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Lawdify
Lawdify turns a dispute's mixed evidence into case context for analysis and drafting. Its Case Brain organizes parties, dates and issues, while the Lawri assistant uses that information to answer questions and prepare work. Expertise Engineering creates reusable skills from a team's own material, and Smart Tables track details as the case develops.
The legal workspace handles email archives, spreadsheets, handwritten files and APAC messaging formats including WhatsApp, WeChat and KakaoTalk. Evidence Check tests whether material supports a proposition. Assisted Drafting uses the team's precedents and style, with tracked edits in Microsoft Word. Outlook and Excel connections bring case information into correspondence and spreadsheet tasks, and email instructions can start agents without opening the main workspace.
Founded in Singapore in 2023, the company serves law firms, internal legal teams and construction claims specialists. A separate insurance product handles claims assessment. Its legal service combines evidence preparation with ongoing dispute work rather than concentrating solely on a finished pleading. Customer data is hosted in Singapore by default, with other regional arrangements available. The terms prohibit model training on client material and require professional evaluation of generated output.
Lawdify, 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.
- CLawdify vs CaseCreateLitigation & eDiscovery
- ELawdify vs EverlawLitigation & eDiscovery
- LLawdify vs LighthouseLitigation & eDiscovery
- LLawdify vs Litmas AILitigation & eDiscovery
- MLawdify vs Merlin Search TechnologiesLitigation & eDiscovery
- RLawdify vs RelativityLitigation & eDiscovery
- RLawdify vs RevealLitigation & eDiscovery
Alternatives to Lawdify
Vendors in the same categories as Lawdify whose graded profiles look most alike, with a line on what each product does.
Similar is not the same, so check that each one does the job you need. No vendor pays for placement.
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- DDecoverAIDecoverAI is an ediscovery platform that takes a document set from upload to court ready production.
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Ordered by how closely the graded profiles match across the 15 capability axes, inside the same categories. See how each axis is graded in the methodology.
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.
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.
Lawdify is built around AI interpretation of evidence and the work that follows from it. Case Brain organizes parties, dates and issues from uploaded material, while Lawri uses that context to answer questions and prepare drafts. Expertise Engineering turns the team's own methods into reusable skills, and Smart Tables run specialized tasks as the dispute develops. Email instructions can start several agents and return their results to the sender.
These functions depend on models understanding and generating content, rather than adding a conversational feature to an older records system. File storage and exports support the service, but the case intelligence is the product being sold.
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.
Evidence Check is designed to test whether a proposition has supporting material in the case file. Lawri can inspect case context, and the research interface presents authorities with relevance and application descriptions. The legal product also offers factual checking and argument strength assessment. Its visible examples do not establish a reproducible accuracy test, a citation status check or a consistent route from every generated assertion to an open source passage.
The terms describe output as probabilistic and place evaluation with the user. These are useful verification intentions and review functions, with the detailed grounding method and measured failure behavior still unspecified.
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.
The legal workflow gives the lawyer a first draft and a visible editing surface. In Word, proposed revisions appear with track changes so the user can review and accept individual edits. The terms also require evaluating probabilistic output for the intended use, including expert human review. Email agents can process attachments and reply with results, while specialized skills automate steps in case preparation. The distinction between a draft and professional judgment is therefore supported by an actual review mechanism.
A threshold that stops an agent, a mandatory approval before consequential action and a recovery route after an incorrect result are not specified.
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.
Lawdify identifies deployed use as well as product demonstrations. Its September 2026 account describes Zurich Insurance Malaysia moving from a three month proof of concept into a multiyear deployment. That is a named operational relationship in the insurance business, rather than a measured result for every legal workflow. The legal service also presents customer experience around evidence organization and case preparation.
The broader claims about faster settlements, reduced loss ratios and fraud detection are not accompanied by a method tying each figure to a named deployment. The available customer evidence supports practical use without establishing a reproducible estimate of legal team productivity.
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.
The February 2026 terms expressly exclude customer documents, legal files and case materials from model training and product improvement. They distinguish that material from anonymized, aggregated operational usage metrics. Customer information is subject to confidentiality obligations, and the hosting provisions describe logical separation between customer environments. Deletion after termination includes backups and a certificate with logs.
These are explicit commitments for material entrusted to the service. The confidentiality section also uses pilot terminology, while specific treatment of legal privilege, internal matter walls and retention by individual model providers remains unclear. The promise covers more than a general assurance that information is secure.
