Harvey vs Legora: how they compare in 2026
This is the most watched head to head in legal AI and the grid does not treat it as a close one. Harvey sits in the top two bands on twelve of fifteen axes, Legora on nine, and the gap is concentrated in exactly the place a buyer should care about: what each vendor is willing to publish. Legora's product story is genuinely distinctive, a shared workspace where the matter team and the AI work in the same place, and it publishes its contract documents openly rather than hiding behind a trust page, which is rarer than it should be. But on citation accuracy it publishes no measurement, no evaluation framework and no description of its retrieval method, while Harvey submitted to an outside evaluator. On oversight, Legora asserts the principle and does not describe the mechanism. Harvey is the better documented vendor. Legora may still be the better tool for how your team actually works.
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.
The models are the product. Assistant, Vault, Knowledge and Workflow Agents are all generative systems, and there is no underlying document or workflow system that would stand without them. Vendor material describes every module in model terms.
The models are the product. The workspace is AI native rather than a document system with a model attached, and every surface the vendor sells, review, drafting, research and workflows, is a generative capability. Remove the models and nothing remains to sell.
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.
CORRECTED 29 Aug 2026, second correction to this row. Previously graded B on two stated grounds, both of which are now resolved. Ground one was that BigLaw Bench is the vendor's own framework rather than independent evidence. That remains true of BigLaw Bench, but independent evidence also exists and was missed: Harvey Assistant participated in the February 2025 Vals Legal AI Report, a third party benchmark against a measured lawyer baseline, and was evaluated across six tasks scoring between 65.0 and 94.8 percent, surpassing the lawyer baseline on five of the six, with 94.8 percent on document question answering at 24.7 points above baseline and 77.8 percent on scanned and messily formatted court transcripts at 24.1 points above baseline, all at sub minute response times. Those figures sit on the evaluator's own site and are checkable without reference to any vendor claim. Ground two was that the citator and refusal limbs failed. That was a double count and is withdrawn: both are separately measured by their own signal rows on this record, and applying them again to the capability grade penalised the same absence twice. It was also inconsistent, since three legal research vendors on this index hold an A on this axis with both of those signals recorded as not addressed. The vendor's own disclosure is unchanged and remains substantial: BigLaw Bench with task categories and grading rubrics on a public repository, measured hallucination rates and source scores by model, a hallucination defined as a factual claim disprovable against a source of truth with reasoning errors tracked separately, and output linking to the specific document passages supporting each assertion. Two limits recorded rather than deducted for: the February 2025 study measured task accuracy rather than citation validity or hallucination rate specifically, and this vendor did not participate in the later Vals study that measured citation authoritativeness. The full BigLaw Bench dataset also sits behind a direct request rather than open publication.
Grounding is claimed in vendor material, which describes reliable and verifiable answers and cells linked to their source. Searched the vendor site, blog, newsroom and trust center on 29 Aug 2026 and located no published accuracy measurement, no evaluation framework, no hallucination rate and no description of the retrieval method. Third party directories describe a citation verification capability, which is not vendor material and does not move this axis.
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.
States in published material that the product is designed to assist lawyers rather than replace them and that it is built to make verification easy. Review surfaces are real and documented: inline links to source passages, role based permissions and conditionals in the workflow builder, and admin level workspace governance. Not located as of 29 Aug 2026: the threshold at which an agent stops and hands back to a lawyer, or what the vendor commits to when an agent is wrong.
Human oversight is asserted as a governing principle in vendor material and is covered in the abstract by an ISO 42001 certification of the AI management system. What is not published is the mechanism: where the review point sits, what an agentic workflow does on its own, at what threshold it stops, and what a supervising lawyer must approve. Searched the vendor site, blog and trust center on 29 Aug 2026. Oversight appears as a stated principle rather than a described control.
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 appear in vendor material with attributed quotes, including Blank Rome on the iManage integration and a published Burges Salmon selection story. Vendor states 700 plus customers across 58 plus countries. Not located as of 29 Aug 2026: dated outcome figures with a stated method a reader could assess, which is what separates this from an A.
