's position is that nothing goes to a client without a lawyer's sign off. In its UAE case study the product flags risk, and the lawyers verify compliance, interpret what the risk means and advise the client. On Actionstep, each draft, review and change is logged to the matter. Which QCounsel steps run without approval, the point at which the product stops and hands back, and what happens after a step goes wrong are not described.
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.
Customer stories name the firm and give figures. Reed Smith, with about 1,800 lawyers in 34 offices, reports 700 Harvey users a day, 1,400 a month and AI certification for every associate. Repsol's legal division started a pilot in January 2024 with 50 lawyers in 12 jurisdictions and reports cutting the time on one process by more than 90%. CMS reports 95% adoption. Other named customers include A&O Shearman, Gleiss Lutz, Cuatrecasas, Macfarlanes, KKR, PwC and Deutsche Telekom. The figures are usage counts and time savings as each customer reports them, with no stated method for how they were measured.
Inspired Thinking Group, a UK marketing and content technology company, piloted Qanooni with its in house commercial legal team, and the results were published in January 2026. Comparable review tasks were timed against the team's earlier baselines using its standard time keeping. Review time fell by 60%, and personal productivity rose 21%. The team expects 25 to 30% once SharePoint and OneDrive files connect, a projection rather than a measurement. Inspire Legal Group became the first UK firm to run Qanooni inside Actionstep, and partners or founders at Legal Circle, Lecote and Primecase are quoted by name. Qanooni puts its base at more than 150 law firms across 11 countries. A UAE case study with the firm unnamed describes more than 200 contracts reviewed in seven days instead of two weeks, and figures on the Actionstep page carry no unit or customer.
Privilege and Confidentiality Posture
How client confidences are handled: attorney client privilege and work product treatment, segregation of one client matter from another, whether client data trains any model, and what the vendor commits to in writing rather than in marketing.
Neither Harvey nor its subprocessors may train any AI model on customer content or data, and model providers work under zero data retention. A firm can ask for a bespoke model trained on its own data and used only for that firm. Harvey syncs and enforces the firm's existing ethical wall policies and never creates, modifies or deletes walls, so the walls provider stays the system of record. Workspaces are logically separated, access follows roles, and data is deleted within 30 days of termination. If the law or a court compels disclosure, Harvey gives advance written notice where it is legally permitted. Attorney client privilege and work product are not addressed as such.
Client documents are referenced through retrieval at the moment of use and are never used to train a model, Qanooni's or any provider's. Each firm's data is logically isolated from every other firm and reachable only by that firm, behind role based access, single sign on and audit logging. The firm owns its matter graph as intellectual property and can export or permanently delete it at any time. Document contents stay in Qanooni's own Azure environment, with no third party document repository added. These commitments are made on Qanooni's website and in its articles. The user agreement that governs the product is not published, and nothing addresses privilege, work product or what the model provider keeps.
UPL and Professional Responsibility Posture
Whether the vendor is clear that it supplies a tool rather than legal advice, who its audience is, and how it addresses unauthorized practice of law, competence and supervision duties, and jurisdiction limits. ABA Formal Opinion 512 is the reference point. Where the advice line is not the duty a product raises, the axis is read through the nearest professional duty it does raise: judicial conduct rules and the reviewing duty for products sold only to courts, and the duty to bill for time actually spent for products that draft time entries.
Output is not legal advice and may contain errors, misstatements or gaps, and the Platform Agreement calls the service a research tool. Harvey sells to lawyers, legal departments and professional services firms, and its agent pages leave the judgment on every task with the lawyer. Access credentials belong to one named user and may not be shared. Nothing addresses competence and supervision duties under professional rules, or the jurisdictions where the product may be used.
Sold to law firms and in house legal teams, the product is framed two ways in its own material. The Actionstep page calls it the legal AI that does the practice of law, covering research, review and drafting. Elsewhere the line runs the other way. Lawyers verify compliance, interpret exposure and advise clients while the product flags risk, and nothing goes out without a lawyer's sign off. Articles on UK practice tie its use to the SRA duties of confidentiality, competence and supervision. The published terms cover the website only. The user agreement for the product is not public, so no advice disclaimer, user restriction or jurisdiction limit appears in writing.
