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Leegality

Leegality is an Indian document execution and contract operations platform operated by Grey Swift Private Limited. It combines Aadhaar and other electronic signatures with digital stamping, internal approvals, a contract repository and obligation reminders. Its AI Review feature evaluates clauses against rules supplied by the customer's legal or compliance team, explains deviations and suggests alternative wording. Users can inspect the existing clause, replace it or dismiss the suggestion.

Obligations AI extracts commitments and assigns owners, while Smart Extraction populates metadata for legacy agreements uploaded in bulk. Teams work through the browser, a Microsoft Word extension or APIs connected to their business systems. Counterparties can review as guests or download and return edited drafts. The platform serves banks, lenders, insurers, stockbrokers, HR teams and other Indian businesses, with Rupifi providing a named contract management testimonial.

Leegality says contract storage and AI processing stay in India and contract data is not used to train models. Basic signing has transaction prices; AI contract operations require a separate commercial discussion. Founded in 2016, the company is based in Gurugram.

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.

CC on AI CentralityArtificial intelligence is present but peripheral: a feature layer on a product whose value stands without it.

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.

Leegality's original business is document execution, including Aadhaar signatures, stamp paper procurement, approval routing and delivery of completed agreements. Those services retain their purpose without generative models. AI Review adds clause analysis against rules defined by the legal or compliance team, explanations of deviations and suggested replacement language. Obligations AI extracts commitments and assigns their owners, while Smart Extraction fills repository metadata from uploaded agreements.

These are identifiable applications of AI to legal work rather than a relabeling of signature automation. They remain features within a broader paperwork platform whose commercial offering also includes document fraud prevention and electronic bank guarantees.

Source: Vendor Published
CC on Citation Accuracy and Hallucination DisclosureAccuracy is asserted without measurement, or grounding is claimed while output cites sources the reader cannot open and verify.

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.

The AI review interface ties a finding to a customer rule and the relevant contract clause. Its example distinguishes requirements that are met, not met or not found, and displays the current clause beside a suggested replacement. That gives a reviewer useful context for deciding whether a contractual requirement has been satisfied. It does not establish legal correctness beyond the supplied rules. No measured error rate, benchmark dataset or independent validation method accompanies the clause review feature.

Nor is there a described legal authority retrieval system that supplies primary cases or statutes and verifies their current status before a proposed revision is used.

Source: Vendor Published
AA on Autonomy and Oversight ModelWhat the system runs alone, what constrains it, and how a lawyer checks it are all published: modes, thresholds, review surfaces, and the route a matter takes back to human judgment. A categorical limit on a named mode or tier, stating what its output may not be used for, meets the threshold limb without a number.

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.

Legal and compliance teams define the rules that constrain AI Review, then inspect deviations and the reasons attached to them. The contract interface gives users separate actions to replace a clause or dismiss its proposed replacement. Leegality Reviewer adds a configurable approval gate: the sender assigns internal or external reviewers, who can approve or reject the agreement before it proceeds to the signer. Obligations AI separately uses configured obligation types, owners and email reminders.

These controls distinguish automated extraction from human contract approval. Their protection depends on configuring the reviewer step; AI analysis alone does not turn a proposed contract into an approved agreement.

Source: Vendor Published
BB on Operational and Outcome EvidenceReal deployment evidence with substance, short of full attribution or measurement: a named customer without figures, or figures without the named customer.

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.

Rupifi's in house counsel Satyanshu Mishra describes using Leegality's contract management product and its configuration options, with the vendor's support helping the team adopt the platform. That is a named legal user discussing the product rather than an unexplained customer logo. The broader execution business also reports IIFL Samasta increasing daily loans per branch from roughly 30 to 35 to roughly 40 to 45 after digitizing paperwork.

Those operational figures concern the signing process, not the accuracy or speed of AI clause review. The contract testimonial has no dated baseline, review sample or measurement isolating the contribution of the models.

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.

Contract data is covered by an express product commitment against use in training any AI model. Leegality also states that AI review and obligation extraction read the agreement without retaining another copy, while the repository continues to hold the underlying contract. Its privacy notice describes encryption, approved access on a need to know basis and processing of signer data on customer instructions. These protections give corporate legal teams a concrete confidentiality position.

They do not explain privilege preservation, separate law firm matters or the identity and contractual duties of the models underneath. Role restrictions on document execution are narrower than a documented ethical wall for AI answers.

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.