Named customers appear in vendor material, including a published Grant Thornton UK forensic investigations story, and the vendor states more than 1,000 customers across 50 plus markets. Additional named users including Cleary Gottlieb, Goodwin, Linklaters, White and Case, Dentons and Barclays appear in vendor recruiting material. Not located as of 29 Aug 2026: dated outcome figures with a method a reader could assess, which is what separates this from an A.
Privilege and Confidentiality Posture
How client confidences are handled: attorney client privilege and work product treatment, segregation of one client matter from another, whether client data trains any model, and what the vendor commits to in writing rather than in marketing.
Substantive published commitments: no training on customer data by default, a contractual prohibition on model providers training, zero data retention enforced on model providers, logical workspace separation, role based access, ethical wall sync with the firm's own walls provider, and processing in the EU, Switzerland or Australia. Two gaps keep this off an A. The security page defines customer data as uploaded documents and customer content as queries and responses as separate contractual terms, so the no training commitment reads plainly on one and not on both. Attorney client privilege and work product handling is not addressed directly in located public material as of 29 Aug 2026.
Substantive published commitments, and unusually for this market they sit in openly published contract documents rather than only on a trust page: general terms and conditions in EU and US versions, a data processing agreement, and a security measures annex covering least privilege access, personnel confidentiality obligations, authorization controls and retention on customer instruction. The security page states the vendor will not use customer data to train or fine tune models. Two gaps hold this off an A. Attorney client privilege and work product handling is not addressed directly in located material, and matter level segregation between users is not documented.
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.
One sentence in a security blog post states the product is designed to assist lawyers rather than replace them. Checked the vendor site, security page, security addendum and help center on 29 Aug 2026 and did not locate a published position on the advice line, on competence and supervision duties, or on jurisdiction limits. The intended audience is unambiguously lawyers and legal departments, which is why this sits at C rather than lower.
The intended audience is unambiguously lawyers, firms and in house teams, and vendor material describes the product as working with lawyers rather than replacing them. Searched the vendor site, the published acceptable use policy, the general terms and the blog on 29 Aug 2026 and located no published position on the advice line, no treatment of competence and supervision duties, and no statement of jurisdiction limits.
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.
CORRECTED 29 Aug 2026, third correction to this record. Previously graded C on the finding that no AI specific governance regime was located and that the published testing was security testing rather than model behaviour testing. That was wrong, and it came from reading the vendor's marketing surfaces rather than opening its trust centre, where the governance material actually sits. What is published on the trust centre, publicly and without a request: ISO/IEC 42001:2023 certification, the international standard for AI management systems, accompanied by a published Statement of Applicability, which is the document identifying which controls apply and why and is therefore a published scope rather than a bare badge. Alongside it, AIUC-1 certification, an AI specific assurance standard, conducted by Schellman, which the vendor states is the first accredited AIUC-1 certification body, and which the vendor describes as validating adversarial testing and its AI security programme specifically. EU AI Act conformity is separately listed. The trust centre carries a dedicated AI section with AI Governance, AI Monitoring and AI Overview items, and an AI Acceptable Use Policy sits in the published policy set. ISO 27701 for privacy information management and an IRAP attestation are also held. Two independent AI specific certifications, one of them adversarially tested, with published statements of applicability and a named accredited certifier, is the strongest AI governance position on this index, ahead of the four other A grades on this axis, each of which rests on ISO 42001 alone or on a single certification plus a framework document. One gap remains and is recorded rather than waived: no disclosure was located about uneven output across matter types, parties or populations, so bias specifically is still unaddressed, and no named individual owner of model governance was located.
Holds an ISO 42001 certification covering its AI management system, independently audited with ongoing surveillance, and publishes what the certification covers: how AI is designed, deployed, supervised and monitored, with human oversight and structured governance named as the operating principles. That is a published governance framework with real substance and independent validation, which is rare in this market. Not located as of 29 Aug 2026: a named internal owner of AI governance, published pre release testing results for model behaviour, or any disclosure about uneven output across matter types, parties or populations.
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.
Publishes retention under customer control with documented vault retention triggers and deletion timelines, role based access control, logical workspace separation, encryption in transit and at rest, and a current named subprocessor list with an update FAQ. Not located as of 29 Aug 2026: a published incident and breach notification practice, which is the remaining element of the A bar.
