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Manupatra

Manupatra is India's oldest legal research platform, founded in 2000 as the country's first digital legal research provider and launched, as the company tells it, at the height of the dot-com collapse. The database covers Indian case law from the Supreme Court, all High Courts and all tribunals, alongside legislative, regulatory and procedural material, commentaries and secondary sources across Indian jurisdictions and Commonwealth countries, and the platform reports more than 10 million indexed legal documents and judgments and over 150,000 active users.

Judgments and statutes are cross-linked through citations, judicial treatment and editorial classification, and currency is signalled to the researcher through effective-date highlights and blue, yellow and red flag indicators that mark whether an authority is still good law. The artificial intelligence sits in three named features on the research platform. Manupatra AI Search, launched in December 2025, is built on semantic AI and large language models and retrieves judgments by legal concept rather than by keyword, returning the ten most relevant cases organised into Facts, Issues, Arguments, Reasoning, Ratio and Summary, each traceable to its source document, with an AI-generated analysis panel and a follow-up chatbot.

AI Summary produces judgment summaries and AI Compare sets judgments side by side. Alongside these the company sells ManuWorks, a separately branded AI toolkit offering OCR, summarisation, translation, document question-answering, case timeline generation, document comparison and AI-assisted drafting. AI features are metered separately from the content subscription through a published credit wallet. The wider Manupatra suite, sold on its own domains, includes Mykase for practice, case and IP management, Manucomply for compliance, Manucontract for contract lifecycle work, Manupatra Academy for legal education, and BDlex, a Bangladesh legal database.

The company is Manupatra Information Solutions Pvt. Ltd., founder-led by Deepak Kapoor, with a registered office in New Delhi, a corporate office in Noida and a team of more than 175 across offices in India and Bangladesh.

Vendor siteNoida, Uttar Pradesh, IndiaFounded 2000
Last verifiedSeptember 13, 2026
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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.

BB on AI CentralityThe models are the engine of a core capability, layered on a product that would still function without them as a document or workflow system.

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.

Artificial intelligence is a substantial, named, shipped layer on a research platform that existed for twenty-five years without it, which is the B band rather than the A. What ships is specific and dated. Manupatra AI Search launched in December 2025, is described by the vendor as powered by semantic AI and large language models, and retrieves judgments by legal concept rather than keyword; AI Summary generates judgment summaries; AI Compare sets judgments side by side.

The separately branded ManuWorks toolkit adds OCR, summarisation, translation, document question-answering, case timeline generation, document comparison and AI-assisted drafting, each with its own published credit rate. The product page carries the HTML title 'Powered by AI' and the headline 'India's trusted Legal Research partner, Powered by AI', and the features link states the platform uses NLP, AI and ML for information retrieval.

What holds it off A is that the vendor itself positions the AI as one retrieval mode among several rather than as the product. Its own guidance directs users to MANU SEARCH, LEGAL SEARCH and CITATION SEARCH for precise, literal or Boolean queries and reserves AI Search for meaning-based ones, and the AI is metered separately from the content subscription through a credit wallet, so a subscriber can hold the platform without holding the AI.

The underlying asset is the editorially enriched corpus and the citation and treatment apparatus, which predate the models and would survive their removal. Verified 13 September 2026.

Source: Vendor Published
BB on Citation Accuracy and Hallucination DisclosureGrounding is real and documented, with linked primary sources and a described retrieval method, short of published accuracy figures an outsider can test.

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 architecturally specific, and no accuracy figure is published, which is the B band precisely. The grounding is described in the vendor's own AI brochure and is more than an assertion: AI Search runs against a proprietary, editorially enriched corpus rather than public web data, results are returned as the ten most relevant judgments organised into Facts, Issues, Arguments, Reasoning, Ratio and Summary, hovering Reference confirms the case source, clicking Citation opens the full judgment, and the vendor states that every insight is explainable and traceable to verified legal sources.

The platform also surfaces judicial treatment directly, detecting overruled, distinguished and conflicting judgments and marking currency with blue, yellow and red flags, so the citation-status limb of the A band is satisfied even though the band overall is not. R40 governs the hallucination claim rather than the D limb: the brochure states that the editorial foundation ensures the AI operates strictly within the legal framework, significantly reducing inaccuracies and eliminating AI hallucinations, and that claim stands alongside real controls rather than in place of them, so 'bare' does not apply.

The failure-modes limb of the A band is satisfied, and it is the most substantive thing this vendor publishes about the limits of its own AI. The brochure carries a section headed 'Guidance on Using AI Search' with an express 'When NOT to Use AI Search' list, telling users to avoid AI Search for precise or literal queries, party names, case citations, exact statutory phrases and verbatim quotations, stating that it does not follow Boolean logic, and routing those queries by name to MANU SEARCH, LEGAL SEARCH and CITATION SEARCH.

A further page contrasts well-framed and poorly framed queries across nine worked examples. Very few records in this corpus publish where their own retrieval is weak, and this one does it in the vendor's own voice and in specific terms. What keeps the row at B is the limb the band leads on: no measured accuracy is published for AI Search, AI Summary or AI Compare, no test set is described, no error rate or evaluation exists, and nothing quantifies the elimination claim, which is an absolute assertion of the kind this axis exists to test.

The remaining A limb also fails: nothing states that the system reports finding no support, and on a product that always returns a ranked ten, whether the tenth result is relevant or merely nearest is unanswered. The agreement pulls the other way and is recorded because it is the vendor's own instrument: clause 11.12 states that judgment text on the site is computer generated and that authenticity, correctness and preciseness must be verified from the certified copy, and clauses 15.1 to 15.3 disclaim any warranty of accuracy and place verification checkpoints on the user.

Verified 13 September 2026. Note amended 13 September 2026 under R125(3) to credit the published limitation disclosure on the failure-modes limb, the grade being unchanged; the disclosure was first recorded on Autonomy and Oversight, where R124(2) correctly declined to credit it.

Source: Vendor Published
BB on Autonomy and Oversight ModelA written commitment that the models work alongside a supervising lawyer, with real review surfaces, short of the full control structure: commonly the threshold at which the system stops or what happens after it is wrong.

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.

Substantive published material on how the tool is meant to be used and where it should not be relied on, short of the A band's thresholds and review surfaces. The strongest item is unusual enough to name in full. The vendor's AI brochure carries a section headed 'Guidance on Using AI Search' with an express 'When NOT to Use AI Search' list, telling users to avoid AI Search for precise or literal queries, party names, case citations, exact statutory phrases and verbatim quotations, stating that AI Search does not follow Boolean logic, and routing those queries to the named non-AI modes MANU SEARCH, LEGAL SEARCH and CITATION SEARCH.