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.
Lawdify's legal workspace is aimed at law firms and internal legal teams handling contentious work. Its terms distinguish the application from legal advice and say that it does not create a lawyer and client relationship. The AI output provision describes generated content as probabilistic and calls for evaluation appropriate to the use case, including expert human review. Word editing and evidence checks support that professional review in the product.
The legal service also reaches construction claims teams and other specialists. A jurisdiction by jurisdiction account of permitted professional use, competence obligations and limits for people who are not lawyers is not provided.
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.
Lawdify identifies an AI Governance Framework and a prompt injection testing report in its trust center. Access to those materials requires a request, so their detailed controls and results are not available in the open view. The privacy policy recognizes a right to human review of certain automated decisions where applicable, and the service makes commitments about customer data use and human evaluation of output. These establish elements of a responsible AI position.
They do not reveal who owns model governance, what release testing covers or whether uneven performance across languages and legal settings has been measured. The restricted framework's contents remain unknown.
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 service combines encryption in storage and transit with authentication, access logging and logical separation of customer environments. Its terms set deletion procedures for removed material and terminated accounts, including a deletion certificate and associated logs after service exit. A trust center names cloud and supporting service providers, while the privacy policy describes security monitoring, backups and incident response procedures.
These provisions address how client material is handled beyond ordinary website privacy. The incident section does not set a customer notification timetable or describe the response workflow in detail, and the complete path through underlying AI providers is not mapped for each processing operation.
AI Liability and Recourse
What the vendor stands behind contractually when its output is wrong. Indemnities, caps, carve outs, insurance, and whether any of it is published or only reachable through a negotiated agreement.
The terms exclude warranties of accurate or reliable output and place professional evaluation with the user. They limit consequential losses and require the customer to defend Lawdify against several categories of claim arising from use or breach. The liability limitation contains exceptions for matters including fraud, intellectual property and confidentiality obligations, but its cap is internally inconsistent: the written amount corresponds to $100 while the parenthetical figure is $10.
A specific promise to defend the customer against an AI output claim is not included. The result is a conventional allocation of risk away from the supplier, with an unresolved ambiguity in the stated monetary limit.
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.
Lawdify connects its case information to Microsoft Word, Outlook and Excel. The Excel application has a concrete setup path: sign in to a Lawdify account using email verification, select a case or matter, then use the chat panel or custom functions. LAWDIFY.ASK returns an answer in a cell, while LAWDIFY.EXTRACT pulls information from case material into the spreadsheet. The application can read and change the workbook and send information over the internet.
A Lawdify subscription is required. This describes both the movement of case information into an existing work surface and the configuration needed to use it, beyond a list of compatible applications.
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.
Customer data is hosted in Singapore by default, with other jurisdictions available by arrangement where the cloud infrastructure supports them. The security offering describes regional support across Asia, the European Union and the United States. The terms also describe logical separation of customer environments, and the current certification scope identifies the legal platform on Azure and Google Cloud Platform. These details make the default hosting location and the existence of regional alternatives concrete.
They do not provide a complete list of selectable processing regions, explain every AI inference location or map storage and processing differences to subscription tiers. Residency therefore remains partly specified.
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.
Prescient Security issued Lawdify's ISO/IEC 27001:2022 certificate on February 13, 2026. Certificate 122744, Issue 2, is valid through February 25, 2028, subject to satisfactory surveillance. Its scope covers the information security management system supporting the Legal AI Analyst platform hosted on Azure and Google Cloud Platform, including engineering, development, information security, legal and finance functions.
The certificate is available directly in the trust center, with the issuer, dates and scope visible. Separate audit and penetration testing reports require access approval. The certificate establishes a current independent management system attestation; it does not certify the correctness of generated legal analysis.
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.
Case Brain combines graph and vector databases to connect contract information with evidence and follow changes in a dispute. Lawri, specialized skills and the email agents operate on that case context rather than treating each request as an isolated conversation. Google Cloud Platform, Microsoft Azure and AWS support the infrastructure, with the legal platform's certification scope specifically covering Azure and Google Cloud Platform hosting.
The foundation models and their versions are not individually identified. Nor is there a stated customer notification mechanism for model substitutions. The architecture is partly explained, while the full chain of model operators remains unspecified.
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.