The published security measures annex covers access on a least privilege and role based model, centrally stored logs traceable to unique usernames with security logs retained at least 12 months, data integrity signing, personnel background checks and confidentiality agreements, and retention set by customer instruction. The published data processing agreement commits the vendor to assist with the customer's own breach notification obligations, so incident practice is addressed. ISO 27001:2022 is audited yearly. Not located as of 29 Aug 2026: a current named subprocessor list, which is the remaining element of the A bar.
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.
Checked the vendor site, its published legal pages including the security addendum and the subprocessor FAQ, and the trust center on 29 Aug 2026. No published indemnity scope, liability cap, carve out, warranty or insurance position located. Commercial terms appear to be reached through a negotiated enterprise agreement rather than published.
A real published position, which is uncommon here. General terms and conditions are published openly in EU and US versions and carry numbered liability clauses, aggregate caps that apply across the subscriber and its affiliates, a separate cap of 100,000 Euro on beta features, and a carve out concept the terms call an Enhanced Claim. A buyer can read the allocation of loss before entering a sales process. Not located as of 29 Aug 2026: indemnity scope for third party claims arising from output, any warranty on output, and any insurance position, so the full picture is short of an A.
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.
Documented native integrations with iManage, NetDocuments, SharePoint and OneDrive, Google Drive, Box, Microsoft Word, Outlook, EDGAR and PitchBook, plus an MCP connector library. Help center articles describe what each integration moves, in which direction, what an admin must configure, and what a given integration does not support. The iManage connection is a direct OAuth integration with an embedded web extension rather than third party middleware.
Real and named integrations: an iManage technology partnership working through iManage APIs with an announced expansion, SharePoint, Box, a Microsoft Word add in for drafting and redlining, Outlook, EDGAR, and import from virtual data rooms and contract lifecycle systems. The vendor is explicit that it integrates with document management systems rather than replacing them. Not located as of 29 Aug 2026: implementer level documentation describing what each integration moves, in which direction, and what an administrator must configure, which is what the A bar asks for.
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.
States processing in the EU and Switzerland or Australia for customers with data localization requirements, and states that this applies to subprocessors as well. Tenancy is multi tenant with logical workspace separation and enforced role based access. Not located as of 29 Aug 2026: where data is stored as distinct from where it is processed, and what changes between tiers.
The claim is made and the detail is not published. Vendor material states flexible storage options matched to data sensitivity, and separate EU and US contract documents indicate region specific arrangements, with the technical team in Sweden operating under GDPR. Searched the vendor site, the security pages and the published legal documents on 29 Aug 2026 and located no list of available regions, no tenancy model, and no statement of where processing happens as distinct from where data is stored.
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.
SOC 2 Type II attestation and ISO 27001 certification with the auditor named as Schellman, renewed annually, and the 2026 cycle announced publicly. Penetration testing and red teaming partners are named as NCC Group and Bishop Fox. Certified under the EU US Data Privacy Framework. A live trust portal at trust.harvey.ai carries the current reports. Reports sit behind a portal request rather than an open download, which is a request flow rather than a sales call.
Three current independent certifications, ISO 27001:2022 audited yearly, SOC 2 Type II, and ISO 42001 for AI management, with a public trust center at security.legora.com carrying a resources section and a data flow diagram, plus security whitepapers and a security measures annex published openly with no gate at all. The open publication of the security annex is full credit rather than a request flow. The certifying auditor is not named in located material, which is the one thing a peer in this category does publish.
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.
Publishes a subprocessor list naming model and infrastructure providers including OpenAI, Anthropic, Google Cloud, AWS and Microsoft, alongside a subprocessor update FAQ and a security diagram showing model access through Bedrock and Vertex AI. States zero data retention and ephemeral processing at the model providers. Not located as of 29 Aug 2026: a published commitment to notify customers before the model supply chain changes, as distinct from an FAQ describing a change that has already happened.
Vendor material refers to how it implements, supervises and evolves AI without identifying what sits underneath. Searched the vendor site, the trust center, the published general terms, the data processing agreement and the security measures annex on 29 Aug 2026 and located no named model provider, no subprocessor list and no commitment to notify customers when the supply chain changes. Third party sources describe a multi model approach running on Microsoft Azure, which is not vendor material and does not move this axis.