That is a published negative boundary attaching to a named mode, and it is rarer in this corpus than a confidence score. Around it sit real verification affordances: Reference hover to confirm the source, Citation click to open the full judgment, and a follow-up chatbot for narrowing rather than for acting. The agreement reinforces it, clause 15.3 placing responsibility for sufficient procedures and checkpoints on the user and clause 11.12 requiring verification against the certified copy.

What is absent is what A asks for. No confidence score, no threshold, no statement of what the system does with a query it cannot answer well, no review surface before output, and nothing at all on oversight of the ManuWorks AI Drafter, which generates legal drafts at 50 credits per query with no described review step. R124(2) is the reason this is B and not A: the constraint published here attaches to a named mode but describes which queries the mode suits rather than what its output may not be used for, which is the limb the Verbit tier constraint satisfied. Recorded against parking item 2 as the closest instance in this lane. Verified 13 September 2026.

Source: Vendor Published
CC on Operational and Outcome EvidenceCustomer logos and unattributed testimonials stand in for evidence, or results are quoted with no basis stated.

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.

Scale is claimed at length and no customer is named and no outcome is measured, which is the C band. What is published is substantial as usage evidence: more than 150,000 active users, more than 10 million legal documents and judgments indexed, twenty-five years of operation, a team of more than 175, and offices across India and Bangladesh. The About page's 'Who We Serve' section enumerates five clientele categories, being legal professionals and law firms, in-house legal departments in corporations and banks, academic institutions, government bodies and regulatory agencies, and law students and researchers across Asia.

Categories are not customers. Not one law firm, company, court, tribunal or university is named anywhere on the surfaces read, there is no client wall, no case study, no testimonial and no logo strip, which is a marked contrast with the penetration disclosure typical of vendors at this scale in the corpus. Nor is any outcome quantified: nothing states time saved, research hours displaced, accuracy improved or matters affected, and the AI brochure's benefit claims are functional descriptions rather than measurements.

The 150,000 figure is itself unattributed and undated, appearing as a counter on the product page and in the About page metadata. The seed recorded 100,000 users, which the vendor's own current pages contradict; the figure written here is the vendor's. Verified 13 September 2026.

Source: Vendor Published
BB on Privilege and Confidentiality PostureSubstantive published commitments on confidentiality and training use, short of the full picture: commonly silence on segregation between users or matters, or on what the underlying model provider may retain.

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 across every limb this axis tests except the one R33 makes decisive, which is what holds an otherwise exceptional record at B. The commitments sit in the published customer agreement rather than a policy page, and they are unusually precise. Clause 4.1 defines Confidential Information to include documents, data, personal data, case files, names, facts, legal strategies and client information uploaded through the website, the AI tools or any related service.

Clause 4.2 requires that it be treated as strictly confidential, used solely for the limited purpose of providing the specific service requested, and not copied, stored, retained, archived, analysed, mined, disclosed or shared for any other purpose, with access restricted to need-to-know personnel under equivalent confidentiality obligations. Clause 4.3 bars disclosure to any third party including affiliates, subcontractors, AI engines and cloud providers without prior express written consent.

Clause 4.7 requires permanent deletion of all Confidential Information and any copies, backups, AI memory, logs, caches or traces immediately after the request is fulfilled and in no event later than 24 hours, with written certification of deletion available on request. Clause 5.8 bars employee viewing of Subscriber Content or AI outputs except to resolve a specific technical issue the Subscriber has raised, with such access logged and minimised.

Clause 4.8 makes these obligations survive termination indefinitely. Training is consent-gated and graded separately. The limb that fails is privilege and work product, and it fails as a matter of language rather than of substance: neither privilege, professional secrecy, work product nor any equivalent is named anywhere, and nothing addresses what happens to privileged material if disclosure is compelled. Clause 4.1's enumeration of case files and legal strategies is the closest the corpus has come outside Verbit's express work-product clause, and it is not the same thing. Verified 13 September 2026.

Source: Vendor Published
BB on UPL and Professional Responsibility PostureA real position is published on advice versus tooling, short of full treatment: commonly a disclaimer without the supervision and competence dimension, or silence on jurisdiction limits.

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.

Substantive published commitments short of alignment with any conduct rule, which is the B band. The agreement addresses the question head on rather than by implication. Clause 16.1, headed 'No Legal Advice', states that material contained on or made available through the site is not intended to and does not constitute legal advice and does not in any manner establish a client-advocate relationship. The disclaimer published on the legal page repeats that the company does not warrant any form it provides and is not creating a lawyer-client relationship by providing forms, and adds that forms should be used as a guide and modified to suit requirements and laws, at the user's own risk.

Clause 15.3 places on the user the responsibility for implementing sufficient procedures and checkpoints to satisfy accuracy requirements for input and output. Clause 11.12 goes further than most records in this corpus by requiring that the authenticity, correctness and preciseness of judgment text be verified from the certified copy of the judgment, which is a verification duty rather than a disclaimer. Taken together that is a real posture on who is answerable for the output.

What is absent is any engagement with the professional rules themselves. No conduct rule of any jurisdiction is named, the Bar Council of India is not mentioned, and no clause requires the subscriber to use the product consistently with professional obligations. The gap is sharper than usual on this record and is named rather than passed over: the Supreme Court of India held in July 2026 that citing unverified AI-generated precedent is professional misconduct and directed the Bar Council of India to frame norms, and this vendor publishes that ruling as editorial content on its own updates service while publishing nothing about what its own AI features mean for that duty. Verified 13 September 2026.

Source: Vendor Published
CC on AI Governance and Bias DisclosureResponsible AI principles are published without a mechanism, a testing regime, or anything a buyer could audit.

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.

Something is published and it is a paragraph, which is the C band rather than the D. The legal page carries a section headed 'Use of AI' reading, in full, that the vendor is committed to using artificial intelligence responsibly and prioritises data privacy, bias mitigation, transparency, human oversight, accountability, user consent, and collaboration with regulations, with the stated aim of maximising AI's benefits while ensuring ethical practices and minimising potential risks.

That is a list of the right words and it is the whole of it. Nothing behind any of the seven named priorities is published: no framework is adopted or certified, no accountable owner or committee is named, no governance process is described, no bias testing is described and no results of any kind are disclosed, and nothing states how human oversight is exercised in a product where the oversight the vendor actually documents is guidance to the user rather than a control in the system.