AI Governance and Bias Disclosure
Published governance over model behavior: who owns it inside the vendor, what is tested before release, and what is disclosed about disparate output across matter types, parties, or populations.
ISO/IEC 42001:2023 certification covers Harvey's AI management system, and the Statement of Applicability published with it sets out the controls in scope. Its AIUC-1 certification, an AI security and safety standard, was conducted by Schellman and, in Harvey's account, validates its adversarial testing and AI security program. The trust center adds IRAP attestation, an EU AI Act item and AI Governance, AI Monitoring and AI Overview documents, with an AI Acceptable Use Policy among its policies. An AI Policy dated 26 December 2025 commits to testing the accuracy, reliability and suitability of the AI in the service and to change management for continuing legal compliance. No accountable owner is named, and nothing is published about uneven output across matter types or populations.
Accuracy, auditability and alignment are the three principles Qanooni names for trust in legal AI, and grounding in cited law is presented as its main control on output. Client data is excluded from model training, and a change of model is designed to happen without moving a firm's data. No governance framework, release testing regime, accountable owner or analysis of how output varies across practice areas, jurisdictions or languages is published. Articles on UK regulation describe how the SRA, the ICO, the FCA and the CMA approach AI in law firms, and the Equality Act 2010 for algorithmic screening, as background for buyers rather than as Qanooni's own controls.
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.
Customers choose what to upload, set their own retention policies and can delete data at any time. Within 30 days of termination, Harvey deletes remaining customer data and content unless told otherwise, and the DPA extends return or deletion to every subprocessor. Access runs on role based controls, logical workspace separation, SAML SSO, audit logs and IP allow listing. The Subprocessor List, updated 21 September 2026, names each provider with its purpose and location, and subscribers receive at least 30 days' notice of an addition with a right to object. Under the Security Addendum, Harvey notifies the customer of a security incident without undue delay and within 48 hours. It then reports the incident's nature, the investigation and the mitigation, and keeps relevant logs for at least a year.
Data is encrypted in transit and at rest on Microsoft Azure, with role based access, single sign on, multifactor authentication and audit logging across the platform. Each firm's data is logically isolated, and the firm can export or permanently delete its matter graph whenever it chooses. The privacy policy lists the service providers that may process personal data, each with its purpose, hosting region and transfer safeguard. They are Stripe for payments, HubSpot for CRM, PostHog for product analytics, Microsoft for productivity and documents hosted in the UAE, and Langfuse in Germany for LLM monitoring. Personal data is kept for a reasonable time with no fixed period, and no retention period is given for documents, prompts or outputs. No incident or breach notice practice is published.
AI Liability and Recourse
What the vendor stands behind contractually when its output is wrong. Indemnities, caps, carve outs, insurance, and whether any of it is published or only reachable through a negotiated agreement.
The Platform Agreement, last updated 9 January 2026, sets out what Harvey stands behind. Section 8 indemnifies the customer against third party claims that the service infringes intellectual property. If a claim arises, Harvey may substitute the service, secure a license to continue, or terminate and refund prepaid fees. The indemnity excludes materials Harvey did not provide and output from input the customer knew was likely to infringe. Harvey warrants that the service conforms to its documentation, is delivered in a professional manner and complies with applicable law. It also commits to carry industry standard insurance with insurers rated A- or better by A.M. Best. Total liability is capped at the greater of 12 months of fees or $250,000. Payment, indemnity and claims the law will not let a contract limit, such as gross negligence, sit outside that cap. Data breach and confidentiality claims carry a separate cap of twice 12 months of fees or $500,000. After a security incident, the Security Addendum commits Harvey to an independent forensic investigation at its own cost. The agreement states that output is AI generated and may contain errors.
The only published terms are the website terms effective 5 August 2025, under UAE law with the Dubai courts as forum. They provide the website as is, exclude Qanooni's liability for the website and its content, and have visitors indemnify Qanooni. Use of the product itself falls under a separate user agreement that is not published. Caps, indemnities, warranties and recourse for wrong output therefore cannot be read before signing.