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.
Checked the vendor home page, the platform and product pages, the help center and the trust center on 29 Aug 2026. No pricing page, no published rate, no stated unit of charge and no published tier structure located. Access to pricing runs through a demo request, which is sales gated and earns no credit. Third party per seat estimates exist in trade coverage but are not vendor published and do not move this axis.
Searched the vendor home page, product pages, newsroom and legal pages on 29 Aug 2026. No pricing page, no published rate, no stated unit of charge and no published tier structure located. The only commercial entry point is a demo request, which is sales gated and earns no credit. Several independent third party pricing analyses state the same, and one reports a consumption based tier that was not located on the vendor site. Third party per seat estimates are not vendor published and do not move this axis. Note that the vendor does publish its general terms openly, which is transparency of terms rather than of price and is graded on the liability axis instead.
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.
Describes its segments with substance: large law firms first, expanding into corporate legal departments and professional services, with 700 plus customers across 58 plus countries and practice coverage spanning litigation, transactional diligence, regulatory and tax. Not located as of 29 Aug 2026: a statement of the boundaries, meaning which firm sizes or practice areas the product is not built for, which is what the A bar asks for.
Segment coverage is described with substance: large law firms, in house legal departments, and professional services including a published forensic investigations customer story, spanning more than 1,000 customers across 50 plus markets with multi jurisdiction and cross border work as a stated strength. Practice coverage spans review and diligence, research, drafting and investigations. Not located as of 29 Aug 2026: any statement of the boundaries, meaning which firm sizes or practice areas the product is not built for.
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?
The vendor security page states that by default it never trains on customer data and that it contractually prohibits model providers from training on customer data. A subprocessor FAQ states customer data is never used to train models unless explicitly authorized by both the customer and the vendor. The same page defines customer data as uploaded documents and customer content as queries and responses as separate contractual terms. No matching term was located in a published agreement as of 29 Aug 2026.
The vendor home page and security page both state that customer data is not used to train or fine tune any AI models. The vendor publishes its general terms and conditions and its data processing agreement openly, and a training prohibition was searched for in those documents on 29 Aug 2026 and not located, so the commitment as recorded rests on the security and marketing pages rather than on a located contract term. The full agreement text was not read end to end.
Prompt and Output Retention
How long does the product keep what a lawyer typed, and can that be set to zero?
REGRADED 29 Aug 2026 after the value set was amended; previously recorded at disclosed without a period, which understated real customer control. The security page states that customers determine what data to upload, how long it is retained, and whether it can be shared internally, and help centre documentation covers configuring vault retention settings including triggers and deletion timelines. That is retention configured by the customer inside the product, which is the strongest form of the control this value describes. Recorded at customer controlled rather than the top value because no zero retention setting for the vendor's own storage was confirmed in public material as of 29 Aug 2026, and no default period is published, so a customer knows they can set the window without knowing what it is before they do. Zero data retention is stated separately as a requirement imposed on model providers, which is a different layer.
REGRADED 29 Aug 2026 after the value set was amended; previously recorded at disclosed without a period, following an earlier correction that established the customer control exists. Rechecked against the source document. Section 17 of the published security measures annex, dated 31 Jan 2025, states that during the term of the data processing agreement personal data is subject to the retention requirements the subscriber instructs from time to time, and that after termination or expiry clause 11 of that agreement governs. Retention is therefore customer instructed and the commitment sits in a contract document rather than a policy page, which is the contractual form of control this value describes and is enforceable in a way a policy page is not. Recorded at customer controlled rather than the top value because no retention period is published and no zero retention setting was located. Also confirmed on the same document and worth factoring in as a retention floor: subscriber environments are logically separated at all times, and full production backups are taken every four hours.
Ethical Walls and Matter Segregation
Does retrieval respect the firm’s ethical walls, or can the model read across them?
Help center documentation states the product follows existing NetDocuments permissions, that a user sees only the cabinets, matters, folders and files they can already access, and that the product does not expand or modify permissions. The iManage integration is documented as a direct OAuth connection that respects iManage permissions and ethical walls. Separate admin documentation covers connecting, syncing and monitoring the firm's own ethical walls provider.