Leegality identifies itself as a software business rather than a law firm and addresses business, product, operations and legal teams. Its terms place responsibility for appropriate stamp duty, document enforceability and retention requirements on the customer. The service is framed around Indian law, and customers outside India are responsible for assessing local suitability. This gives a clear boundary around the provider's role in document execution.

The AI feature nevertheless describes clause replacements as compliant with the customer's rules without a corresponding account of professional competence duties. No bar specific supervision framework explains how a lawyer should validate those suggestions before advising a client.

Source: Vendor Published
DD on AI Governance and Bias DisclosureNo governance position published for a system whose output affects legal outcomes.

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.

Customer rule sets define what AI Review looks for in an agreement, but those rules are an application control rather than an account of how Leegality governs its models. There is no named AI governance owner, release testing program, bias assessment or report of differences in performance across languages and contract types. The platform's Indian language signing options and identity verification features do not answer those questions for clause interpretation.

Information security certifications address a different set of controls. A legal team therefore receives a configurable review workflow without a published mechanism for assessing systematic model errors or the vendor's response when those errors recur.

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.

The privacy notice separates account data from document and signer information processed on customer instructions. It describes encryption during transfer and storage, access approval, monitoring and audits. Uploaded agreements remain for a period determined by customer settings or legal requirements, and the pricing feature list includes automatic purging of signed files. Several service providers and their purposes are named, including the hosting company, signature authorities and electronic stamping services.

The AI product adds a commitment not to retain another document copy during processing. Missing pieces include named model subprocessors, a complete prompt and output retention schedule and a customer incident notification timetable.

Source: Vendor Published
CC on AI Liability and RecourseLiability is addressed only through a standard limitation clause that disclaims the exposure the product creates.

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.

Leegality's standard terms disclaim responsibility for the contents and enforceability of agreements and do not warrant that service results will be accurate or reliable. The liability formula is the greater of INR 100 or fees associated with executing a document, excluding specified expenses and charges, subject to an aggregate ceiling of INR 10,000 per user. Consequential and other indirect losses are excluded. The indemnity runs from the user to Leegality, with no corresponding published protection for an erroneous AI revision.

A separately signed agreement takes precedence, so enterprise buyers may have different provisions; the public terms themselves offer little recourse for faulty legal output.

Source: Vendor Published
BB on Practice Systems Integration DepthReal integrations exist and are documented, short of depth: named connections without a description of what they actually move.

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.

The Word extension has an explicit setup path through the Microsoft marketplace followed by a Leegality login. Users see assigned tasks in the sidebar, run rule based AI review and share agreements with counterparties from the editor. Guests can review online or download, edit and upload their version without creating an account. Outside Word, APIs connect document journeys to a customer's CRM, loan systems or HR software; webhooks return signed documents to customer servers.

These are described transfers and actions, not just integration logos. Permission mapping, version conflict handling and a complete implementation account for each connected business system remain unspecified.

Source: Vendor Published
AA on Deployment Model and Data ResidencyDeployment options and data residency are published, including the regions available, what changes between tiers, and where processing happens as distinct from where data is stored.

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.

Leegality operates a hosted platform accessed through its dashboard, Word extension or APIs. Both storage and processing of contract data are expressly restricted to servers in India, including AI review and obligation extraction. The privacy notice identifies Amazon Internet Services Private Limited as the hosting provider and likewise places personal data processing in India. There is no advertised alternative region for a customer to select, nor a published private installation offering.

The geographic commitment therefore covers the available service rather than a menu of deployment tiers. It does not identify the individual model service or give a detailed account of backup locations within the country.

Source: Vendor Published
BB on Security Certifications and Trust CenterCertification is real and stated, short of accessible evidence: a named standard without scope, date, or a way to obtain the report.

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.

The privacy notice names ISO 27001:2022, ISO 27017:2015 and ISO 27018:2019, alongside a SOC 2 Type II attestation covering security, availability and confidentiality. It describes recurring independent audits and separately refers to CERT IN empaneled auditors for Aadhaar and signature requirements. Leegality also provides a trust center entry point and offers its SOC report and auditor details on request. The public statements do not supply the attestation period, named auditor or an inspectable report establishing the full product scope.

The standards are more specific than generic security badges, but their existence does not by itself validate the quality of AI contract interpretation.

Source: Vendor Published
DD on Model Supply Chain DisclosureNothing published about the model supply chain a customer inherits.

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.

Neither the AI Review explainer nor the contract product description identifies the model family or inference provider used for clause analysis and obligation extraction. The privacy notice names the infrastructure host and several execution providers, but it does not distinguish an AI model service from general hosting. A commitment to processing in India and avoiding training on contracts addresses location and use of data, not the identity of the model supplier.