Bias in particular is asserted as a priority and never returned to, on a product whose AI ranks and summarises judicial authority and surfaces judicial treatment, where a systematic tilt in which precedents surface would be invisible to the researcher. Recorded and not credited as governance, because they are commercial or contractual rather than governance instruments: the agreement's AI section is a strong commitment and is graded on the confidentiality and training rows, and the responsible-AI paragraph is not tied to it.

The Grievance Redressal Officer named on the same page is a statutory Indian IT Act appointment for complaints handling, not an AI accountability owner, and is recorded as such. Verified 13 September 2026.

Source: Vendor Published
BB on AI Safety and Data StewardshipSubstantive published policy covering most of the ground, short of the full set: commonly no named subprocessor list or no stated incident practice.

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.

Substantive published policy covering most of the ground, missing the named subprocessor list, which is the B band and the single limb it names. What is published is contractual rather than promotional and it is specific. Clause 4.4 requires industry-standard technical and organisational security measures. Clause 4.5 commits to notifying the Subscriber in writing within 24 hours of becoming aware of any actual or suspected unauthorised access, disclosure, loss, corruption or breach, to providing full details and impact, to containing, investigating and remediating at its own cost, and to cooperating in legal, regulatory or remedial action.

A named notification window with a stated content requirement is the limb most records in this corpus lack entirely. Clause 4.6 accepts the role of data processor with the Subscriber as data fiduciary under the Digital Personal Data Protection Act 2023 and commits to the Information Technology Act 2000. Clause 4.7 requires deletion within 24 hours with written certification. Clause 5.3 requires that any storage be temporary, encrypted and automatically deleted after use.

The privacy policy adds encryption technologies, secure servers and firewalls, access control mechanisms, employee confidentiality agreements and training, and states these are regularly reviewed, and records compliance with the SPDI Rules 2011. What is missing is the subprocessor limb and it is missing in an interesting way. No processor is named anywhere, and clause 4.3 explains why the vendor might think none needs naming, since it bars disclosure to any third party including subcontractors, AI engines and cloud providers without express written consent.

The privacy policy nonetheless discloses that third parties perform payment processing, email delivery and hosting, and that the products may integrate cloud storage services including Dropbox and Google Drive, so processors exist and none is identified. No certification supports any of it. Verified 13 September 2026.

Source: Vendor Published
BB on AI Liability and RecourseA real published position on liability, short of the full picture: commonly a stated indemnity without scope or caps.

AI Liability and Recourse

What the vendor stands behind contractually when its output is wrong. Indemnities, caps, carve outs, insurance, and whether any of it is published or only reachable through a negotiated agreement.

A published agreement addresses three of the four limbs with real specificity and the overall allocation is heavily one-sided, which is B rather than A. Warranty is addressed by exclusion: clauses 25.1 and 25.2 provide the information on an 'As Is' basis and disclaim all warranties including merchantability, fitness for purpose and non-infringement, and clauses 15.1 and 15.2 disclaim any representation that the service will be correct, accurate, reliable, uninterrupted or timely.

Liability is addressed and largely excluded: clauses 25.3 and 25.4 exclude liability in contract or tort for any loss howsoever arising in connection with the service, expressly including where caused by the vendor's own negligence, and clause 25.5(i) is the provision that matters most on this axis, excluding liability for any claim relating to the subscriber's inability or failure to perform legal research work properly or completely, or to any decision made or action taken in reliance on the Data.

A cap exists at clause 26.1, limited to the aggregate charges paid during the subscription period, though it is drafted as applying to claims relating to copyright in the data rather than as a general cap, which is a real gap named here rather than smoothed over. What lifts this above the floor is that the agreement also runs the other way, which is uncommon in this corpus. Clauses 21.2 and 26.3 require the vendor to indemnify, defend and hold harmless the Subscriber, its clients, employees and affiliates against claims, losses, damages, liabilities, penalties and legal costs arising from any breach of confidentiality or misuse of Subscriber Content, any unauthorised access or data breach, any negligence, wilful misconduct or violation of law by the vendor or its personnel, and any infringement of intellectual property rights.

Clause 5.9 adds immediate termination, indemnification and injunctive relief without proof of special damages for misuse of Subscriber Content, and clause 12.1 a prorated refund. Insurance is not addressed anywhere. Verified 13 September 2026.

Source: Vendor Published
CC on Practice Systems Integration DepthIntegrations are listed as logos or marked as coming, with no documentation an implementer could use.

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.

Integrations are claimed and some host applications are named, with no documented catalogue and no configuration detail, which is the C band. What is named is thin and scattered rather than gathered on an integrations page, and no integrations page exists in the navigation, which is itself a page-inventory finding under R20. The research platform publishes a 'Plug In' item in both the Subscription and Research menus, resolving to ManupatraAlert, an alerting plug-in on the manupatrafast.com property.

The privacy policy discloses that the products may integrate or offer third-party services including data visualisation services and cloud storage solutions, naming Dropbox and Google Drive, for uploading, storing or sharing documents. The wider suite implies internal connection between the research platform and the Mykase practice and case management product, Manucomply and Manucontract, but each sells on its own domain with its own login and nothing published describes data moving between them.

What is absent is everything the higher bands ask for. No practice management system, document management system or CRM used by Indian firms is named as supported, so a buyer cannot establish whether its own system connects. No public API reference, developer documentation, connector register or authentication model was located. No direction of flow, prerequisite or configuration step is described for any connection, including the plug-in.

Nothing states whether AI Search or the ManuWorks toolkit can be reached from inside another application or only from the vendor's own interface. Verified 13 September 2026.

Source: Vendor Published
BB on Deployment Model and Data ResidencyDeployment model is stated clearly with partial residency detail, or residency is offered without the processing location being addressed, or the tenancy model is stated on its own with no residency detail published.

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.

Cloud delivery with a published residency commitment and no tenancy model stated, which under R38 is B because tenancy and region are co-equal limbs and publishing either clears C. Residency is answered in unusually committal terms for this corpus. The privacy policy carries a section headed 'Data Localization' stating that all personal information is stored and processed on servers located within the user's country of residence, that for users in jurisdictions requiring data localisation the vendor ensures personal data is stored and processed on servers physically within that country's territorial boundaries, and that it does not transfer such data outside the country unless in accordance with applicable law and with appropriate safeguards.

