CaseCreate vs Lawdify: how they compare in 2026
CaseCreate and Lawdify approach a litigation draft from different starting points. CaseCreate offers a menu of work products and a discovery question bank, with optional AI generation from the user's facts and researched law. Its export step leaves the lawyer to revise the result. The AI Legal Index identifies that task selection model as useful when the required pleading or discovery response is already known. Lawdify begins by organizing the matter's underlying evidence. Case Brain connects parties, dates and issues across files, while Lawri applies that context to drafting and analysis. The AI Legal Index identifies its Excel connection as a particular advantage for disputes where schedules, invoices and project records need to be considered together. Word editing and email instructions give teams additional ways to use the case information. CaseCreate concentrates on producing a chosen draft; Lawdify maintains a developing factual workspace that can support many requests as the dispute changes.
At a glance
All 15 axes, side by side
The same grid applied to every vendor in the index, graded from public sources. Hover a grade to see what the letter means on that axis.
AI Centrality
How much of the product is actually AI. Whether the machine learning is the mechanism the buyer is paying for or a feature layered onto conventional software, and whether the vendor is specific about which is which.
CaseCreate uses ChatGPT and Claude to draft litigation work from selected options and facts supplied by the user. Its generated outputs include motions, demand letters, discovery requests and appellate briefs. Alongside that AI layer, the platform has a selection based drafting system, a question database, practice checklists and a file labeler. The founder describes AI as optional, with automated pleading creation remaining available through structured choices. That combination makes generation central to several drafting tasks without making every function dependent on a model. The product is a litigation workspace with both automated assembly and generative drafting, rather than a standalone conversational assistant.
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.
CaseCreate describes its drafts as accurate and suitable for refinement, and asks users to provide the facts and law they have researched. That input can constrain a draft, but the public workflow does not show linked primary authorities, pinpoint support or a retrieval method that verifies generated assertions. No measured error rate, evaluation set or account of citation failures accompanies the accuracy claim. Its registration agreement also disclaims accuracy and reliability of results. The discovery question bank and objection responder provide drafting assistance without explaining how each proposed objection is connected to current authority or a verifiable passage in the case file.
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 drafting sequence begins with a user's selection of a work product and, where needed, supplied facts and legal research. After generation, the lawyer exports and edits the result before using it. This creates a review step and leaves the final text under professional control. Practice checklists also guide preparation, while optional AI permits use of the selection based drafting functions. The public workflow does not describe a mandatory approval gate, a confidence threshold that stops generation or an escalation route following an incorrect draft. Nor does it identify an automatic filing process that would act on behalf of the lawyer.
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.
In its January 2026 founder submission for ABA TECHSHOW, CaseCreate reported approximately ten customers paying monthly subscriptions. That statement identifies paid use at a particular stage of the business, although it supplies no customer names, matter examples or retention figures. The current homepage promises faster drafting but gives no measured comparison against manual preparation. A visible disclaimer identifies some displayed metrics as illustrative placeholders, so those figures do not establish performance. Its association partnership describes a market relationship rather than a measured customer result. The available account therefore supports a small paying customer base without a quantified improvement in litigation work.
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 privacy policy promises reasonable precautions against misuse or unauthorized access to personal information. It covers account details, transaction information and sharing with service providers. It does not separately define confidential matter content, attorney client privilege or work product, and it makes no explicit commitment against using client material for model training. The terms give broad reuse rights over comments and feedback, a category that is not clearly aligned with uploaded case material. No matter segregation or model provider handling arrangement is described. General personal information protection therefore leaves the treatment of legal confidences and drafting inputs largely unspecified.
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.
CaseCreate presents itself as software for litigators and asks users to supply their own researched law for generated work. Its founder identifies solo and small firms, independent paralegals and legal departments as intended customers. The registration terms classify site material as general information and direct users toward primary sources, but do not expressly define the boundary between software assistance and legal advice. They also do not require attorney supervision for independent paralegals or identify a professional license check. The Texas governing law provision governs the agreement rather than defining every jurisdiction in which the resulting work may be used.
