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Manupatra

Manupatra is an Indian legal research platform, founded in 2000. Its database covers Indian case law from the Supreme Court, all High Courts and all tribunals, plus statutes, regulations, commentary and material from Commonwealth countries. It reports more than 10 million indexed documents and over 150,000 active users. Blue, yellow and red flags show whether a judgment or statute is still good law. AI Search, launched in December 2025, finds judgments by legal concept.

It returns the ten most relevant cases broken into facts, issues, arguments, reasoning, ratio and summary, each linked to its source. AI Summary summarizes judgments and AI Compare sets them side by side. A separate toolkit, ManuWorks, offers OCR, summaries, translation, document questions, case timelines, comparison and drafting. AI use is paid for through a published credit wallet. Manupatra Information Solutions Pvt. Ltd. is led by founder Deepak Kapoor and based in Noida, with offices in India and Bangladesh.

Compared with

Manupatra, head to head

Side by side on the same 15 capability axes and 12 legal signals: where the two part company, and what neither one publishes.

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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.

A substantial, named AI layer sits on a Manupatra research platform that ran for 25 years without it. AI Search launched in December 2025, is described as powered by semantic AI and large language models, and finds judgments by legal concept rather than keyword. AI Summary summarizes judgments and AI Compare sets them side by side. The ManuWorks toolkit adds OCR, summaries, translation, document questions, case timelines, comparison and drafting, each with its own credit rate.

The site is headlined India's trusted Legal Research partner, Powered by AI. Manupatra still treats AI as one search mode among several. It tells users to use MANU SEARCH, LEGAL SEARCH and CITATION SEARCH for exact or Boolean queries and keeps AI Search for queries by meaning. The AI is paid for separately through a credit wallet, so a subscriber can use the platform without it. The core asset is the edited corpus and its citation and treatment links, which predate the models.

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.

Manupatra grounds its AI in its own edited corpus and shows where it is weak, but publishes no accuracy figure. Its AI brochure says AI Search runs on a proprietary, edited corpus rather than public web data. Results come as the ten most relevant judgments, broken into Facts, Issues, Arguments, Reasoning, Ratio and Summary. Hovering on Reference confirms the source, and clicking Citation opens the full judgment. The platform also flags overruled, distinguished and conflicting judgments, with blue, yellow and red flags for whether authority is still good.

The brochure claims the edited base eliminates AI hallucinations. That claim sits alongside real controls. Manupatra also publishes where AI Search is weak. A section titled When NOT to Use AI Search warns against exact queries, party names, citations, exact statutory wording and verbatim quotes, and routes them to MANU SEARCH, LEGAL SEARCH and CITATION SEARCH. Another page gives nine examples of well and poorly framed queries.

What is missing is measurement. No accuracy figure, test set, error rate or evaluation is published for AI Search, AI Summary or AI Compare, and nothing backs the claim that hallucinations are eliminated. Nothing says the system reports when it finds no support. It always returns ten results, so whether the tenth is relevant or merely nearest is unanswered. Clause 11.12 of the agreement says judgment text is computer generated and must be checked against the certified copy. Clauses 15.1 to 15.3 disclaim accuracy and put checks on the user.

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.

Clear guidance covers when not to use the AI, but Manupatra sets no thresholds or review step. Its AI brochure has a section titled When NOT to Use AI Search. It tells users to avoid AI Search for exact or literal queries, party names, case citations, exact statutory wording and verbatim quotes. It says AI Search does not follow Boolean logic and sends those queries to MANU SEARCH, LEGAL SEARCH and CITATION SEARCH. Users can check sources: hovering on Reference confirms the source, clicking Citation opens the full judgment, and a chatbot handles follow up questions.

The agreement backs this up. Clause 15.3 makes the user responsible for checks, and clause 11.12 requires verification against the certified copy. What is missing: no confidence score, no threshold, nothing on what the system does with a query it handles poorly, and no review step before output. Nothing covers oversight of the ManuWorks AI Drafter, which writes legal drafts at 50 credits a query. The published limit says which queries suit AI Search, not what its output may not be used for.