Searched the vendor site, the iManage partnership announcement, the security page, the published security measures annex and the trust center on 29 Aug 2026. No vendor material was located addressing whether retrieval enforces document management system permissions at query time per user, or how ethical walls and matter level segregation are handled. The security annex documents least privilege access for vendor personnel, which is a different question. A partner case study describes per query authentication, which is not vendor material.
Third Party Request and Subpoena Notice
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
Checked the security page, the published security addendum and the subprocessor update FAQ on 29 Aug 2026. No located term or policy addresses government or law enforcement requests for customer data, and no transparency report was located.
Searched the published EU and US general terms and conditions, the data processing agreement, the security measures annex and the acceptable use policy on 29 Aug 2026. No clause addressing government or law enforcement requests for customer data was located, and no transparency report was located. This records a search that did not surface the clause rather than a reading of the full agreements end to end.
Primary Law Corpus Provenance
Where does the law in this product come from, and does the vendor have the right to use it?
The published subprocessor material identifies RELX and LexisNexis as a source provider behind an Ask LexisNexis feature, alongside web search providers, and product material refers to premium legal databases and curated public sources. The identification appears in the subprocessor list rather than a coverage page. No licence or rights basis, jurisdiction list or update cadence for the primary law corpus was located as of 29 Aug 2026.
Research coverage is described by jurisdiction, reported at twelve, and the vendor announced the acquisition of Qura, a Stockholm legal database covering case law, legislation and regulation, which it is extending to larger markets. What is not identified is the corpus itself: which publishers or public sources the law comes from, the licence or public domain basis for each, and the update lag. Searched the vendor site, newsroom and product pages on 29 Aug 2026.
Good Law Verification
Does the product tell you when the authority it just cited has been overruled?
Checked product pages for the research module, the help center and the subprocessor material on 29 Aug 2026. A LexisNexis sourced research feature is documented, but no public material was located addressing whether authority returned by the product carries a treatment signal or is checked for subsequent history.
Searched the vendor site, product pages, newsroom and blog on 29 Aug 2026. No vendor material was located addressing whether authority returned by the product carries a treatment signal, whether subsequent history is checked, or whether any commercial citator is licensed. A third party directory describes a citation verification capability, which is not vendor material and was not treated as evidence.
Refusal and Uncertainty Behaviour
What does the product do when the answer is not in the corpus?
The vendor publishes measured hallucination rates and describes how hallucinated claims are detected and scored. Checked that research material, the product pages and the help center on 29 Aug 2026 and did not locate published material describing an explicit no answer or abstention path when the product cannot ground an answer.
Searched the vendor site, blog, newsroom and trust center on 29 Aug 2026. No published material was located describing what the product does when it cannot ground an answer, whether an explicit no answer path exists, or whether any confidence or grounding signal is exposed to the user.
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 29 Aug 2026. Instrument searched: the AI Hallucination Cases database maintained by Damien Charlotin, which tracks court decisions worldwide involving AI generated hallucinated content and records the AI tool implicated where it is known. Also checked published sanctions summaries from Norton Rose Fulbright covering 2026 and two vendor maintained trackers. The entries located name filers, and in some rows other products, rather than this one. This is a statement about the public record on the date shown and not a clearance, and it is bounded by what that database covers.
No court order, opinion or disciplinary record naming this product has been located as of 29 Aug 2026. Instrument searched: the AI Hallucination Cases database maintained by Damien Charlotin, which tracks court decisions worldwide involving AI generated hallucinated content and records the AI tool implicated where it is known. Also checked published 2026 sanctions summaries and secondary sanctions trackers. The entries located name filers, and in some rows other products, rather than this one. This is a statement about the public record on the date shown and not a clearance, and it is bounded by what that database covers.
Bar Guidance Alignment
Has the vendor engaged in public with the ethics opinions its buyers are bound by?
Published material refers in general terms to aligning with the high standards expected of legal work and to designing the product so that verification is easy. Checked the blog, resource pages and help center on 29 Aug 2026 and did not locate engagement with any named ethics opinion, including ABA Formal Opinion 512 or state bar guidance.