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.
Word, Outlook, Teams and SharePoint all run Harvey inside them, and Vault syncs documents from iManage, SharePoint and Google Drive. The iManage connection is a direct OAuth integration with an embedded web extension, and NetDocuments access follows the firm's existing permissions. Intake takes requests from email, Jira, Slack, ServiceNow, iManage, Google Drive and SharePoint and sends updates back to the source channel. Command Center syncs employee profiles through SCIM. Aderant and Ansarada integrations are documented in the trust center, and customers can build their own integrations, including through an MCP connector library. LexisNexis content reaches research through Ask LexisNexis.
Installed from Microsoft AppSource as a ribbon tab in Word, the product also works in Outlook and Teams, so drafting, review and research happen in the documents and email the firm already uses. The Actionstep integration goes deepest. When a lawyer starts drafting in Word or Outlook, Qanooni pulls the matter details, client information, deadlines and related documents from Actionstep. Finished work saves back to the matter with version control, audit logs and matter linking. It switches on inside an existing Actionstep with no data migration. A Docusign partnership announced in April 2026 connects drafting and review to signature and agreement management. Document management systems are supported without being named, and the SharePoint and OneDrive file connection was still described as coming in January 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.
Microsoft Azure hosts Harvey's cloud environment, with each customer's data logically separated and access set by role. Customers can keep data in region in the EU or Switzerland, the United States or Australia. Customers with localization needs can also have processing in the EU and Switzerland or in Australia, and that commitment extends to Harvey's subprocessors. The Subprocessor List gives each model provider's processing locations. Where Anthropic or Mistral models are not offered in a chosen region, Harvey reaches them through hosting platforms such as AWS Bedrock and Google Vertex. What changes between plans or tiers is not stated.
Microsoft Azure hosts the platform as cloud software, with each firm's data logically isolated from other firms. Document contents stay in Qanooni's own Azure environment while the lawyer works in the firm's Microsoft 365 tenant. For UK firms Qanooni describes data held in Microsoft's UK and EU data centers. For UAE and wider GCC work it states that local data is stored and processed in Microsoft's UAE data centers to meet DIFC and ADGM rules. The privacy policy allows personal data to be stored in the United States and the UAE. No private cloud or on premises option, tier difference or separate processing location for the language model is described.
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.
Schellman audits Harvey for SOC 2 Type II and ISO 27001 every year, and the 2026 audit and certification renewal are complete. The trust center also lists ISO 27701, ISO/IEC 42001, AIUC-1, IRAP, TX-RAMP, GDPR, CCPA and an EU AI Act item. It publishes Statements of Applicability for ISO 27001, 27701 and 42001. Schellman, NCC Group and Bishop Fox perform external audits, and third party penetration tests run every year. Reports, the CAIQ v4.0.3, SIG Core and SIG Lite questionnaires and the data flow and network diagrams are released through a self serve access request, with bulk download.
ISO/IEC 27001:2022 certification and a SOC 2 Type II attestation cover the operating environment for the platform, which runs on Azure infrastructure that carries its own certifications. The auditor, the report period and the controls in scope are not published. Security documentation is sent on request through the demo and contact route, and there is no trust center or self serve portal. Personal data falls under the DIFC Data Protection Law of 2020, with complaints going to the DIFC Commissioner of Data Protection, and the company states GDPR compliance.
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 Subprocessor List names ten AI providers with their processing locations, among them Microsoft, OpenAI, Google Cloud, Amazon Web Services, Anthropic and Mistral. ElevenLabs supplies voice services, DeepL machine translation, and Baseten and Fireworks.ai further model hosting. Claude and Gemini models run through Amazon Bedrock and Google Vertex AI, as Harvey's subprocessor FAQ explains. Model providers work under zero data retention, with no human review and no training on customer data. Under the DPA, customers who subscribe to the list receive notice at least 30 days before a new subprocessor is added and may object. Which model serves which feature is not stated.