There is also no published model change notification procedure. Customers can understand the review workflow while still lacking the information needed to assess a particular foundation model or its replacement.

Source: Vendor Published
BB on Commercial TransparencyReal pricing is published for part of the range, with enterprise tiers withheld, or the unit and structure are stated without the figure.

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.

Basic execution has explicit transaction prices: INR 25 for each Aadhaar signatory and INR 15 for each non Aadhaar signatory. Digital stamping costs INR 45 per paper plus stamp duty and INR 500 per order, with a minimum of 30 papers; signing requires at least INR 100 of credits. The Basic account includes one user and one workflow. Advanced business features require a quote, and the advertised INR 300,000 annual budget dividing line is not an AI subscription price.

A first flow can be configured and tested free, but implementation charges beyond that and the cost or allowance for AI Review 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.

Leegality focuses on Indian business paperwork, with named uses in banking, lending, microfinance, stockbroking, insurance, human resources and procurement. Contract examples include vendor agreements, master services agreements, nondisclosure agreements, employment letters and loan documentation. Legal teams can define their own compliance rules while business colleagues initiate work, approve it or sign. The terms and privacy notice explicitly center Indian law and leave overseas suitability to the customer.

This is a clearer audience than a claim to serve every practice. It is not a published coverage map for litigation, specialist legal research or the full range of legal issues a generated clause might raise.

Source: Vendor Published
Sources on file

6 public documents

The public pages on file for Leegality, 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

INR 15 per non Aadhaar signatory; AI contract operations quoted

INR, as published, never converted
  • Leegality publishes execution charges but no standalone rate or usage allowance for AI Review and obligation extraction. Advanced business features require a quote that separates signature consumption, stamping, users, workflows and any contract management charges.

Basic signing uses prepaid transaction credits, with INR 100 minimum purchase. Aadhaar signatures cost INR 25 per signatory. Stamping adds INR 45 per paper, applicable duty and INR 500 per order, with a 30 paper minimum.

Implementation: The first document flow can be configured and tested free. Charges for broader implementation or AI rule setup are not stated.

Confidentiality and data terms: Not stated

Note: One user and one workflow are included in Basic. The INR 300,000 annual budget prompt distinguishes Basic from advanced business plans; it is not a published AI fee. Purchased eSign transactions expire after 365 days and standard terms deny refunds.

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?

Never, in policy only

A public policy or trust page states no training on customer content, with no matching term located in the published agreement.

Leegality promises that contract data used for AI review or obligation extraction is never used to train any AI model. That promise appears in its contract product explanation, rather than an express model training restriction in the standard terms. The incorporated privacy notice limits signer processing to customer instructions and permits analytics on usage information. It does not clearly grant a separate right to train on agreement content. The policy commitment consequently remains distinct from a negotiated contractual prohibition.

Source: Vendor Publishedyour contract data is never used to train any AI modelAs of Oct 16, 2026Evidence

Prompt and Output Retention

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

Customer controlled, no zero option

The customer controls the retention window, by product configuration or by contractual instruction, but zero retention is not stated as available.

Customers can control how long uploaded agreements are stored, subject to legal requirements, and automatic purging of signed files is an available feature. The AI workflow separately promises not to retain a copy of the contract it reads. Those statements do not establish zero retention for the whole account or every generated clause and processing log. The default schedule, backup removal period and exact treatment of prompts and outputs are not specified for the AI service.

Source: Vendor Publisheddepending on the settings enabled by the Leegality ClientAs of Oct 16, 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.

Execution roles restrict which team members can authorize documents, and the privacy notice describes access approvals based on need to know. Reviewers and approvers can also be assigned to a particular contract. These controls support differentiated access in a corporate workflow. They do not explain whether repository permissions are reapplied to every AI request, how separate clients are isolated, or how a lawyer excluded from one matter is prevented from receiving its content in an answer.

Source: Vendor PublishedSet access-based roles for your teamAs of Oct 16, 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.

The privacy notice allows disclosure when courts or other competent authorities legally require it. It supplies no corresponding promise to notify the affected customer before complying, contest an overbroad request or provide a recurring transparency report. General notices about privacy policy changes address a different event. The standard service terms also permit freezing transactions for regulatory obligations without prior intimation, so that provision does not supply an advance warning commitment for compelled access either.

Source: Vendor Publisheddisclose information when legally obligated to do soAs of Oct 16, 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?