The current terms distinguish recurring self service subscriptions from enterprise arrangements governed by an order form. Additional processing pages and capacity for AI tasks can carry separate charges, so both the recurring structure and usage expansion are visible. Prices are presented during registration or contracting rather than in an open rate table. Cancellation deadlines differ between self service and enterprise subscriptions, and fees are generally nonrefundable.
An earlier founder submission gave an annual range without identifying the currency, which does not establish a current comparable price. Implementation charges and the amount charged for each additional processing unit are also not separately stated.
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.
The legal platform serves law firms and internal legal teams preparing disputes, with construction and infrastructure claims prominent in its founder account. Claims consultants, expert witnesses and contractors also use the same kind of evidence preparation workflow. Support includes APAC languages and communication formats such as WhatsApp, WeChat and KakaoTalk, alongside email archives, spreadsheets and handwritten material.
The company separately sells insurance claims assessment, including bodily injury work. That combination gives a specific picture of the intended settings and evidence types. An exhaustive jurisdiction and practice coverage table, exclusions for particular legal tasks and firm size limits are not supplied.
5 public documents
The public pages on file for Lawdify, 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.
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lawdify.com/en/products/legal5 signals
Primary Law Corpus Provenance, Good Law Verification, Refusal and Uncertainty Behavior and 2 more
Read Oct 16, 2026
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privacy.lawdify.com/resources4 signals
Client Data in Training, Prompt and Output Retention, Ethical Walls and Matter Segregation and 1 more
Read Oct 16, 2026
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Court Disclosure Support
Read Oct 16, 2026
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Outside Counsel Guideline Readiness
Read Oct 16, 2026
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Fabricated Citation Record
Read Oct 16, 2026
Subscription and usage charges; amounts not stated
- The service has recurring subscriptions.
- Extra processing pages and AI task capacity can cost more.
- Enterprise fees are set by agreement.
- An open rate table and implementation amount are not provided.
Recurring subscriptions, with enterprise terms set by order form and additional charges for processing pages and AI task capacity.
Implementation: No separate implementation fee is stated.
Note: Self service pricing appears during registration. Enterprise fees depend on the order form. The historical annual range does not identify its currency and is not treated as a current rate.
Legal Signals
What each signal meansA 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.
Client Data in Training
Can material a lawyer puts into this product be used to train a model?
The published terms prohibit training on customer content. Not a policy page, the agreement.
The February 2026 terms explicitly prohibit using customer documents, legal files and case material to train models or improve products and services. Only anonymized, aggregated usage metrics, such as feature use and error rates, may support platform improvement. That exception concerns operational telemetry, rather than the substance of client matters. The privacy policy also excludes customer personal data from generalized public model training.
Reusable skills within the customer's workspace are a product function; they do not override the express restriction on training from customer content.
Prompt and Output Retention
How long does the product keep what a lawyer typed, and can that be set to zero?
Retention is acknowledged in public materials with no stated period.
Account data remains subject to the privacy policy's service, legal and business purposes. The terms set a 30 day period after a user deletes customer material and a similar exit period before resources and backups are removed, subject to applicable requirements. A deletion certificate and logs follow service termination. These are deletion event rules, rather than a fixed lifetime for every prompt and answer during an active subscription. A customer selected zero retention option and a separate schedule for AI provider copies are not described.
Ethical Walls and Matter Segregation
Does retrieval respect the firm’s ethical walls, or can the model read across them?
No located public material addresses walls or matter level segregation.
The hosting terms describe logical separation between customer environments, with authentication and access controls. The product also organizes information into cases and lets the Excel user select a matter. Those features do not specify how conflicting matters inside one firm are separated during retrieval. Inheritance of source system permissions, enforcement for each user and the treatment of shared skills across restricted matters are not described.
Customer isolation therefore has an express basis, while the behavior of ethical walls within an individual firm's workspace remains unspecified.
Third Party Request and Subpoena Notice
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
Terms commit to notice where lawfully permitted. No transparency report located.
The confidentiality terms require prompt written notice of a compelled disclosure demand to the extent practicable, allowing the disclosing party to seek a protective order at its own expense. The receiving party also agrees to cooperate with those efforts. For a broad regulatory request not aimed at the customer, the agreement permits compliance with prompt notice where the regulator allows it. Disclosure may still proceed when legally required.
These provisions establish a notice commitment with stated qualifications, without a transparency report describing requests actually received.
Primary Law Corpus Provenance
Where does the law in this product come from, and does the vendor have the right to use it?