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 by Manupatra, with no customer named and no outcome measured. It reports more than 150,000 active users, more than 10 million documents and judgments, 25 years in operation, a team of more than 175, and offices in India and Bangladesh. Its About page lists five kinds of client: legal professionals and firms, in house legal teams at companies and banks, academic institutions, government and regulators, and students and researchers across Asia.

Categories are not customers. No law firm, company, court, tribunal or university is named, and there is no client list, case study, testimonial or logo. No outcome is measured: nothing on time saved, research hours or accuracy, and the AI brochure's benefits describe features rather than results. The 150,000 figure has no date or source and appears as a counter on the product page and in the About page metadata.

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.

Manupatra's agreement makes precise confidentiality commitments, but never mentions privilege. Clause 4.1 defines Confidential Information to include documents, data, personal data, case files, names, facts, legal strategies and client information uploaded through the site, the AI tools or any related service. Clause 4.2 requires it to be kept strictly confidential and used only to provide the service requested. It may not be copied, stored, analyzed, mined or shared for any other purpose, and only staff who need it, under equal duties, may access it.

Clause 4.3 bars disclosure to any third party, including affiliates, subcontractors, AI engines and cloud providers, without express written consent. Clause 4.7 requires permanent deletion of all such information, including copies, backups, AI memory, logs and caches, right after the request is met and within 24 hours. Written certification is available on request. Clause 5.8 bars staff from viewing Subscriber Content or AI outputs except to fix a technical issue the Subscriber raised, with access logged and kept to a minimum.

Clause 4.8 makes these duties survive termination indefinitely. Training requires consent. What is missing is privilege. Neither privilege, professional secrecy nor work product is named, and nothing covers privileged material if disclosure is compelled. Listing case files and legal strategies comes close, but is not the same.

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. Where the advice line is not the duty a product raises, the axis is read through the nearest professional duty it does raise: judicial conduct rules and the reviewing duty for products sold only to courts, and the duty to bill for time actually spent for products that draft time entries.

Legal advice is plainly disclaimed in Manupatra's agreement, which puts the duty to check output on the user but engages with no conduct rule. Clause 16.1, headed No Legal Advice, says material on the site is not legal advice and creates no relationship of client and advocate. The disclaimer on the legal page says Manupatra does not warrant its forms and creates no relationship of lawyer and client by providing them.

It adds that forms are a guide to be adapted at the user's own risk. Clause 15.3 makes the user responsible for checks on the accuracy of input and output. Clause 11.12 requires users to verify judgment text against the certified copy, a duty rather than a disclaimer. What is missing: no conduct rule is named, Bar Council of India guidance is not mentioned, and nothing asks subscribers to use the product consistently with their professional duties.

The gap is sharp here. In July 2026 the Supreme Court of India held that citing unverified AI generated precedent is professional misconduct and directed India's Bar Council to frame norms. Manupatra publishes that ruling as news on its own updates service, but says nothing about what its AI features mean for that duty.

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 behavior: who owns it inside the vendor, what is tested before release, and what is disclosed about disparate output across matter types, parties, or populations.

Responsible AI gets one paragraph from Manupatra and nothing behind it. The legal page's Use of AI section says Manupatra uses AI responsibly. It lists data privacy, bias mitigation, transparency, human oversight, accountability, user consent and regulatory collaboration as priorities, to maximize benefits and minimize risks. That is the whole of it. No framework is adopted, no owner or committee is named, no governance process or bias testing is described, and no results are published.

Nothing says how human oversight works, beyond guidance to users. Bias is named as a priority and never returned to, on a product that ranks and summarizes court decisions, where a tilt in which precedents surface would be invisible to the user. The AI section of the agreement is a strong data handling commitment, but the responsible AI paragraph is not tied to it. The Grievance Redressal Officer named on the same page is a statutory appointment under India's IT Act for complaints, not an AI owner.