The platform is model agnostic. The model underneath can be swapped without moving a firm's data, since the firm's precedents, voice and accumulated judgment live in its matter graph rather than in a trained model. Neither the model in production nor its provider is named. Hosting on Microsoft Azure is stated, and the privacy policy lists Langfuse, based in Germany, for LLM observability and monitoring. No commitment to tell customers when the model changes is published.
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.
Fees are set in each customer's order form and invoiced under the Platform Agreement. If an order form is terminated early under the agreement, Harvey refunds a pro rata share of prepaid unused fees. Undisputed late amounts carry a finance charge at the Federal Funds Rate plus 1.5% a year. No rate, plan, tier or unit of charge appears on Harvey's site, and buying starts with a contact sales form.
No price, plan, unit of charge or contract term is published. Every route leads to a 30 minute demo, and the Actionstep page sends firms to a phone number or their Actionstep representative. An ROI calculator estimates the hours and value a team could recover from its own rates and weekly hours, in pounds, dollars, euros or dirhams, and asks for contact details before it shows the report. It says nothing about what Qanooni costs.
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.
Large law firms, mid sized firms, in house legal departments and professional services firms are the stated buyers. Industry pages cover healthcare and life sciences, technology, energy and utilities, and media, entertainment and telecom. More than 200,000 lawyers at over 3,500 organizations in more than 85 countries use Harvey, including 80% of Am Law 100 firms and five of the Fortune 10. Solutions pages address litigation, transactional work and innovation teams, and research spans legal, regulatory and tax questions across jurisdictions. Firm sizes or practice areas the product is not built for are not stated.
Law firms are the main buyer, from boutiques to full service practices, with more than 150 using the product across 11 countries. In house teams such as Inspired Thinking Group's commercial legal team use it too. Jurisdictions are named. The legal data graph covers the UK, the EU, the UAE, Saudi Arabia, Qatar and other GCC states, with Arabic and English drafting for UAE contracts and checks against UAE Labour Law and DIFC and ADGM rules. Published work spans commercial contracts, M&A due diligence, employment contracts under UK law, conveyancing and litigation chronologies. The ROI calculator lists practice settings from corporate and litigation to family, immigration, criminal and private client work. Practice areas or jurisdictions the product does not support are not stated.
The 12 legal signals, side by side
Recorded rather than graded. These are the questions a practitioner has to answer before a tool touches a client matter, and the answers are taken from public material only.
Client Data in Training
Can material a lawyer puts into this product be used to train a model?
Under the Platform Agreement, Harvey will not train any AI model on customer content or customer data, and its subprocessors will not either. The term covers both uploaded documents, which Harvey calls customer data, and the prompts and answers it calls customer content. A firm that asks for it can have a bespoke model trained on its own data and used only for that firm. Harvey may use usage data, such as feature and session statistics, to develop and improve the service, and usage data excludes customer data and content.
A firm's documents are referenced through retrieval when a lawyer asks and are never used to train a model, Qanooni's own or any provider's. The same commitment appears on its security, home and Actionstep pages, and the firm's matter graph stays its own intellectual property. Because the model sits outside the firm's data, a change of model leaves the firm's knowledge where it is. No customer agreement is published, so no matching contract term can be read.
Prompt and Output Retention
How long does the product keep what a lawyer typed, and can that be set to zero?
Customers decide what to upload, how long it is kept and whether it can be shared inside the organization, and they can delete data at any time. No default retention period is published. Model providers work under zero data retention, and subprocessors other than cloud storage providers may not retain or log content for human review. After termination, Harvey deletes remaining customer data and content within 30 days unless the customer instructs otherwise.
A firm can export or permanently delete its matter graph and documents whenever it chooses, and work saved through Actionstep stays on the matter with its version history. Personal data is kept for a reasonable length of time with no period given, and Langfuse monitors LLM activity from Germany. No retention window is stated for prompts, outputs or the logs of model calls, and no zero retention setting is described.
Ethical Walls and Matter Segregation
Does retrieval respect the firm’s ethical walls, or can the model read across them?