The About page describes the company as a cloud-first platform, and the AI brochure states that the models are trained on Indian data and built in India, which speaks to where the processing sits even though it is written as a provenance claim. The limits are real and are named rather than left to inference. The localisation commitment is written about personal information, and the material this axis most concerns on an AI product is Subscriber Content uploaded to the AI tools, which the agreement governs on confidentiality terms without stating where it is processed; the two are not the same category and nothing joins them.

No tenancy model is described anywhere, so a buyer cannot establish whether a firm's uploaded documents sit in a shared or isolated environment. No data centre, region, availability zone or cloud provider is named, no on-premises or private deployment is offered or refused, and nothing distinguishes storage from processing for the AI features specifically. Verified 13 September 2026.

Source: Vendor Published
DD on Security Certifications and Trust CenterNo independent security attestation located.

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.

No certification and no trust centre were located on any surface, which is the D band, and the absence is the vendor's rather than this index's. The page inventory was taken from the navigation and footer under R20 and there is no security page, no trust page, no compliance page and no certification badge anywhere on the estate: the footer's Company column runs About, Contact, Careers and Legal, and the Legal page's six tabs are Corporate, Copyright, Privacy Policy, Disclaimer, IT Compliance and Public Record.

No ISO 27001, ISO 27701, SOC 2, StarAudit, CERT-In empanelment, PCI DSS or any other standard is claimed, no auditor is named, no report period is given, and no certificate, attestation or penetration test summary is offered for download or on request. A targeted search for certification claims returned nothing attributable to the vendor. What exists instead is a description of controls without external validation, and it is recorded so the grade is read as a disclosure finding rather than as a claim about the vendor's actual security: the privacy policy lists encryption technologies, secure servers and firewalls, access control mechanisms, and employee confidentiality agreements and training, stated to be regularly reviewed and updated, and the agreement commits at clause 4.4 to industry-standard technical and organisational measures.

The statutory position is disclosed, being compliance with the Information Technology Act 2000, the SPDI Rules 2011 and the Digital Personal Data Protection Act 2023, with a named Grievance Redressal Officer, but a statutory compliance assertion is not an independent attestation and is not credited here. Verified 13 September 2026.

Source: Vendor Published
CC on Model Supply Chain DisclosureThe vendor refers to advanced or proprietary models without identifying what sits underneath.

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 supply chain is partly disclosed, which is the B band's territory on partiality but falls to C because what is disclosed is the technology class and the build location rather than anything about the models themselves. What the vendor does say is more than silence and is recorded precisely. The AI brochure and the December 2025 launch material both state that Manupatra AI Search is powered by semantic AI and large language models.

The brochure states that the system is trained on Indian data and built in India, and that it runs on a proprietary, editorially enriched legal knowledge ecosystem developed over decades rather than on generic AI systems trained on public or non-curated data. That answers what the models were pointed at and where the work was done. It does not answer the questions this axis asks. No model is named, no version is given, and no provider is identified, so a buyer cannot establish whether the large language models are the vendor's own, licensed, or accessed as a third-party service, and the phrase 'built in India' describes the product rather than the model.

Nothing states where inference runs. No commitment to notify subscribers of a model change was located. There is no subprocessor list that would answer the question by another route. One provision cuts against the silence and is noted because a careful reader will find it: clause 5.5 of the agreement bars the vendor from making Subscriber Content available to third parties including, expressly, AI vendors and cloud providers without prior express written consent, which contemplates that such vendors exist in the stack while naming none of them. Verified 13 September 2026.

Source: Vendor Published
AA on Commercial TransparencyA buyer can learn what this costs without entering a sales process: published rates, the unit being charged, and what implementation adds.

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.

Figures, units, structure and the governing commercial terms are all published and a buyer can plan against them without a sales conversation, which is the A band. The AI Solutions page publishes an ungated price table. Unlimited AI Summary access is 5,000 rupees a year for Supreme Court judgments, 5,000 rupees a year for High Court judgments and 10,000 rupees a year for both, all stated exclusive of GST. AI wallet plans covering AI Search, AI Compare and AI Summary are published at 1,000 credits for 6,000 rupees, 1,500 credits for 9,000 rupees and 2,000 credits for 12,000 rupees.

The unit of charge is not only stated but decomposed: the ManuWorks toolkit publishes per-feature consumption at 15 credits per page for OCR, 3 per page for summarisation, 20 per page for translation, 5 per query for question-answering, 8 per page for timeline generation, 15 per document for comparison and 50 per query for AI drafting, with credit value fixed at 1 credit to 1.25 rupees, a 10,000 rupee minimum first purchase and a 5,000 rupee minimum top-up.

Activation is stated to be pro-rated and a credit dashboard showing top-ups, usage and balance is described. So a buyer can model the cost of a specific workload in advance, which almost nothing else in this corpus permits. The commercial terms behind the price are published too, in the agreement: advance payment, non-refundability, renewal and deactivation mechanics, the vendor's right to modify charges with effect from the next renewal term, a seven-day window to dispute transactional charges, and taxes payable in addition.

Two limits are named rather than glossed. The content subscription itself, as opposed to the AI add-ons, routes to a subscription plans page and the agreement states that the product price card is available on request, so the platform's own base price is less exposed than its AI pricing. And clause 3.9's transactional pricing statement implies a usage-metered tier whose rate card is not published. Verified 13 September 2026.

Source: Vendor Published
BB on Firm and Practice CoverageSegment and practice coverage is described with substance, short of the boundaries: what is supported is clear, what is not is left open.

Firm and Practice Coverage

Who the product is actually built for. AmLaw, midlaw, small firm and solo, in house departments, government and courts, and which practice areas are supported rather than merely claimed.

Coverage is documented with real substance across jurisdiction, content type and buyer role, short of the stated limits the A band requires. Jurisdictional coverage is the strongest part and is specific: Indian case law from the Supreme Court, all High Courts and all tribunals, together with legislative, regulatory and procedural material, notifications, reports, commentaries and secondary sources across all Indian jurisdictions and Commonwealth countries, with a dedicated content coverage page, more than 10 million indexed documents, and daily addition of new laws, notifications and judgments.

A separate Bangladesh database, BDlex, is sold alongside. Buyer roles are addressed explicitly and across the range: the AI pricing page names students, lawyers, law firms and corporate legal teams as the audiences for the credit model, and the About page enumerates legal professionals and individual practitioners, in-house legal departments in corporations and banks, academic and educational institutions, government bodies, regulatory agencies and policy makers, and law students, researchers and educators across Asia.