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.

Most of the ground is covered in specific terms by Manupatra's agreement, which names no subprocessors. Clause 4.4 requires industry standard technical and organizational security. Clause 4.5 commits to written notice within 24 hours of any actual or suspected unauthorized access, loss or breach, with full details and impact. Manupatra must also contain, investigate and fix it at its own cost, and cooperate in any legal or regulatory action.

Clause 4.6 makes Manupatra the 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 any storage to be temporary, encrypted and deleted after use. The privacy policy adds encryption, secure servers and firewalls, access controls, and staff confidentiality agreements and training, all regularly reviewed, and states compliance with the SPDI Rules 2011.

No processor is named. Clause 4.3 bars disclosure to any third party, including subcontractors, AI engines and cloud providers, without express written consent. But the privacy policy says third parties handle payments, email and hosting, and that products may connect to Dropbox and Google Drive, so processors exist and none is named. No certification backs any of this.

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.

Warranty, liability and indemnity are covered in detail in the agreement, and the balance favors Manupatra. Clauses 25.1 and 25.2 provide the information as is and disclaim all warranties, including merchantability, fitness for purpose and noninfringement. Clauses 15.1 and 15.2 disclaim any promise that the service will be correct, accurate, reliable, uninterrupted or timely. Clauses 25.3 and 25.4 exclude liability in contract or tort for any loss linked to the service, even where caused by Manupatra's own negligence.

Clause 25.5(i) excludes liability for any claim about the subscriber's failure to do legal research properly, or any decision made in reliance on the Data. Clause 26.1 caps liability at the charges paid in the subscription period, but it is drafted for copyright claims on the data, not as a general cap. The agreement also runs the other way. Clauses 21.2 and 26.3 require Manupatra to indemnify and defend the Subscriber, its clients, staff and affiliates.

That covers breach of confidentiality, misuse of Subscriber Content, unauthorized access or data breach, negligence, willful misconduct or breach of law by Manupatra, and intellectual property infringement. Clause 5.9 adds immediate termination, indemnity and injunctive relief for misuse of Subscriber Content, and clause 12.1 a prorated refund. Insurance is not addressed.

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.

A few integrations are named among those claimed, with no catalog and no setup detail. There is no integrations page. A Plug In menu item leads to ManupatraAlert, an alert plugin on manupatrafast.com. The privacy policy says products may connect to third party services, including data visualization and cloud storage such as Dropbox and Google Drive, for uploading and sharing documents. The wider suite, including the Mykase practice management product, Manucomply and Manucontract, suggests links to the research platform.

But each sells on its own domain with its own login, and nothing describes data moving between them. No practice management, document management or CRM system used by Indian firms is named. No public API, developer documentation or authentication model is published. No data flow, prerequisite or setup step is described for any connection. Nothing says whether AI Search or ManuWorks can be used from inside another application.

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.

Personal data stays in the user's country under a Manupatra commitment, but tenancy goes undescribed. The privacy policy's Data Localization section says all personal information is stored and processed on servers in the user's country of residence. Where a jurisdiction requires localization, data stays within its borders and is not moved abroad except as the law allows, with safeguards. The About page calls Manupatra a cloud first platform, and the AI brochure says the models are trained on Indian data and built in India.

There are limits. The localization promise covers personal information, but Subscriber Content uploaded to the AI tools is governed by confidentiality terms that do not say where it is processed. No tenancy model is described, so nothing says whether uploaded documents sit in a shared or isolated environment. No data center, region or cloud provider is named, no on premises or private option is offered or refused, and nothing separates storage from processing for the AI features.

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 security certification or trust center appears for Manupatra. The navigation and footer have no security, trust or compliance page and no certification badge. The footer's Company links are 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 other standard is claimed, no auditor is named, and no certificate or penetration test summary is offered.