NetDocuments permissions carry through, so a user sees only the cabinets, matters, folders and files they can already open, and Harvey does not change those permissions. The iManage connection is a direct OAuth integration that respects iManage permissions and ethical walls. Harvey also syncs the firm's own ethical walls provider and blocks walled users from reaching or sharing restricted content.
Each firm's matters, precedents and knowledge are logically isolated and reachable only by that firm, and nothing is pooled across firms. Inside the firm, role based access, single sign on and audit logging control who sees which matter, and the matter graph organizes every document and email by the matter it belongs to. How matter permissions are set, and whether they follow the access rules in the firm's document management system or in Actionstep, is not described.
Third Party Request and Subpoena Notice
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
If law or a court order compels Harvey to disclose a customer's confidential information, the Platform Agreement commits it to advance written notice where legally permitted and to help seek confidential treatment. The DPA makes the same commitment for law enforcement requests for personal data. Where the law forbids notice, Harvey seeks a waiver and tells the customer once the prohibition ends. Its Law Enforcement Requests policy sends agencies to the customer first, challenges requests its lawyers consider unlawful and answers foreign requests only through channels such as a Mutual Legal Assistance Treaty. No transparency report is published.
Under its privacy policy, Qanooni may have to share information with public authorities or law enforcement, for example under a court order, after satisfying itself that a lawful basis exists and documenting the decision. It makes no commitment to tell the firm about a request or to resist one, and no transparency report is published. Product terms that might add a notice duty are not public.
Primary Law Corpus Provenance
Where does the law in this product come from, and does the vendor have the right to use it?
Knowledge connects questions to legal databases, curated public sources and Harvey's data partners, more than 500 legal sources across jurisdictions. The Subprocessor List names RELX, doing business as LexisNexis, for Ask LexisNexis, and Parallel Web Systems and you.com for web browsing and knowledge sources. Harvey's AI Policy commits it to obtaining the rights and licenses its data sets require. No source list by jurisdiction, license basis per source or update schedule is published.
The legal data graph connects statutes, case law, regulations, circulars and gazettes for the UK, the EU, the UAE, Saudi Arabia, Qatar and other jurisdictions. Named sources include the UK's legislation service, the EU's official law database, the UAE Ministry of Justice and the Saudi Bureau of Experts, and connections are described as permissioned, timestamped and refreshed routinely. The rights basis for each source and a fixed update schedule are not given.
Good Law Verification
Does the product tell you when the authority it just cited has been overruled?
Knowledge answers from more than 500 legal sources and draws LexisNexis content through Ask LexisNexis. Harvey does not describe a treatment signal or a later history check on the authorities it returns.
Each line of an answer cites the statute, case or regulation it rests on, and the legal data graph maps how laws amend one another, which cases interpret a provision and how versions have changed over time. Sources are read live at the time of the request, so a statute appears in its current form rather than as a training snapshot. No flag on a cited case that has been overruled, reversed or distinguished is described.
Refusal and Uncertainty Behavior
What does the product do when the answer is not in the corpus?
BigLaw Bench publishes hallucination rates and explains how Harvey defines and detects hallucinated claims, and agents cite a source for every claim. No setting or behavior is described for declining to answer when Harvey cannot ground a response.
Answers come only from retrieved sources. Where no authority supports a point, the product says so and leaves the claim out rather than inventing support, and Qanooni invites firms to test this in a demo on their own matters. No published evaluation shows how often it declines to answer.
Fabricated Citation Record
Does a public court record exist addressing fabricated or hallucinated legal citations in output from this product?
The AI Hallucination Cases database, maintained by Damien Charlotin, records court decisions worldwide that address hallucinated AI content and names the tool involved where known. It lists one matter naming Harvey, Hill v. Foundation Media LLC (S.D.N.Y., No. 25-cv-5947). On 22 September 2026 the court directed defense counsel to say whether AI was used on a brief with two questioned quotations and a citation, and a week later it took no further action.