Searched the vendor site, blog, newsroom and resource pages on 29 Aug 2026. No engagement with any named ethics opinion was located, including ABA Formal Opinion 512 and state or national bar guidance. The vendor publishes substantial governance and certification material, which addresses its own AI management system rather than the professional responsibility obligations its buyers are bound by.
Billing and Fee Posture
Does the vendor address what happens to the bill when the work takes an hour instead of six?
Vendor material offers impact and return on investment resources framed around what the product does for a firm or business, and the help center documents usage analytics dashboards and reporting APIs. Checked those surfaces on 29 Aug 2026 and did not locate a per matter record of AI assisted work intended for fee purposes, or any published guidance on billing, fee or client disclosure treatment.
Vendor material is framed around speed and volume, describing analysis of thousands of documents in minutes and teams moving faster. Searched the vendor site, blog and legal pages on 29 Aug 2026 and located no per matter record of AI assisted work intended for fee purposes, and no published guidance on billing, fee or client disclosure treatment.
Outside Counsel Guideline Readiness
Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?
UPDATED 29 Aug 2026 during the trust portal sweep; value unchanged, evidence enumerated. The trust centre was opened directly and its published inventory is the most complete outside counsel readiness pack on this index. Available without a request, as named items: a Data Processing Addendum, a Business Associate Addendum, a Data Subject Requests item, completed self assessment questionnaires in three standard formats being CAIQ v4.0.3, SIG Core and SIG Lite, a Data Flow Diagram, a Network Diagram, a HIPAA report, a report titled Security and Privacy of Customer Data, and a Security Welcome Packet. A Subprocessors section is published as a standing part of the trust centre. Sensitive documents sit behind a self serve access request with a bulk download option. Compliance items are listed individually and include statements of applicability for ISO 27001, 27701 and 42001, which tell a client's reviewer what each certification actually covers. A firm answering a client AI clause could assemble a complete response from this without a sales conversation. One limitation recorded honestly: the subprocessors list renders client side and its contents were not retrieved in this pass, so the section's existence is established rather than the identity of the subprocessors in it.
Read against the artifacts this signal turns on, the picture is mixed and the value understates one half of it. Openly published with no gate and forwardable to a client today: general terms and conditions in EU and US versions, a data processing agreement, a security measures annex and an acceptable use policy. Not located as of 29 Aug 2026: a current subprocessor list, any statement of which model providers see client content, and any client facing consent or notification pack. The trust center carries a resources section that routes document access through a request.
Court Disclosure Support
If a judge’s standing order requires an AI disclosure, can the product produce one?
Published material documents audit logs as a default enterprise control, inline links from assertions to the specific source passages behind them, and usage analytics available through a dashboard and APIs. Checked those surfaces on 29 Aug 2026 and did not locate a per document export covering model used, sources retrieved and human verification together.
Searched the vendor site, product pages and published legal documents on 29 Aug 2026. Partner material describes citations being preserved when work is exported to Word, and the security annex documents security logging traceable to unique usernames, which is an infrastructure control rather than a record of AI assisted work. No per document record covering model used, sources retrieved and human verification was located.
The questions both sides leave open
Derived from the records above rather than written, so it cannot favour either vendor. Take these into both conversations and ask each side the same question.
- Commercial Transparency
- Third Party Request and Subpoena Notice
- Good Law Verification
- Refusal and Uncertainty Behaviour
Which one fits
Choose Harvey if
- You need measured accuracy rather than asserted accuracy. Harvey participated in an independent benchmark run by an outside evaluator. Legora publishes no accuracy figure, no hallucination rate and no description of how retrieval works.
- Integration depth decides the purchase. Harvey documents its iManage, NetDocuments, SharePoint and Microsoft connections at implementer level. Legora has a real iManage partnership but does not publish that depth of detail.
- You want to know where the AI stops and the lawyer takes over. Harvey documents review surfaces, role based permissions and workflow conditionals. Legora covers oversight in the abstract through an ISO 42001 certification without describing the mechanism.
Choose Legora if
- Your matters run across jurisdictions and the working pattern matters more than the benchmark. Legora is built around a shared surface for the matter team and the AI, with Tabular Review linking every cell back to its source, and states multi jurisdiction work as a strength.