Practice coverage is addressed through the content rather than through practice-area packaging, which suits a general research database, and R15 governs that limb: a horizontal case-law platform does not vary by practice area and is neither credited nor penalised for the absence of practice-specific editions. What holds it off A is that no limit is stated anywhere. Nothing identifies a jurisdiction, court level, tribunal or content type that is out of scope, nothing states the earliest coverage date or any gap in the historical record, nothing says which Commonwealth jurisdictions are included and which are not, and nothing states whether the AI features cover the whole corpus or only parts of it, which matters because AI Search is described in terms of judgments while the database also holds statutes, rules and commentary. Verified 13 September 2026.

Source: Vendor Published
Sources on file

5 public documents

The public pages on file for Manupatra, with the recorded signals each one supports and the date it was last read. Open any of them and check the reading against the record.

Pricing

From ₹5,000 per year

  • Manupatra is one of the few vendors in this index where you can work out what the AI will cost you before you speak to anyone.
  • The AI features are priced two ways and both are published. For summaries there is a flat annual fee: ₹5,000 a year for unlimited AI summaries of Supreme Court judgments, ₹5,000 a year for High Court judgments, or ₹10,000 a year for both, all before GST. For everything else there is a credit wallet: ₹6,000 buys 1,000 credits, ₹9,000 buys 1,500, and ₹12,000 buys 2,000, and those credits are spent across AI Search, AI Compare and AI Summary.
  • The useful part is that the vendor publishes what each action costs in credits, so you can estimate a real workload rather than guess. Running text recognition over a scanned document is 15 credits a page, summarising is 3 credits a page, translating is 20 credits a page, asking a question about a document is 5 credits, generating a case timeline is 8 credits a page, comparing two documents is 15 credits, and asking the AI to draft something is 50 credits. A credit is worth ₹1.25. The first purchase of toolkit credits has to be at least ₹10,000 and top-ups at least ₹5,000. A dashboard shows what you have bought, used and have left, and activation is pro-rated if you join mid-term.
  • Two things to watch. Credits expire with your subscription and are not carried into a renewal. And these prices are for the AI; what the underlying research subscription itself costs is not published, so you will need to ask for that price card.

Published figures with a published unit of charge, in Indian rupees, exclusive of GST. Two structures run in parallel. A flat annual AI Summary tier: unlimited summaries of Supreme Court judgments at ₹5,000 a year, unlimited summaries of High Court judgments at ₹5,000 a year, and both together at ₹10,000 a year. A consumption-based AI wallet covering AI Search, AI Compare and AI Summary: 1,000 credits at ₹6,000, 1,500 credits at ₹9,000, and 2,000 credits at ₹12,000.

Credits are stated to be valid only for the duration of the current subscription and are expressly not carried forward at renewal. The separately branded ManuWorks AI toolkit is metered on the same credit unit with a published per-action rate card: OCR at 15 credits per page, summarisation at 3 credits per page, translation at 20 credits per page, document question-answering at 5 credits per query, case timeline generation at 8 credits per page, document comparison at 15 credits per document, and AI drafting at 50 credits per query.

Credit value is fixed at 1 credit to ₹1.25, with a minimum first-time purchase of ₹10,000 and a minimum top-up of ₹5,000, both exclusive of GST. Activation is stated to be pro-rated within a subscription period and a credit dashboard reports total top-up credits, credits used and current balance. Commercial terms are published in the subscriber agreement: subscription fees payable in advance, payments expressly non-refundable, deactivation on expiry with a discretionary 15-day grace on assurance of payment, the vendor's right to modify charges taking effect at the next renewal term, a seven-day window to dispute transactional charges before they are deemed accepted, and taxes, duties and levies payable in addition.

The content subscription's own price is not published and the agreement states the product price card is available on request.

Confidentiality and data terms: No business associate agreement, data processing addendum or separately signable data instrument is published, and none is needed to reach the substance, because the confidentiality and AI terms sit inside the main subscriber agreement rather than in a side document. That agreement, published as a PDF and reachable from the legal page, carries a Confidentiality and Data Protection section and a dedicated AI Usage, Model Training and Restrictions on Use of Subscriber Content section. Between them they commit the vendor to treat uploaded case files, legal strategies and client information as strictly confidential, to use them solely for the specific request, to bar disclosure to any third party including AI vendors and cloud providers without prior express written consent, to notify the subscriber in writing within 24 hours of any actual or suspected breach with full details and remediation at the vendor's cost, to delete all uploaded content and any copies, backups, AI memory, logs, caches or traces within 24 hours with written certification available, and not to train on subscriber content absent a standalone signed consent. The vendor accepts the data processor role with the subscriber as data fiduciary under India's Digital Personal Data Protection Act 2023 and commits to the Information Technology Act 2000 and the SPDI Rules 2011. What is absent is external validation of any of it: no ISO, SOC 2 or CERT-In empanelment is claimed anywhere, no auditor is named, no trust centre exists, and no processor is identified by name notwithstanding that the privacy policy discloses payment processing, email delivery, hosting and cloud storage integrations with Dropbox and Google Drive.

Note: Figures, credit rates and structure read directly from the vendor's own ungated AI Solutions page on 13 September 2026, and the commercial mechanics read from the published subscriber agreement PDF. entryPriceUsd carries the published numeral 5000 in its native currency, Indian rupees, following the settled corpus convention confirmed at write time across eleven existing VendorPricing rows, the closest analogue being Lexlegis.ai, also Indian, which holds 9000 for a figure displayed as ₹9,000. No currency conversion has been applied and none should be inferred; the field name asserts a currency the corpus data does not carry, which is recorded as a parking item for the pull close rather than resolved here. The figure taken is the lowest published annual price on the estate, being 5,000 rupees a year for unlimited AI Summary access on Supreme Court judgments, stated exclusive of GST. Two limits qualify the A on Commercial Transparency and belong here too. The published prices are for the AI layer; the underlying content subscription routes to a subscription plans page and clause 3.1.3 of the agreement states that the product price card is available from the vendor on request, so the platform's base price is less exposed than its AI add-ons. And clause 3.9 contemplates subscribers under Transactional Pricing receiving a detailed statement of usage charges, implying a metered content tier whose rate card was not located.

Legal Signals

What each signal means

A 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.

Confidentiality and Privilege

Client Data in Training

Can material a lawyer puts into this product be used to train a model?