Public reporting shows no certification claim by Manupatra either. This describes what is published, not Manupatra's actual security. The privacy policy lists encryption, secure servers and firewalls, access controls, and staff confidentiality agreements and training, all regularly reviewed. Clause 4.4 of the agreement commits to industry standard technical and organizational measures. Manupatra states compliance with the Information Technology Act 2000, the SPDI Rules 2011 and the Digital Personal Data Protection Act 2023, and names a Grievance Redressal Officer. A statement of legal compliance is not an independent audit.

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.

Large language models trained on Indian data power the AI, Manupatra says, but no model or provider is named. The AI brochure and the December 2025 launch material say AI Search is powered by semantic AI and large language models. The brochure says it is trained on Indian data, built in India, and runs on a proprietary legal knowledge base developed over decades rather than generic AI trained on public data. That says what the models use and where the work was done.

It does not name a model, version or provider, so nothing shows whether the models are Manupatra's own, licensed, or a third party service. Built in India describes the product, not the model. Nothing says where inference runs, no commitment to notify subscribers of model changes is published, and there is no subprocessor list. Clause 5.5 of the agreement bars sharing Subscriber Content with third parties, expressly including AI vendors and cloud providers, without written consent. That assumes such vendors exist but names none.

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.

Manupatra publishes AI prices, units and terms, so a buyer can plan costs without a sales call. The AI Solutions page has an open price table. Unlimited AI Summary costs 5,000 rupees a year for Supreme Court judgments, 5,000 rupees for High Court judgments, or 10,000 rupees for both, before GST. AI wallet plans for AI Search, AI Compare and AI Summary are 1,000 credits for 6,000 rupees, 1,500 for 9,000 and 2,000 for 12,000.

The ManuWorks toolkit publishes credit costs per action: 15 a page for OCR, 3 a page for summaries, 20 a page for translation, 5 a query for document questions, 8 a page for timelines, 15 a document for comparison and 50 a query for drafting. One credit is worth 1.25 rupees. The first purchase must be at least 10,000 rupees and each later purchase at least 5,000. Activation is prorated, and a dashboard shows credits bought, used and left.

The agreement sets the terms: payment in advance, no refunds, renewal and deactivation rules, price changes only from the next renewal, seven days to dispute transaction charges, and taxes on top. Two limits. The research subscription itself is not priced publicly, and the agreement says its price card is available on request. Clause 3.9 also implies a usage metered tier whose rates are not published.

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 set out by jurisdiction, content and buyer, with no limits stated by Manupatra. It covers Indian case law from the Supreme Court, all High Courts and all tribunals. It adds statutes, regulations, notifications, reports, commentary and secondary sources across Indian jurisdictions and Commonwealth countries. It has a coverage page, reports more than 10 million documents, and adds new material daily. A separate Bangladesh database, BDlex, is sold alongside.

The AI pricing page names students, lawyers, law firms and corporate legal teams as buyers. The About page lists practitioners, in house legal teams at companies and banks, academic institutions, government and regulators, and students and researchers across Asia. As a general case law database, it is not packaged by practice area. No limit is stated. Nothing names an out of scope court, tribunal or content type, the earliest coverage date or any gaps, or which Commonwealth countries are included. Nothing says whether the AI features cover the whole corpus, though AI Search is described in terms of judgments only.

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

INR, as published, never converted
  • You can work out what Manupatra's AI will cost before you talk 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, spent across AI Search, AI Compare and AI Summary.
  • Manupatra publishes what each action costs in credits, so you can estimate a real workload. Text recognition on a scanned document is 15 credits a page, summarizing is 3 a page, translating is 20 a page, a question about a document is 5, a case timeline is 8 a page, comparing two documents is 15, and an AI draft is 50. A credit is worth ₹1.25. The first purchase of toolkit credits must be at least ₹10,000, and later purchases at least ₹5,000. A dashboard shows what you have bought, used and have left, and activation is prorated if you join mid term.
  • Two things to watch. Credits expire with your subscription and do not carry into a renewal. And these prices cover the AI only. The research subscription's own price is not published, so you will need to ask for that price card.