- You want the commercial terms in front of you before signing. Legora publishes general terms in EU and US versions, a data processing agreement and a security measures annex, which is more contractual disclosure than most of this market offers.
- You are buying in Europe and want a vendor whose data protection documentation is written for that starting point rather than adapted to it.
In summary
Harvey
Harvey is an enterprise legal AI platform for law firms, in house legal departments and professional services firms. The AI Legal Index grades it in the top two bands on twelve of fifteen capability axes, ahead of Legora at nine, with A grades on citation accuracy, AI centrality, integration depth, governance disclosure and security certifications. It participated in the independent 2025 Vals Legal AI Report, publishes contractual prohibitions on model provider training with enforced zero data retention, and documents its document management integrations at the level an administrator can act on. Its published gaps are liability and recourse, where nothing addresses what happens when an output is wrong, commercial transparency, where no pricing of any kind is published, and professional responsibility, where a single sentence in a blog post is the only located position.
Legora
Legora is a collaborative AI workspace for law firms and in house legal teams, built around a shared surface where the matter team and the AI work in the same place, with Tabular Review turning large document sets into structured review with each cell linked to its source. The AI Legal Index grades it in the top two bands on nine of fifteen capability axes. Its distinguishing strength is contractual openness: general terms in EU and US versions, a data processing agreement and a security measures annex are published rather than gated, alongside an ISO 42001 certification of its AI management system. It is held back by disclosure rather than capability: no published accuracy measurement, no described retrieval method and no described oversight mechanism were located as of 29 August 2026.
Questions buyers ask
Harvey vs Legora: which is better for a law firm?
On the AI Legal Index grid Harvey is the better documented vendor, sitting in the top two bands on twelve of fifteen axes against Legora's nine. The difference is concentrated in published evidence: Harvey submitted to an independent benchmark and documents its integrations and review surfaces in detail, while Legora publishes no accuracy measurement and describes oversight as a principle rather than a mechanism. Legora's collaborative working surface is genuinely distinctive and may still fit a team better.
Does Legora publish accuracy or hallucination rates?
No. As of 29 August 2026, checking the vendor site, blog, newsroom and trust centre, the AI Legal Index located no published accuracy measurement, no evaluation framework, no hallucination rate and no description of the retrieval method. Legora's material describes reliable and verifiable answers with cells linked to their source, which is a grounding claim rather than a measurement. Harvey by contrast participated in the February 2025 Vals Legal AI Report, run by an outside evaluator.
Which one integrates better with iManage?
Both have real iManage connections and Harvey documents its more thoroughly. Harvey's is a direct OAuth integration with an embedded web extension, with published articles describing what moves, in which direction and what an administrator must configure. Legora has an announced iManage technology partnership working through iManage APIs, plus SharePoint, Box, a Word add in, Outlook and EDGAR, and is explicit that it integrates with document management systems rather than replacing them.
What do Harvey and Legora cost?
Neither publishes a price. Both carry the lowest grade on commercial transparency in the AI Legal Index. Checking both properties on 29 August 2026 found no pricing page, no published rate, no stated unit of charge and no tier structure on either, with the only commercial entry point being a demo request on each. Independent pricing analyses exist for both but are not vendor published and do not change the grade.
What do Harvey and Legora both leave unpublished?
Both score lowest on commercial transparency, publishing no rate at all. Both sit at the same middling grade on professional responsibility, with no published position on the advice line, on competence and supervision duties, or on jurisdiction limits, despite selling squarely to lawyers. And neither states the boundary of what it is not built for, which is the limb that separates a good coverage disclosure from an excellent one.
Read the gap on this page as a disclosure gap, not a capability finding. Legora's lower grades on citation accuracy and oversight record what could not be located in public material on 29 August 2026 after checking the vendor site, blog, newsroom and trust centre. Third party directories describe a citation verification capability at Legora, which is not vendor material and therefore does not move the grade. If Legora publishes a measurement or a described control structure, this record will be corrected and redated rather than upgraded as a courtesy. Both vendors are direct competitors for the same large firm accounts, so treat customer counts on either side as vendor stated. Neither reviewed this page.
Neither vendor paid for inclusion, placement or a grade, and neither reviewed this page before it published. Everything above comes from public material on the dates shown. How the index grades.