Opt in

Training occurs only where the customer has affirmatively enabled it.

Training is barred by default and available only on the subscriber's express written consent, which is this value and the strongest instance of it in the corpus. Clause 5.2 of the published agreement, headed 'Absolute Prohibition on AI Training and Internal Use', bars the vendor from using Subscriber Content in whole, in part, anonymised, pseudonymised, aggregated, derived or otherwise for training, fine-tuning or improving any AI or machine learning model, for developing or enhancing algorithms, features or products, for internal analytics or database enrichment, for quality improvement, troubleshooting or research and development, or for teaching, demonstration or testing.

The anonymised and aggregated carve-out that has qualified most training clauses in this corpus is closed here rather than left open. Clause 5.7 requires that any contemplated use for training or improvement be authorised by prior express written consent obtained through a standalone written agreement, and states that silence or continued use of the service shall not constitute consent, which forecloses the deemed-consent route.

Clause 14.3.1 repeats the prohibition in the ownership section and clause 5.9 makes breach a material breach carrying indemnification and injunctive relief. The value is opt-in rather than contractual-never because the agreement does not commit never to train; it commits not to train without a separate signed permission the subscriber may withhold at its sole discretion. That follows the Agiloft precedent on a consent-governed no-training clause.

Recorded for completeness: the privacy policy states the same rule in weaker terms for user data generally, and R43(1) is discharged, the agreement having been located and read in full.

Source: Vendor Publishedunless the Subscriber has provided prior express written consent, which may be withheldAs of Sep 13, 2026Evidence

Prompt and Output Retention

How long does the product keep what a lawyer typed, and can that be set to zero?

Disclosed fixed window

A specific retention period is published and the customer cannot change it.

A fixed maximum retention period is published in the customer agreement, which is this value, and the period is the shortest located in this corpus. Clause 4.7, headed 'No Retention / Mandatory Deletion', requires the vendor to permanently delete and remove all Confidential Information uploaded by the client and any copies, backups, AI memory, logs, caches or traces immediately after fulfilling the specific request and in no event later than 24 hours after use, and to provide written certification of deletion on request.

The enumeration is what makes it gradeable rather than aspirational: AI memory, logs and caches are the places retention actually survives a deletion promise, and they are named. Clause 5.3 adds that the vendor shall not store, cache, retain, archive or otherwise preserve Subscriber Content beyond what is strictly necessary to generate the requested output, and that all storage must be temporary, encrypted and automatically deleted immediately after use.

Clause 5.6 extends the same treatment to AI outputs containing or derived from Subscriber Content, which are to be treated as the subscriber's confidential information and not stored, reused or made available to any other user or system. Two limits are recorded rather than smoothed. The 24-hour rule governs Subscriber Content uploaded to the service and does not by its terms reach the query text of a research search or the account and usage telemetry the privacy policy describes collecting.

And the privacy policy's own retention section is the opposite shape, committing only to keep personal information as long as necessary and directing readers to ask the data protection manager for periods; where the two differ on subscriber material the agreement governs.

Source: Vendor Publishedin no event later than 24 hours after useAs of Sep 13, 2026Evidence

Ethical Walls and Matter Segregation

Does retrieval respect the firm’s ethical walls, or can the model read across them?

Claimed, not documented

Segregation is asserted in public materials with no published detail on how it is enforced.

Access control is committed to in contract and no segregation model is described, which is this value, though the reason is unusual enough to state carefully. What is documented is vendor-side access rather than customer-side walls, and it is documented well: clause 4.2(d) restricts access to need-to-know personnel bound by equivalent confidentiality obligations, and clause 5.8, headed 'Monitoring / Human Review', bars any employee from viewing Subscriber Content or AI outputs except where necessary to resolve a specific technical issue the subscriber has raised, requiring any such access to be logged, minimised and subject to confidentiality obligations.

A logged-access commitment of that kind is rare in this corpus. There is also a real user-level access regime: clause 11.10 requires IP-based and remote-access subscribers to supply a list of named Authorized Users before the subscription starts, clause 3.5 makes the subscriber liable for all actions under its credentials and reserves termination for password sharing, clause 3.6 makes an organisation responsible for its constituents, and clause 2.3 limits display to one person at a time on non-IP plans.

What is not addressed is the thing this signal names. Nothing describes segregation between matters, between clients, or between users within a subscribing firm, no permission model, role model or ethical wall is described, and nothing states whether documents one user uploads to the ManuWorks toolkit are reachable by a colleague on the same organisational subscription. The product class softens this only partly under R15: a shared research database has no matter structure, but the AI toolkit takes uploaded case documents and that is precisely where a wall would matter.

Source: Vendor Publishedrestrict access strictly to employees or personnel who have a need-to-knowAs of Sep 13, 2026Evidence

Third Party Request and Subpoena Notice

If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?

Disclosure addressed, notice absent

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.

Compelled disclosure is addressed and customer notice is absent, which is this value under R39. The privacy policy states that the vendor may be required to disclose personal data to third parties where required under applicable laws, judicial orders or governmental regulations, alongside transfer in a merger, acquisition, divestiture or dissolution, and disclosure to protect rights, property or safety. Nothing anywhere states that the subscriber would be told a demand had been received, given an opportunity to object or to seek relief, or informed after the fact, and no transparency report or law-enforcement guidelines page exists on the estate.

A genuine tension between the two instruments is recorded rather than resolved silently, because a reader who finds it unaided and does not find it here would trust the record less. The customer agreement is drafted more protectively than the policy and contains no compelled-disclosure carve-out at all: clause 4.3 states that the vendor shall not disclose or make available Confidential Information to any third party without the subscriber's prior express written consent, and clause 5.5 repeats it for Subscriber Content.

Read literally the agreement admits no exception for a court order, which cannot be the intended effect and which no clause reconciles. Under R37 the agreement governs where the two conflict, but the agreement's silence on legal process is silence rather than a notice commitment, so it cannot lift this value. The practical position for a buyer is that the vendor has said what it may disclose under compulsion, in the weaker of its two instruments, and has said nothing at all about telling the customer.

Source: Vendor PublishedWhere required under applicable laws, judicial orders, or governmental regulationsAs of Sep 13, 2026Evidence
Accuracy and Authority

Primary Law Corpus Provenance

Where does the law in this product come from, and does the vendor have the right to use it?

Sources named and licensed

The vendor names its primary law sources and the licence or public domain basis for each, with an update cadence.