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.
The public product description focuses on faster litigation drafting, structured selections and a final editing step. It does not set out principles for responsible model development, an accountable AI governance role or a release approval process. Named founders and a practicing lawyer on the leadership team establish company roles without assigning responsibility for evaluating generated legal work. No published testing program addresses differences across jurisdictions, document types or affected groups. The general prohibited use provisions govern user behavior, including discrimination, rather than reporting how the models themselves are evaluated for uneven or inappropriate output in legal matters.
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 published privacy terms cover account data, browser information, consent, service providers and basic security precautions. Payment processing through Stripe receives specific treatment, including a statement about transaction data after completion. Those provisions do not give a retention period for legal prompts, generated drafts or uploaded case records. There is also no named incident notification timetable, legal content deletion procedure or inventory of infrastructure processors. A user may withdraw consent for continued collection or disclosure, but the policy does not explain the effect on existing matter files or backups. The operational rules for the AI data lifecycle remain separate from the payment handling description.
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 service agreement broadly excludes warranties and disclaims liability for inaccurate results, service interruption and losses arising from use. The customer undertakes to indemnify Case Crafter Inc. and related parties for specified breaches and third party claims. No reciprocal provider indemnity, output accuracy warranty or insurance commitment addresses an erroneous pleading or missed legal issue. The agreement selects Texas law and Dallas jurisdiction, and permits termination in stated circumstances. These standard terms allocate most use risk to the customer without publishing a specific remedy for defective AI work. They do not promise reimbursement for lawyer verification or correction of a generated filing.
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.
The platform operates as its own browser workspace, with users selecting a task, supplying information and exporting the generated draft for editing. No named connection to a practice management, document management, email or docketing system accompanies that workflow. The discovery labeler converts and organizes files, but that internal file function does not establish synchronization with a firm's existing repository. Its partnerships concern legal practice and staffing rather than data connectors. An API, integration configuration guide and description of permission inheritance are not supplied. Moving work between CaseCreate and the firm's other systems is therefore described through user input and export.
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.
CaseCreate runs in a web browser without an installed desktop application. The customer creates an account and works in the hosted service, but the public material does not identify its cloud host, tenant arrangement or storage region. The privacy policy warns generally that external providers may operate in another jurisdiction, without naming the locations relevant to legal drafting. It does not distinguish where files are stored from where ChatGPT or Claude processing occurs. No private cloud, customer hosted installation or regional selection is described. The Texas contractual forum does not establish the physical location of client material or model inference.
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.
The privacy policy states that reasonable precautions and industry practices protect personal information. Its specific standards discussion concerns Stripe and payment card handling under PCI DSS. That payment processing assurance does not establish an independent assessment of CaseCreate's legal drafting application or storage of case files. The public product and registration materials do not identify a SOC 2 report, ISO security certificate, assessor or application trust center. There is no accessible scope or assessment period for an audit of the product itself. The distinction is between a named payment standard and assurance covering the legal content processed by the service.
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.
The current drafting workflow identifies ChatGPT and Claude as the AI technologies used to produce work. The founder's earlier product account also describes ChatGPT based generation alongside structured document assembly. These names disclose part of the model supply chain, while leaving the deployed versions, hosting arrangements and routing between providers unspecified. No published term commits to notifying customers before a model replacement or provider change. Provider specific retention and training settings are also unstated. The workflow explains what the models do, but does not give a technical account of how client facts move between the application and those external services.
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 offer is a single subscription at $199 per month, billed monthly and cancellable at any time. It includes unlimited drafting, documents and matters, along with the discovery suite, checklists, subpoenas, jury instructions and file labeling tools. The price is described as independent of seat count, with no additional tiers or fees. Browser access requires no local installation. A free trial is available without a public duration in the plan description. The earlier founder submission quoted $150 per month; the current product page gives the applicable advertised figure. No separate implementation charge is presented within the inclusive offer.