Harvey is named only in counsel's own letter to the court, which says the brief was prepared with Harvey. No order makes any finding about Harvey or its output. A Galicia High Court order of 7 July 2026 lists Harvey AI among verified legal AI tools while setting a €1,800 fine, again with no finding about the product. Harvey's agreement states that output is AI generated and may contain errors.
The AI Hallucination Cases database maintained by Damien Charlotin, which records court decisions worldwide that address hallucinated AI content and the tool involved where known, has no entry naming Qanooni. Every answer the product gives carries a citation that opens the source behind it.
Bar Guidance Alignment
Has the vendor engaged in public with the ethics opinions its buyers are bound by?
Harvey's terms call the service a research tool whose output is not legal advice, and the agent pages leave the judgment on each task with the lawyer. No named ethics opinion appears, such as ABA Formal Opinion 512 or a state bar opinion.
Articles for UK firms tie AI use to UK GDPR and to the SRA's duties on confidentiality, competence and supervision. They also summarize how the SRA, the Law Society of England and Wales and the Law Society of Scotland approach AI, and a pilot plan template for UK firms sets out governance controls and roles. UAE material covers DIFC and ADGM data rules. No specific ethics opinion or practice note is discussed, and no mapping of the product to guidance in either market is published.
Billing and Fee Posture
Does the vendor address what happens to the bill when the work takes an hour instead of six?
ROI calculators for law firms and in house teams sit on Harvey's site, and customer stories report time saved, such as Repsol's. Command Center reports adoption by user, practice group and role. Nothing records AI assisted work per matter for billing, or addresses how a firm bills for that work or discloses it to clients.
On Actionstep, every draft, review and change Qanooni makes is logged back to the matter with the cited authorities behind it, a per matter record of AI assisted work. Elsewhere the platform keeps an audit log. Qanooni claims drafting 50% faster, six to eight hours saved per lawyer each week and fewer non billable hours, and offers an ROI calculator. It publishes no guidance on billing or disclosing AI assisted work to clients.
Outside Counsel Guideline Readiness
Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?
The trust center offers a Data Processing Addendum, a Business Associate Addendum and a Data Subject Requests item. It adds the CAIQ v4.0.3, SIG Core and SIG Lite questionnaires, data flow and network diagrams, a HIPAA report and a Security Welcome Packet. Sensitive items are released through a self serve request with bulk download. Statements of Applicability for ISO 27001, 27701 and 42001 show what each certification covers.
The public Subprocessor List names every provider with its purpose and location, and subscribers hear of additions 30 days ahead.
The privacy policy lists five service providers with their purpose, hosting region and transfer safeguard. They are Stripe, HubSpot, PostHog, Microsoft and Langfuse, and copies of the standard contractual clauses are offered by email. No model provider is named. Security documentation and certification detail are sent on request, and no client facing disclosure pack is published.
Court Disclosure Support
If a judge’s standing order requires an AI disclosure, can the product produce one?
Audit logs are a standard enterprise control, agents log every step, and every claim links to the source passage behind it. Command Center reports usage by user and feature. No export brings together the model used, the sources retrieved and the human review for one document.
Every line of output cites its source, and on Actionstep each draft, review and change is logged to the matter with the authorities behind it. QRedline's edits arrive as track changes, so the document itself shows what the product proposed and what the lawyer accepted. The platform keeps audit logs of access. No export ties a document to the model used, the sources retrieved and the lawyer who verified it, and no court disclosure template is published.
The questions both sides leave open
Derived from the records above rather than written, so it cannot favor either vendor. Take these into both conversations and ask each side the same question.
- Commercial Transparency
- Good Law Verification
Which one fits
Choose Harvey if
- You run a large firm or legal department across many offices. Harvey reports use at more than 80 of the AmLaw 100 and in over 85 countries, and Command Center benchmarks usage across teams, practice groups and offices.
- Your documents live in iManage, NetDocuments or SharePoint. Harvey works inside iManage, Word and Outlook and pulls context from those systems, Google Drive and LexisNexis, with more than 500 regional knowledge sources.
