Contractzy vs Leah: how they compare in 2026
Contractzy and Leah connect contract language with work that follows signature, but their operating scope differs. Contractzy organizes risk review, approvals, signatures, and commitments around an agreement. CORA extracts obligations, assigns responsibility, and tracks due dates, while a guidebook supplies the positions used to review new language. Leah connects that contracting work to procurement and finance through specialized agents sharing commercial context. A supplier approval or invoice process can therefore sit alongside contract obligations within its wider platform. Leah also provides Word redlining and a legal helpdesk that attaches sources to answers. Contractzy is relevant when a team wants a contract workflow with defined user and agreement packages and several hosting choices. Leah has a broader remit where the intended system must execute related commercial processes across departments and existing enterprise applications.
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.
CORA AI powers contract risk analysis, summarization, metadata extraction, and obligation management inside a broader contract lifecycle platform. Review starts with company guidebooks, while extraction turns scanned PDFs, images, and Word files into searchable information. Obligation management creates owners, milestones, deadlines, and renewal alerts from agreements. Templates, clause libraries, approvals, signatures, version history, and the repository remain useful without model inference. Essentials and Professional also separate conventional contracting functions from the fuller AI package in Enterprise. The models therefore run substantial review and analysis functions, while established workflow and storage features remain a separate part of the product.
Leah sells AI agents and an orchestration layer that sit on top of a contract lifecycle platform, and that platform works without them. The vendor describes it the other way round. It says other vendors bolted AI onto systems built for manual workflows, while Leah was designed from scratch with orchestration as the foundation. ContractPod Technologies has sold contract lifecycle management since 2012. Leah launched in March 2023 as an AI services hub within that platform, went standalone in May 2023, and Leah Intelligence followed in October 2024. Without the agents, the product is still a working CLM with guided intake, approval routing, DocuSign and Adobe Sign execution and a contract repository. That CLM has its own market and its own Gartner category placement. The orchestration layer on top is model driven.
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.
Risk analysis highlights ambiguous clauses and departures from company guidebooks, then lets reviewers inspect changes through tracked redlines. CORA AI also extracts parties, dates, monetary terms, and obligations from uploaded agreements. Accuracy claims include 98% for risk detection, 95% or more for metadata extraction, and up to 99% in the pricing FAQ, without a defined evaluation set or error breakdown. The contract text supplies context, but a retrieval method with linked primary legal authority and citation treatment is unspecified. Severity labels describe contractual risk rather than confidence in an answer. Critical decisions still call for human review under the pricing guidance.
Leah's Contract Helpdesk answers questions from the customer's agreements and links each response to the clause or document supplying the answer. Its illustrated payment example identifies the agreement version and clause number, while Leah Discovery extends retrieval across a portfolio. Users can open the underlying contract and initiate a reminder, amendment or escalation from the answer. This is a described route from a question to its contractual source. However, the product's categorical claim that Leah does not hallucinate is not supported by a published test set or error breakdown. The AI terms expressly disclaim accuracy, completeness and currency, and linked contract text does not validate external legal authority.
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.
Reviewers upload a Word or PDF guidebook or generate one with AI, scan an agreement, and inspect highlighted risks and tracked revisions. Editable guidebooks encode company requirements, and alerts identify departures or high risk clauses. Contracts failing mandatory criteria are prevented from advancing until compliance is ensured. Legal teams retain control over precise edits, with approval routing and version history supporting review before execution. The pricing guidance recommends human review for critical decisions. The remaining uncertainty is the control path after an incorrect classification: the criteria configuration, override permissions, and escalation route for an AI error are not specified.
Customer policies determine which Leah agents may act, the data they may access, thresholds, and escalation requirements. The orchestrator applies approvals, escalations, and rejections during execution, then records the action, rationale, policy, inputs, and outcome. Policies are configurable rather than fixed defaults. The AI terms add a categorical limit: automated decisions with legal or similarly significant effects on individuals require adequate human review and legal compliance. Customers must also independently verify outputs and cannot present them as provider approved or wholly human generated. Trials and betas are restricted to internal evaluation. These contractual limits accompany the product's policy, execution, and audit loop.
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.
Legal leaders at Bajaj Markets, Bridgestone, and Easebuzz describe actual use of the platform. Manish Jain emphasizes responsive support; Reni Verghese describes managing contracts against timelines; Nitin Bhuwania describes reducing administrative effort and retrieving executed agreements after digitization. These accounts identify customers and concrete activities, although they do not supply dated before and after measurements. Separate CORA AI claims include an internal study of faster summarization and improved extraction, without a disclosed sample or method. Implementation generally takes two weeks to one month depending on integrations, customization, and migration. That estimate describes rollout effort rather than a measured customer outcome.
Leah publishes qualitative quotes from four named people. Noelle Perkins is EVP and Chief Legal Officer at Cushman and Wakefield, and Lidia Kamleh is Chief Legal Officer at Dubai Future Foundation. Frances Bain-Cumberbatch is Chief Legal and External Affairs Officer at Ansa McAL, and Zillia Knight is Senior Legal Officer at Terumo Europe. Three results are published with the customer unnamed. A major American logistics company cut contract review time by 91 percent. A global manufacturer protected more than $18 million of revenue, and an American retail REIT tracked more than $2 million of savings. About 54 enterprise logos appear, including Philips, MUFG, Sandoz, Pernod Ricard, Alaska Airlines and Wood PLC. PwC and KPMG appear among them. PwC entered a commercial alliance in March 2024, and Epiq resells Leah in its Service Cloud. Integreon is quoted as an early adopter that resells it, and Pinsent Masons adopted it for managed legal services in July 2025. Partners and customers are shown together without distinction, and the Chief Product Officer of Execo, another services partner, is among the testimonials.