No located public material identifies the corpus behind the product’s answers.
Legal research is described as covering cases, statutory material and other legal databases, alongside analysis of the customer's own evidence. The interface illustrates relevance and application summaries, but does not identify a complete set of source publishers, licensing arrangements or jurisdiction specific update schedules. The insurance offering separately refers to proprietary injury and settlement intelligence, which does not establish the rights supporting the legal research collection.
Customer uploaded evidence and external legal authority have different provenance, and the latter's acquisition and licensing terms remain unspecified.
Good Law Verification
Does the product tell you when the authority it just cited has been overruled?
No located public material addresses whether authority is checked for subsequent history.
Lawri can check facts against the case file, and Evidence Check examines whether evidence exists and supports a proposition. Those functions concern factual support. The legal research feature includes smart citations, case relevance and statutory analysis, but does not identify a licensed citator or explain its own subsequent treatment process. A case appearing relevant is different from confirming that it remains usable authority after later decisions.
The product's general verification functions therefore do not establish an automated good law check for authorities used in a draft.
Refusal and Uncertainty Behavior
What does the product do when the answer is not in the corpus?
No located public material addresses what the product does when it cannot ground an answer.
The interface includes a prompt optimizer, factual checking and evidence support checks. The terms warn that model output is probabilistic and should receive expert evaluation. None of those descriptions specifies a refusal path when the available material cannot support an answer. A stop condition, a visible uncertainty threshold and the response presented after grounding fails are not defined for Lawri or the email agents.
The question is how the product handles insufficient support before delivering a result, separate from the lawyer's opportunity to review it afterward.
Fabricated Citation Record
Does a public court record exist addressing fabricated or hallucinated legal citations in output from this product?
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 matching entry was found in the AI Hallucination Cases database for Lawdify, Lawri, Case Brain or Smart Tables as of October 16, 2026. The check covered the company name and the named legal product components rather than treating a general account of AI misuse as an incident involving this service. This result records the absence of a matching case in that database on the stated date. It does not measure citation accuracy, establish that every generated draft is reliable or remove the need for professional verification.
Bar Guidance Alignment
Has the vendor engaged in public with the ethics opinions its buyers are bound by?
No located public material engages with bar or ethics guidance.
The legal workspace supports lawyers through first drafts, evidence analysis and tracked edits, and its terms retain expert review and disclaim legal advice. Those provisions do not connect the workflow to a named bar opinion or a jurisdiction specific framework for competence, confidentiality and supervision. The company's mention of inclusion in a government AI guide is a product listing rather than an explanation of professional obligations.
No mapped set of bar requirements accompanies the described legal workflow or its use by claims specialists who are not lawyers.
Billing and Fee Posture
Does the vendor address what happens to the bill when the work takes an hour instead of six?
Public materials claim time savings without addressing billing or disclosure, and the product sits inside a fee relationship between a lawyer and a client where those savings would change the bill.
Lawdify presents faster case preparation and less repetitive evidence work as benefits for disputes teams. Its agents can examine files, produce first drafts and bring case information into spreadsheets, which may change the time spent on a matter. The legal workflow does not include a record separating AI effort from lawyer time for a client invoice. Guidance on passing through productivity gains, recording review time or explaining AI use in an engagement is also not supplied. The cost argument remains an efficiency claim rather than a billing method.
Outside Counsel Guideline Readiness
Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?
A current subprocessor or model provider list is published.
The named service providers are Google Cloud Platform, Microsoft Azure, AWS, Cloudflare, GitHub and Vanta, covering hosting, monitoring, version control and compliance. Customers can also inspect the current terms, privacy policy and ISO certificate, while additional assurance materials require an access request. This provides identifiable suppliers for part of a client's vendor review. A full model provider inventory and a prepared client disclosure or consent package are not presented with the list.
The available material therefore supports supplier identification without establishing every fact needed for a particular client's AI clause.
Court Disclosure Support
If a judge’s standing order requires an AI disclosure, can the product produce one?
Some elements of the record are available, short of a document level export.
The Excel connection retains chat history organized over time, with controls to revisit, rename and delete conversations. Word drafting uses tracked changes, and the legal workspace can export organized bundles for filings. These preserve parts of the work and review context. They do not form a single export identifying the model used for each passage, all retrieved sources and the lawyer who verified them. A court specific disclosure or verification certificate is not described. The available record is partial and should not be treated as an automatically completed filing declaration.