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 founder identifies solo and small firms as the main audience, with independent paralegals, medium firms and insurance legal departments also targeted. CaseCreate supports civil litigation drafting through pleadings, discovery, motions, demand letters and appellate work, with a real estate attorney association partnership. Its January 2026 plan emphasized Texas first and described additional state specific features as future expansion. The current product menu does not supply a jurisdiction by jurisdiction availability table. Nor does it distinguish every supported practice specialty or exclude consumer use through a clear eligibility rule. The work types are concrete, while geographic and professional boundaries remain incomplete.
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.
The 12 legal signals, side by side
Recorded rather than graded. These are the questions a practitioner has to answer before a tool touches a client matter, and the answers are taken from public material only.
Client Data in Training
Can material a lawyer puts into this product be used to train a model?
The registration terms and privacy policy do not specify whether legal inputs or generated drafts may train models. The agreement permits unrestricted reuse of comments, ideas and feedback, but does not clearly define that category as client matter content or establish a training right. The privacy policy's consent language concerns purchase information and secondary uses such as marketing. It does not create a comprehensive service only restriction on legal content.
No dedicated training prohibition, permission or customer control is stated for the ChatGPT and Claude drafting workflow.
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?
The policy describes payment information being used to complete a transaction and then no longer saved, but does not extend that statement to legal drafts or prompts. Case files, generated work, account history and backups have no published storage duration. Withdrawal of consent is possible for continued collection or disclosure, without a described deletion schedule for existing litigation material. Unlimited documents and matters in the subscription describe product access, not a promise that those records are either preserved indefinitely or erased immediately.
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?
Individual and organization account types are available at registration, and the product organizes litigation work by matter. The public workflow does not explain which users can view each matter, whether separate teams have isolated content or whether model retrieval is limited by those permissions. A common case workspace does not establish an ethical wall. There is no described inheritance of restrictions from a firm's external repository or procedure for revoking a team member's access to material already processed by the drafting service.
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?
The privacy policy permits disclosure of personal information when required by law or following a violation of the service terms. It does not promise advance or subsequent notice to the customer, reserve a specific notice decision or describe a process for challenging an excessive demand. No transparency report accompanies the provision. The clause explains a circumstance in which information can leave the service, while the customer's opportunity to object and the handling of legal matter content under such a request remain unstated.
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?
Users can provide their own researched law and facts for drafting. CaseCreate also supplies a discovery question database, checklists and document assembly options, but does not identify the underlying legal authorities or rights supporting that material. No external primary law collection, licensing agreement or update schedule is named. The founder's Texas focus describes an intended market rather than a complete source inventory.
The public workflow therefore does not establish what legal material, beyond the user's own inputs and model knowledge, supports a generated argument.
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?
CaseCreate drafts from selected options and user supplied facts and law, without describing a service that evaluates the later treatment of cited cases. No commercial citator or proprietary subsequent history feature is named. The instruction to bring researched law assigns an input task to the user, but does not specifically require a good law check or show one inside the product. Discovery objections and appellate drafting may contain legal assertions; the public workflow does not explain how the continuing validity of their authorities is established.
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?
The generation workflow moves from selecting a document to producing and editing a draft. It does not describe an abstention response when the supplied facts are incomplete or the legal authority is unsupported. No confidence display, unsupported assertion warning or demonstration of a refused legal request accompanies the product material. The terms disclaim accuracy and reliability, which allocates risk without specifying model behavior. A final opportunity to edit the work leaves correction with the user rather than defining when generation itself stops.
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?