Sources are identified and the licensing basis for third-party material is stated in the agreement, which is this value and only the second instance of it in this pull. Provenance is addressed in three places. Clause 10.2 of the agreement states that certain information and data made available are the property of content providers and are identified as such, and that the vendor has been licensed by those content providers to store, catalogue and distribute the information to subscribers, with no rights transmitted to the user.

The Public Record section of the legal page states that public records are created and maintained by government agencies and open for public inspection, that all data in the public records databases is supplied by courts and government agencies, that the vendor collects public records from established sources in the government and judiciary, and that in some cases this occurs under agreement with those suppliers whose terms of use and information protection requirements may be more stringent than applicable law.

The copyright section adds that third-party content has been reproduced after taking prior permission from the party concerned, whose copyright is retained. Against that the AI brochure grounds the models on the vendor's own editorially enriched corpus, built through citations, judicial treatment and interpretive summaries developed over decades, which is owned rather than licensed material. So a buyer can establish the classes of source and the basis on which each is held.

What is not published is a supplier-by-supplier register, any licence term or duration, or a statement of whether the licences extend to AI processing of the licensed material as distinct from its distribution, which is the live question on a licensed corpus feeding a language model.

Source: Vendor PublishedManupatra has been licensed by the content providers to store, catalogue and distributeAs of Sep 13, 2026Evidence

Good Law Verification

Does the product tell you when the authority it just cited has been overruled?

Own treatment signal

The vendor computes and surfaces subsequent history itself, with the method described.

The vendor operates its own treatment apparatus rather than licensing one, which is this value. The product page carries a section headed 'Be sure you are using Good Law' stating that with effective-date highlights and blue, yellow and red flag indicators the platform ensures every statute and judgment accessed is good law. A three-colour flag scheme applied to both statutes and judgments, with effective-date signalling, is a citator in substance and is the vendor's own: nothing indicates any part of it is licensed from another publisher, and the underlying treatment data is described in the AI brochure as part of the proprietary editorial enrichment built over decades through citations, judicial treatment and cross-references.

The AI layer is wired into it rather than bypassing it, which is the part that matters for this signal on an AI product. The brochure states that AI Search lets a user instantly determine whether a judgment has been overruled, distinguished or followed, identify conflicting judgments, and understand how courts have interpreted a statute over time, and the product page lists authority checks and citation maps among the built-in analytics.

Two limits are named. No methodology is published for how treatment is determined, whether editorially by the licensed advocates who enrich the corpus or algorithmically, and no coverage statement says which courts, which years or which content types carry flags, which matters on a database spanning all Indian tribunals and Commonwealth jurisdictions. And nothing states what a flag means in borderline cases or how quickly a new adverse judgment propagates to the flag.

Source: Vendor PublishedBlue, Yellow, and Red flag indicatorsAs of Sep 13, 2026Evidence

Refusal and Uncertainty Behaviour

What does the product do when the answer is not in the corpus?

Not addressed

No located public material addresses what the product does when it cannot ground an answer.

No located public material describes what the system does when it cannot produce a reliable answer, which is the floor, and the note records why that verdict sits alongside genuinely useful published guidance rather than against silence. The vendor publishes more about the boundaries of its AI than most records in this corpus. Its AI brochure carries a section headed 'Guidance on Using AI Search' with an express 'When NOT to Use AI Search' list, telling users to avoid AI Search for precise or literal queries, party names, case citations, exact statutory phrases and verbatim quotations, stating that it does not follow Boolean logic, and routing those queries to the named MANU SEARCH, LEGAL SEARCH and CITATION SEARCH modes.

A further page sets out how to frame a good query and contrasts well-framed and poorly framed examples. That is a published account of where the tool is weak, which is rare and is recorded as such. It is not this signal. Every one of those statements addresses what the user should do before running a query; none addresses what the system does after one. Nothing states that AI Search declines a query, flags low confidence, marks an uncertain result for verification, returns fewer than ten results when fewer are relevant, or tells the user it has found nothing responsive rather than returning the closest available matches.

On a retrieval product that always returns a ranked ten, whether the tenth result is relevant or merely nearest is exactly the question, and it is unanswered. The surfaces read on the date shown were the AI brochure in full, the product page, the AI solutions page, the AI Search FAQ page, whose four accordion bodies render client-side and did not return, the agreement and the legal page.

Source: Vendor PublishedAs of Sep 13, 2026Evidence

Fabricated Citation Record

Does a public court record exist addressing fabricated or hallucinated legal citations in output from this product?

None located

No court order, opinion or disciplinary record addressing fabricated or hallucinated legal citations produced by this product has been located as of the date shown. This is a statement about the public record on that one subject, not a finding about the product, and this signal is not a litigation history.

Searched on 13 September 2026 against the company name and the AI product name, across reporting and trackers covering Indian decisions on AI-generated fabricated citations, including the Supreme Court of India's July 2026 ruling and the 2026 line of cases preceding it. None located. No decision, order or tribunal finding names Manupatra or Manupatra AI Search as the source of a fabricated citation. Context is recorded because it bears on how this absence should be read, and it cuts in the vendor's favour rather than against it.

India has the most active fabricated-citation record of any jurisdiction in this corpus: a Supreme Court bench set aside National Company Law Tribunal and appellate orders resting on non-existent citations, held that citing unverified AI-generated precedent is professional misconduct for an advocate, and directed the Bar Council of India to frame norms, with earlier instances including a Bengaluru tax tribunal order recalled over four non-existent citations and a Bombay High Court assessment quashed over three invented precedents.

In the commentary that followed, Manupatra is named repeatedly as one of the authorised databases against which a citation should be verified, which is the opposite posture to the one this signal records. Under R119 this signal records fabricated legal citations in filings and nothing else, so the vendor's wider litigation or regulatory history, if any, would not appear here.

Source: Bar Guidance or Court RecordAs of Sep 13, 2026
Professional Responsibility

Bar Guidance Alignment

Has the vendor engaged in public with the ethics opinions its buyers are bound by?

Generic reference

Public materials refer to professional responsibility in general terms without naming guidance.

Professional responsibility is engaged in general terms without any guidance being named, which is this value. What exists is contractual and real as far as it goes. Clause 16.1 of the agreement, headed 'No Legal Advice', states that material on or made available through the site is not intended to and does not constitute legal advice and does not in any manner establish a client-advocate relationship, and the disclaimer on the legal page repeats that the vendor is not creating a lawyer-client relationship by providing forms.