Published figures with a published unit of charge, in Indian rupees, before GST. Two structures run side by side. A flat annual AI Summary tier: unlimited Supreme Court judgment summaries at ₹5,000 a year, High Court at ₹5,000 a year, and both at ₹10,000 a year. A credit based AI wallet for AI Search, AI Compare and AI Summary: 1,000 credits at ₹6,000, 1,500 at ₹9,000 and 2,000 at ₹12,000. Credits are valid only for the current subscription and do not carry forward at renewal.

The ManuWorks toolkit uses the same credits with a published rate card: OCR 15 credits a page, summarization 3 a page, translation 20 a page, document questions 5 a query, case timelines 8 a page, document comparison 15 a document, and AI drafting 50 a query. One credit equals ₹1.25, with a minimum first purchase of ₹10,000 and a minimum later purchase of ₹5,000, before GST. Activation is prorated within a subscription period, and a dashboard reports credits bought, used and left.

The subscriber agreement sets the terms. Fees are paid in advance and are not refundable. Access ends at expiry, with a discretionary 15 day grace period on assurance of payment. Manupatra may change charges from the next renewal term. Transaction charges must be disputed within seven days or are deemed accepted, and taxes are extra. The research subscription's own price is not published, and the agreement says the 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 center 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 are on Manupatra's open AI Solutions page, and commercial terms are in the published subscriber agreement PDF. The entry price is the lowest published annual price, 5,000 rupees a year for unlimited AI Summary of Supreme Court judgments, before GST, shown in Indian rupees as published. Two limits. The published prices are for the AI layer. The research subscription leads to a plans page, and clause 3.1.3 of the agreement says its price card is available on request. Clause 3.9 also mentions Transactional Pricing with a detailed statement of usage charges, which implies a metered content tier whose rates are not published.

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 on subscriber data is barred by default and allowed only with the subscriber's express written consent. Clause 5.2 of the agreement, headed Absolute Prohibition on AI Training and Internal Use, bars using Subscriber Content in any form for training, fine tuning or improving any AI or machine learning model. That covers whole or partial, anonymized, pseudonymized, aggregated or derived content. It also bars use for building algorithms, features or products, internal analytics, database enrichment, quality work, troubleshooting, research, teaching, demos or testing.

Anonymized and aggregated use, a common exception, is closed here. Clause 5.7 requires prior express written consent in a standalone written agreement for any training or improvement use, and says silence or continued use is not consent. Clause 14.3.1 repeats the ban, and clause 5.9 makes a breach material, with indemnity and injunctive relief. The agreement does not promise never to train. It promises not to train without a separate signed permission the subscriber may refuse at its sole discretion. The privacy policy states the same rule in weaker terms for user data generally.

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.

Manupatra's agreement sets a fixed maximum: 24 hours. Clause 4.7, headed No Retention / Mandatory Deletion, requires permanent deletion of all uploaded Confidential Information, including copies, backups, AI memory, logs, caches and traces. Deletion must happen right after the request is met and no later than 24 hours after use. Written certification of deletion is available on request. Naming AI memory, logs and caches matters, because those are where data usually survives a deletion promise.

Clause 5.3 bars storing or caching Subscriber Content beyond what is strictly needed to produce the output, and all storage must be temporary, encrypted and deleted right after use. Clause 5.6 treats AI outputs containing or derived from Subscriber Content as the subscriber's confidential information, not to be stored, reused or shared. Two limits. The 24 hour rule covers uploaded Subscriber Content, not the text of a research search or the account and usage data the privacy policy describes collecting.

And the privacy policy's own retention section only promises to keep personal information as long as necessary, and refers readers to 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.

Manupatra commits to access control in its contract but describes no separation model. What is documented is access on Manupatra's side. Clause 4.2(d) limits access to staff who need it and are bound by equal confidentiality duties. Clause 5.8, headed Monitoring / Human Review, bars staff from viewing Subscriber Content or AI outputs except to fix a technical issue the subscriber raised, with access logged and kept to a minimum.