- Data residency and certification drive the decision. Harvey keeps data in region in the EU or Switzerland, the United States or Australia, enforces a firm's existing ethical wall policies, and holds ISO 42001 beside SOC 2 Type II and ISO 27001.
Choose Qanooni if
- You want the matter itself to be the context. QMatters builds the parties, facts and timeline from the matter's email and documents and keeps them current, so each task starts with the full file.
- Your firm runs on Actionstep. Qanooni pulls matter details, deadlines and documents from Actionstep into Word and Outlook and saves finished work back to the matter with version control and an audit log.
- Your work runs under UK, EU or Gulf law. The legal data graph covers the UK, the EU, the UAE, Saudi Arabia and Qatar, with Arabic and English drafting for UAE contracts and a citation on every line.
In summary
Harvey
Harvey builds AI for law firms, legal departments and professional service firms. Its agents carry legal work through to a result, Vault stores and analyzes large document sets, and Knowledge researches legal, regulatory and tax questions. Spaces handles work with other organizations, and Command Center tracks usage. According to the AI Legal Index, Harvey states that its Platform Agreement bars training underlying models on inputs, outputs or uploaded documents. Customers can keep data in the EU or Switzerland, the United States or Australia, and Harvey holds SOC 2 Type II, ISO 27001 and ISO 42001.
Qanooni
Qanooni, from Qanooni AI Ltd in Dubai's DIFC free zone, is a legal AI platform that works inside Microsoft Word, Outlook and Teams. QMatters builds a graph of each matter from its email and documents and overlays more than 5,000 live legal authorities, and QCounsel, QDraft and QRedline research, draft and review on that foundation. According to the AI Legal Index, Qanooni states that client data is never used to train a model, holds ISO 27001 and SOC 2 Type II, and publishes no price. More than 150 firms in 11 countries use it by its own count.
Questions buyers ask
Is Qanooni a smaller alternative to Harvey?
The two overlap on research, drafting and review, and Qanooni's own materials compare them. The difference is in shape. Harvey is a broad platform with agents, Vault, Knowledge and Spaces for large organizations. Qanooni organizes everything around the matter and works inside Word and Outlook, with an Actionstep integration aimed at smaller firms. From the AI Legal Index, based on each vendor's own published materials as of October 13, 2026. No vendor pays for placement.
How do Harvey and Qanooni ground answers in the law?
Harvey draws on more than 500 regional knowledge sources and lets firms ask LexisNexis from inside the platform. Qanooni retrieves from more than 5,000 legal authority sources mapped in a legal data graph and cites every line, and where no authority supports a point it says so rather than making the claim. From the AI Legal Index, based on each vendor's own published materials as of October 13, 2026. No vendor pays for placement.
Do Harvey or Qanooni train models on client data?
Harvey states that its Platform Agreement bars training underlying models on inputs, outputs or uploaded documents, and a firm can ask for a bespoke model trained only for itself. Qanooni states on its website that client content is never used to train a model, its own or any provider's, and its user agreement is not published. From the AI Legal Index, based on each vendor's own published materials as of October 13, 2026. No vendor pays for placement.
Where does each store a firm's data?
Harvey offers in region storage in the EU or Switzerland, the United States and Australia. Qanooni runs on Microsoft Azure, with UK and EU data centers for UK firms and Microsoft's UAE data centers for local data in the Gulf. From the AI Legal Index, based on each vendor's own published materials as of October 13, 2026. No vendor pays for placement.
Which of the two works inside Word?
Each does. Harvey runs in Word, Outlook, iManage, web browsers and a mobile app. Qanooni installs as a ribbon tab in Word, also works in Outlook and Teams, and brings matter context from Actionstep into those applications. From the AI Legal Index, based on each vendor's own published materials as of October 13, 2026. No vendor pays for placement.
Neither vendor paid for inclusion, placement or a grade, and neither reviewed this page before it published. Everything on it comes from public material on the dates shown. How the index grades.
Harvey announced a $550M raise in 2026 at a $15.5B valuation. Qanooni AI Ltd raised a $2M pre seed round in June 2025, and Qanooni's website answers how it compares with Harvey. Neither vendor reviewed this page.