Clause 11.12 requires that the authenticity, correctness and preciseness of judgment text be verified from the certified copy, and clause 15.3 places responsibility for sufficient procedures and checkpoints on the user. Those are duties pointed at the right question. What is absent is any named authority. No bar body, conduct rule or ethics opinion of any jurisdiction is cited, the Bar Council of India is not mentioned, and nothing maps any AI feature to a professional obligation.

The gap is sharper on this record than on most and is stated plainly. In July 2026 the Supreme Court of India held that citing unverified AI-generated precedent is professional misconduct and directed the Bar Council of India to constitute a committee to frame norms, with draft regulations on AI use in courts out for consultation. The vendor publishes that ruling as editorial content on its own legal updates service.

It publishes nothing connecting its own AI Search, AI Summary or AI Drafter to the verification duty the same ruling imposes, at a moment when its buyers are being told by their highest court that the duty is theirs personally.

Source: Vendor Publisheddoes not constitute legal advice nor does it, in any manner establish a clientAs of Sep 13, 2026Evidence

Billing and Fee Posture

Does the vendor address what happens to the bill when the work takes an hour instead of six?

Not addressed

The product sits inside a lawyer to client fee relationship and no located public material addresses billing, fee or disclosure treatment, with no savings claim published either.

Nothing published addresses what happens to the bill when AI-assisted work takes an hour instead of six, which is the floor, and all four of the higher values are false of this record rather than nearly true. The product sits squarely inside a lawyer-to-client fee relationship: the buyers named on the vendor's own pricing page include lawyers, law firms and corporate legal teams, and legal research is conventionally either billed as time or passed on as a disbursement in Indian practice.

Nothing states which. No per-matter record of AI-assisted work is described, nothing identifies output as AI-assisted for the purposes of a bill, no guidance on fee or disclosure treatment is published, and no saving is claimed in billable terms, the AI brochure's benefit language being about finding material that keyword search misses rather than about time recovered. Recorded and expressly not credited, because R21 and R24 govern and technology cost is a different object from AI-assisted work: the credit wallet is unusually granular about cost, publishing per-page and per-query credit rates for OCR, summarisation, translation, question-answering, timeline generation, comparison and drafting, a fixed credit value, and a dashboard showing top-ups, usage and balance.

That machinery would let a firm attribute AI cost to a matter with more precision than almost anything else in this corpus, and clause 3.9 of the agreement provides a detailed statement of transactional charges for verification. None of it is presented as a client-billing or disclosure instrument, and the vendor never makes the connection. The gap is a genuine one and the summary carries it.

Source: Vendor PublishedAs of Sep 13, 2026Evidence

Outside Counsel Guideline Readiness

Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?

Not addressed

No located public material supports a client side disclosure obligation.

None of the three artifacts this signal looks for exists, which is the floor, and the note explains why the floor understates what a firm could actually do with this vendor's paperwork. No subprocessor list is published anywhere. No model provider is named, the AI being described only as semantic AI and large language models trained on Indian data and built in India, so a firm asked which third party processes its uploaded documents could not answer from a list.

No consent or notification pack drafted to be forwarded to a client exists, and no data processing addendum is published as a separate instrument. Under R29 partial means some providers named across the product's AI, and none is named, so subprocessors-listed is unavailable; nothing is gated behind a request either, so on-request would be false. What a firm does have is a published, forwardable customer agreement that answers the underlying question in the negative and in strong terms.

Clause 5.5 bars the vendor from providing access to, disclosing or transferring Subscriber Content to any third party including affiliates, subcontractors, service providers, AI vendors, cloud providers or other users without prior express written consent, clause 4.3 says the same for Confidential Information, clause 5.2 bars training, and clause 4.7 requires deletion within 24 hours. On the question a client AI clause actually asks, that is a better answer than most subprocessor lists give.

It is not the artifact the signal names, and the value records the artifact. Recorded as the clearest instance in this pull of a vendor whose contract would satisfy a client where its disclosure estate would not.

Source: Vendor Publishedwithout the Subscriber's prior express written consentAs of Sep 13, 2026Evidence

Court Disclosure Support

If a judge’s standing order requires an AI disclosure, can the product produce one?

Not addressed

No located public material addresses court disclosure or verification certification.

Nothing published helps a lawyer disclose AI involvement to a court, which is the floor, and on this record that absence is more consequential than on most. Two adjacent features exist and neither is a disclosure instrument, so both are recorded and not credited. The AI brochure states that the right panel provides an AI-generated analysis of the query which the user can download or share, and that individual results can be emailed, printed or downloaded.

That is an export of AI output, but nothing states that an exported analysis is labelled as machine-generated, carries a timestamp, records the query that produced it, or is distinguishable from a manually compiled note once it leaves the platform. Clause 11.12 of the agreement requires that judgment text be verified against the certified copy, which is a verification duty rather than a disclosure mechanism and speaks to the accuracy of the source rather than to the involvement of the model.

What is absent is everything the higher values describe: no audit trail of AI use, no per-matter or per-query record a firm could produce, no certification template, no export designed to evidence machine involvement, and no guidance on when or how AI assistance should be disclosed. The consequence is concrete here in a way it is not for most products. The Supreme Court of India held in July 2026 that citing unverified AI-generated precedent is professional misconduct and that a decision resting on hallucinated material is no decision in law, so an Indian advocate may shortly need to evidence how a cited authority was found.

This platform produces AI-generated case analysis and provides no means of showing afterwards which words were the model's.

Source: Vendor Publishedmust be verified from the certified copy of the judgmentAs of Sep 13, 2026Evidence
Contact

Correct a record, or ask how something was graded

Every grade and every signal on this index is drawn from public sources and dated. If a record is wrong, out of date, or missing an artifact the index did not locate, send the source and it will be reviewed and the record redated. Vendors are welcome to submit documentation. Nothing on this index is for sale, including a listing, a placement, or a grade.

AI Legal Index

The AI Legal Index is an independent index that tracks changes to AI vendors in legal. It holds 61 vendors across 9 categories, each graded on the same 15 capability axes and recorded against 12 legal signals, from public sources. No vendor pays for inclusion, placement, or rating.

Index Status
Last index update
September 13, 2026
The AI Legal Index is an editorial reference. It is not a regulatory body, not a law firm, and nothing published here is legal advice or a recommendation to retain or avoid a vendor. Records are verified against published sources, bar guidance and public court records. Where a record reads not addressed, the material was not located in public sources on the date shown. See the Methodology page for evaluation standards and limitations.
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