User access rules exist too. Clause 11.10 requires IP based and remote access subscribers to list named Authorized Users before the subscription starts. Clause 3.5 makes the subscriber liable for all actions under its login and allows termination for password sharing. Clause 3.6 makes an organization responsible for its users, and clause 2.3 limits display to one person at a time on plans not based on IP. What is not addressed is separation between matters, clients or users within a firm.

No permission model, role model or ethical wall is described, and nothing says whether documents one user uploads to ManuWorks can be reached by a colleague on the same subscription. A shared research database has no matters, but the AI toolkit takes uploaded case documents, and that is 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.

Data may be disclosed when compelled, Manupatra says, with nothing about telling the customer. The privacy policy says personal data may be disclosed where required by law, court order or government regulation, in a merger, acquisition or similar deal, or to protect rights, property or safety. Nothing says the subscriber would be told of a demand, given a chance to object, or told afterward. There is no transparency report or law enforcement guidelines page.

The two documents conflict. The customer agreement is more protective and has no exception for compelled disclosure. Clause 4.3 says Manupatra will not disclose Confidential Information to any third party without the subscriber's prior express written consent, and clause 5.5 says the same for Subscriber Content. Read literally, that allows no exception for a court order, which cannot be the intent, and no clause reconciles it.

The agreement governs where the two conflict, but its silence on legal process is not a promise of notice. So Manupatra has said what it may disclose under compulsion, in its weaker document, and nothing 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 license or public domain basis for each, with an update cadence.

Sources are identified, and the agreement states the licensing basis for third party material. Clause 10.2 says some information belongs to content providers, is marked as such, and is licensed to Manupatra to store, catalog and distribute to subscribers, with no rights passing to the user. The Public Record section of the legal page says public records come from courts and government agencies. Manupatra collects them from established government and judicial sources, in some cases under agreements whose terms may be stricter than the law.

The copyright section says third party content is reproduced with prior permission and its copyright retained. The AI brochure grounds the models in Manupatra's own edited corpus, built over decades from citations, judicial treatment and summaries, which it owns. So a buyer can see the types of source and how each is held. Not published: a list of suppliers, any license term or duration, or whether the licenses cover AI processing as well as distribution. That matters for 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.

Treatment flags come from a system of Manupatra's own rather than a licensed one. The product page section titled Be sure you are using Good Law says effective date highlights and blue, yellow and red flags mark whether each statute and judgment is good law. That flag scheme, on both statutes and judgments, works as a citator and is Manupatra's own. Nothing suggests any part is licensed, and the AI brochure describes the treatment data as part of the edited corpus built over decades.

The AI uses it. The brochure says AI Search lets a user see whether a judgment has been overruled, distinguished or followed, find conflicting judgments, and trace how courts have read a statute over time. The product page lists authority checks and citation maps among its analytics. Two limits. No method says how treatment is decided, whether by the advocates who edit the corpus or by software, and nothing says which courts, years or content types carry flags. Nothing says what a flag means in borderline cases or how fast a new adverse judgment updates the flag.

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

Refusal and Uncertainty Behavior

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.

When the system cannot give a reliable answer, nothing says what it does, though Manupatra gives useful guidance on where the tool is weak. Its AI brochure section titled When NOT to Use AI Search tells users to avoid it for exact queries, party names, citations, exact statutory wording and verbatim quotes. It says AI Search does not follow Boolean logic, and routes those queries to MANU SEARCH, LEGAL SEARCH and CITATION SEARCH.

Another page shows how to frame a good query, with good and poor examples. All of that is about what the user should do before a query, not what the system does after one. Nothing says AI Search declines a query, flags low confidence, marks an uncertain result for checking, returns fewer than ten results when fewer are relevant, or says it found nothing. It always returns a ranked ten, so whether the tenth result is relevant or merely nearest is unanswered.

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.