Not addressed

No located public material identifies the corpus behind the product’s answers.

The defined inputs are customer contracts and compliance rules configured by the legal team. Leegality does not identify a legal research collection, enumerate its authority sources or explain licenses for statutes, judgments or commentary used by the underlying model. Its separate guides to Indian electronic signatures are educational resources, not a declared retrieval corpus for AI Review. A clause suggestion can follow the customer's rule without establishing the provenance of any additional legal knowledge used to generate it.

Source: Vendor PublishedAs of Oct 16, 2026Evidence

Good Law Verification

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

Not addressed

No located public material addresses whether authority is checked for subsequent history.

A contract can be tested against a rule about governing law or another requirement, but no citator or judicial treatment service is identified. The interface's met, not met and not found labels describe compliance with the supplied checklist. They do not certify that a case remains good law or that a statutory requirement has not changed. Changes in law therefore need to be reflected in the team's rules and separately validated before a review result is treated as current legal advice.

Source: Vendor PublishedAs of Oct 16, 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.

The review example labels a missing contractual requirement as not found and lets a reviewer dismiss suggested wording. That is useful handling of absent clauses, but it is not a model refusal policy. There is no described behavior for conflicting instructions, inadequate legal support, an unsupported jurisdiction or uncertain interpretation. Nor is a confidence measure accompanied by an escalation procedure for those circumstances. Human approval provides a workflow checkpoint while the model's response to insufficient knowledge remains unspecified.

Source: Vendor PublishedAs of Oct 16, 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.

The October 16, 2026 review of the Charlotin database found no entry naming Leegality in either the AI tool field or the remaining case information. The product's main legal output is contractual language and rule analysis, rather than a court submission built from cited authorities. That use profile may affect how an incident would appear in a litigation database. Absence of a named case is not a measured accuracy result and does not establish that fabricated legal assertions cannot occur.

Source: Operator VerifiedAs of Oct 16, 2026Evidence
Professional Responsibility

Bar Guidance Alignment

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

Not addressed

No located public material engages with bar or ethics guidance.

The company explains Indian signature and documentation requirements and makes its software role distinct from a law firm. It does not connect AI Review's controls to a named bar opinion or a jurisdiction specific framework for lawyers' competence, confidentiality and supervision obligations. Banking and data protection compliance materials address separate regulatory duties. Configurable review approvals can assist a legal team's process, but the vendor does not map those features to professional conduct guidance for use of generative AI.

Source: Vendor PublishedAs of Oct 16, 2026Evidence

Billing and Fee Posture

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

Outside the fee relationship

The product does not touch a fee between a lawyer and a client. It operates before an engagement exists, or it is bought by a team that bills no client for the work. Savings claims aimed at the buyer’s own cost are recorded in the summary and do not make the row a savings claim, because no client bill is in the loop.

The published commercial relationship is a business purchasing document execution and contract operations services. Pricing is based on signatures, stamp papers and quoted business features, rather than recording a lawyer's time or allocating an AI expense to a legal client. Leegality identifies business, product and operations teams as its usual buyers alongside legal teams. Its claimed paperwork savings concern corporate operating costs. No client billing ledger, disclosure template or law firm fee allocation workflow is described.

Source: Vendor Publishedour primary buyers are business, product, and ops teamsAs of Oct 16, 2026Evidence

Outside Counsel Guideline Readiness

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

Subprocessors listed

A current subprocessor or model provider list is published.

The privacy notice names Amazon Internet Services, signature providers including CDSL and Protean, SHCIL, NeSL and WhatsApp Business, with their processing purposes. Some other categories remain generic, including SMS, payment and email providers. That supplies part of a procurement disclosure package but omits the model provider for AI clause review. Leegality also offers an information security questionnaire and audit rights through its enterprise arrangements. No prepared outside counsel AI disclosure package or complete legal client approval form is published.

Source: Vendor PublishedBelow is a list of third-party service providersAs of Oct 16, 2026Evidence

Court Disclosure Support

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

Partial record

Some elements of the record are available, short of a document level export.

Executed agreements receive a secure audit trail recording the signing journey, and the contract interface preserves reviewers, remarks and recent activity. Those records may help explain who approved or signed an agreement. They do not amount to an export showing which model generated a clause, the prompt used or how counsel verified the output. Leegality promotes the signing record for court use, but no separate AI use declaration or complete model provenance export is described for a filing.

Source: Vendor PublishedGet court-admissible Secure Audit Trail for each contractAs of Oct 16, 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 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 16, 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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