Damien Charlotin's AI Hallucination Cases database contains no matching entry for CaseCreate or its former CaseCrafter name as of October 16, 2026. The product generates litigation work with external AI systems, and its agreement disclaims the reliability of results. Absence of a matching judicial or disciplinary incident does not establish that all drafts or citations are accurate. The database records reported legal incidents, rather than providing a comprehensive evaluation of every pleading, objection or appellate argument generated through this particular service.
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?
The product is built around lawyers' drafting work and asks them to contribute their own researched law. Its public materials do not apply a named ethics opinion to competence, confidentiality, supervision or client consent. The general information disclaimer and final editing step describe use conditions without explaining professional responsibility requirements. Independent paralegals are among the founder's intended users, yet no separate supervision arrangement is described for them.
The real estate association partnership establishes a professional relationship, not a published mapping to bar 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?
CaseCreate promotes shorter drafting time and a shift toward charging clients for completed work through flat fees. This addresses the business model of a law practice, but does not provide a per matter account of AI activity or a method for separating actual lawyer time from automated preparation. There is no concrete client disclosure template or guidance on treating the software expense in a bill. The stated monthly subscription is the firm's purchase price; the product's general flat fee message does not determine an appropriate fee for an individual engagement.
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?
ChatGPT and Claude power generation, giving a firm two relevant names for an initial account of its AI use. It does not provide a complete subprocessor register, model versions, processing locations or provider specific handling terms. The registration policy separately names Stripe for payments. No client consent wording or standard disclosure package connects these services to confidential legal work. The public names therefore expose part of the external AI arrangement without supplying a complete response to a client's information requirements.
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?
A user can export and edit the generated litigation draft, but the public material does not describe an accompanying record of the model, inputs, authorities or human verification. No court disclosure template or certification workflow is supplied. The practice checklists organize preparation without expressly recording AI provenance. Export of the final work product alone would not establish which passages were generated or which citations a lawyer independently validated. Any explanation of that process for a court would require information beyond the described drafting output.
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.
The questions both sides leave open
Derived from the records above rather than written, so it cannot favor either vendor. Take these into both conversations and ask each side the same question.
- Ethical Walls and Matter Segregation
- Primary Law Corpus Provenance
- Good Law Verification
- Refusal and Uncertainty Behavior
- Bar Guidance Alignment
Which one fits
Choose CaseCreate if
- The lawyer has already assembled the relevant facts and researched law.
- A discovery question database and objection responder are central to the task.
- Routine pleading preparation benefits from a defined menu of draft types.
Choose Lawdify if
- The matter contains large amounts of mixed evidence that must be organized first.
- Project spreadsheets need to be examined alongside correspondence and underlying records.
- Team members want to work with case context through Word, Outlook or Excel.
In summary
CaseCreate
CaseCreate offers litigation drafting tasks, checklists and a discovery question bank in a single subscription.
Lawdify
Lawdify builds case context from evidence and brings that context into analysis and drafting.
Questions buyers ask
How does each product begin a draft?
CaseCreate begins with a selected task and information supplied by the user. Lawdify can pull information from its Case Brain and apply the team's precedents or writing style. From the AI Legal Index, based on each vendor's own published materials as of October 16, 2026. No vendor pays for placement.
Does CaseCreate offer Lawdify's evidence workspace?
CaseCreate has matter organization and file labeling, but its public workflow does not describe Lawdify's evolving case knowledge system or its Microsoft connections. From the AI Legal Index, based on each vendor's own published materials as of October 16, 2026. No vendor pays for placement.
Can Lawdify accept an email instruction?
Yes. Its legal workflow describes receiving an instruction and attachments by email, creating tasks and returning the agents' results to the inbox. From the AI Legal Index, based on each vendor's own published materials as of October 16, 2026. No vendor pays for placement.
Neither vendor paid for inclusion, placement or a grade, and neither reviewed this page before it published. Everything on it comes from public material on the dates shown. How the index grades.
The comparison covers legal drafting and dispute preparation. Lawdify also sells a separate insurance claims product.