No decision, order or tribunal finding names Manupatra or Manupatra AI Search as the source of a fabricated citation, in reporting and trackers of Indian decisions on fabricated citations produced with AI, including the Supreme Court of India's July 2026 ruling and the 2026 cases before it. India has an active record on this. A Supreme Court bench set aside National Company Law Tribunal and appellate orders that rested on citations that do not exist, and held that citing unverified AI generated precedent is professional misconduct.

It directed India's Bar Council to frame norms. Earlier cases include a Bengaluru tax tribunal order recalled over four citations that do not exist and a Bombay High Court assessment quashed over three invented precedents. In the commentary that followed, Manupatra is named often as one of the authorized databases for checking citations. This record covers fabricated legal citations in filings only, so other litigation or regulatory history 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 comes up in general terms, with no guidance named. Clause 16.1 of the agreement, headed No Legal Advice, says material on the site is not legal advice and creates no relationship of client and advocate. The legal page's disclaimer repeats this for forms. Clause 11.12 requires judgment text to be verified against the certified copy, and clause 15.3 makes the user responsible for checks. No bar body, conduct rule or ethics opinion is cited, Bar Council of India guidance is not mentioned, and nothing maps any AI feature to a professional duty.

The gap is sharp. In July 2026 the Supreme Court of India held that citing unverified AI generated precedent is professional misconduct. It directed India's Bar Council to form a committee to frame norms, with draft rules on AI in courts out for consultation. Manupatra publishes that ruling as news on its own legal updates service. It says nothing linking AI Search, AI Summary or the AI Drafter to the verification duty that ruling places on each lawyer.

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.

What happens to the bill when AI cuts the time a task takes goes unaddressed by Manupatra. The product sits inside the fee relationship. Its pricing page names lawyers, law firms and corporate legal teams as buyers, and in Indian practice research is usually billed as time or passed on as a cost. Nothing says which applies. No per matter record of AI work is described, nothing marks output as AI assisted for billing, no guidance on fees or disclosure is published, and no saving is claimed in billable terms.

The AI brochure's benefits are about finding what keyword search misses, not time saved. The credit wallet is very detailed about cost, with per page and per query rates, a fixed credit value and a dashboard of credits bought, used and left. That could let a firm assign AI cost to a matter, and clause 3.9 gives a detailed statement of transaction charges. But that is technology cost, not AI assisted work, and Manupatra never presents it as a billing or disclosure tool.

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 items a firm would forward is available from Manupatra: no subprocessor list, no named model provider, and no client facing consent or notice pack. The AI is described only as semantic AI and large language models trained on Indian data and built in India. A firm asked who processes its uploaded documents could not answer from a list. No data processing addendum is published separately, and nothing is offered on request.

What a firm does have is a published customer agreement it can forward, which answers the core question firmly. Clause 5.5 bars Manupatra from giving access to, disclosing or transferring Subscriber Content to any third party without express written consent. That includes affiliates, subcontractors, service providers, AI vendors, cloud providers and other users. 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's AI clause asks, that is a strong answer. It is still not a subprocessor list or provider statement, which is what a firm's guidelines usually ask for.

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.

Manupatra publishes nothing that helps a lawyer disclose AI involvement to a court, and the gap matters here. Two related features exist, and neither is a disclosure tool. The AI brochure says the right panel gives an AI generated analysis of the query that can be downloaded or shared, and results can be emailed, printed or downloaded. But nothing says an exported analysis is labeled as machine generated, carries a timestamp, records the query, or can be told apart from a manual note once it leaves the platform.

Clause 11.12 requires judgment text to be checked against the certified copy, which concerns the accuracy of the source, not the model's involvement. There is no audit trail of AI use, no per matter or per query record, no certification template, no export built to show machine involvement, and no guidance on when to disclose AI help. In July 2026 the Supreme Court of India held that citing unverified AI generated precedent is professional misconduct, and that a decision resting on hallucinated material is no decision in law.

Indian advocates may soon need to show how a cited authority was found. This platform produces AI case analysis and gives no way to show later which words were the model's.

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

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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 462 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
October 21, 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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