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 agreement limits personal data use to delivering, maintaining, securing, and improving the contracted services under customer instructions. It covers contract files, attachments, metadata, communications, approval records, and access logs, and rules out selling customer data or unrelated advertising uses. Subprocessors must accept protections at least as strong as the agreement. Role permissions restrict visibility to authorized departments and users, while production access follows least privilege. The improvement permission contains no explicit model training exclusion. Privilege preservation, work product treatment, matter isolation during retrieval, and foundation model retention commitments remain unspecified, so these provisions do not settle every confidentiality question for a law firm.
Customer inputs and outputs are confidential Customer Data under the May 2026 agreement. Their use is limited to providing and maintaining the service, with a separate AI clause permitting training or improvement solely for that customer's benefit. The trust portal rules out generalized model training, while the DPA identifies four model providers that store or retain no Customer Data. Role permissions and a private Azure OpenAI environment support access isolation. Mutual confidentiality obligations and prior notice of legally compelled disclosure apply. Explicit privilege and work product preservation, and matter-specific retrieval walls inside a customer's organization, remain unspecified.
UPL and Professional Responsibility Posture
Whether the vendor is clear that it supplies a tool rather than legal advice, who its audience is, and how it addresses unauthorized practice of law, competence and supervision duties, and jurisdiction limits. ABA Formal Opinion 512 is the reference point. Where the advice line is not the duty a product raises, the axis is read through the nearest professional duty it does raise: judicial conduct rules and the reviewing duty for products sold only to courts, and the duty to bill for time actually spent for products that draft time entries.
Legal departments use CORA AI to identify contractual risks, make edits, and manage approvals, while procurement, sales, finance, and HR users share the broader workflow. Human decision authority is explicit in the product positioning, and critical decisions are subject to a recommendation for human review. The CORA AI introduction also directs customers to consult their legal departments about regulatory implementation. Those operating instructions do not establish an advice versus software boundary, permitted legal jurisdictions, or a position on unauthorized practice. The software terms disclaim warranties generally without a specific legal advice disclosure. Nonlawyer participation is supported without a corresponding professional responsibility framework.
Attachment D requires independent review of every AI output for its intended use and prohibits representing output as provider approved or wholly human generated. Automated decisions with legal or similarly significant effects require adequate human review and compliance with law. The platform nevertheless promotes autonomous work across legal, procurement, finance, and contracting functions. These general AI use restrictions establish customer responsibilities, but do not explicitly distinguish legal advice from software assistance, restrict use by jurisdiction, or map professional competence duties. The broad legal automation positioning therefore has a contractual review requirement without a dedicated professional responsibility explanation for practicing lawyers.
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 CORA AI introduction describes pretrained language models refined through legal expert feedback, regular updates, and testing across legal scenarios. That establishes a quality aspiration but leaves release criteria, review ownership, evaluation sets, and results across contract types or jurisdictions unspecified. The model training description refers broadly to contracts, legal materials, and precedents rather than a traceable evaluation program. Prajot Borkar is the named data protection officer, responsible for privacy compliance; that role does not establish accountability for model behavior. Company guidebooks let customers impose their own contract policies, but they are distinct from governance of the vendor's models and training process.
A dedicated AI governance page names six failure modes the vendor says it engineered out. They include black box decisions that cannot be defended to a regulator or board, and compliance frameworks retrofitted after the fact. Against them the page sets three pillars and a loop of policy, execution and audit. Each action is logged with its rationale and governing policy, in records described as tamper resistant and immutable. The page also says every action is measured against benchmarks for accuracy, bias and outcome, and that accountability is structural rather than aspirational. It names no person or role accountable for model behavior and describes no testing before release. It gives no benchmark method or schedule and discloses no bias measurement result.
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 May 2026 agreement identifies eight subprocessors and their functions, including AWS for hosting, Bedrock inference, and Textract processing. Controls include encryption, least privilege access, internal multifactor authentication, audit logs, restricted production access, monitoring, and backups. Incident procedures cover identification, investigation, management, and response. Customer notification follows a confirmed personal data breach without undue delay where legally required, rather than an unconditional fixed deadline. Data remains as long as needed for service, legal, dispute, or security purposes. Return or deletion follows a written request at termination within a commercially reasonable timeframe, with unspecified backup schedules and legal exceptions.
The DPA names model, hosting, support, signature, and integration subprocessors with their locations and purposes. New subprocessors require 30 days' notice and permit an objection, with termination and unused-fee refunds if unresolved. Security incidents affecting personal data require notice within 48 hours of awareness. The trust portal describes role restrictions, identity-provider authentication, monitoring, incident exercises, and penetration testing. Contract data can be exported during the term and deleted following a request after termination, subject to backup and legal exceptions. A routine prompt history duration remains unspecified. Provider-level zero retention does not define the lifetime of records held by Leah itself.
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 software terms cap the operator's and suppliers' liability at the amount the client actually paid. Service comes as is and as available, with broad exclusions for warranties, fitness, noninfringement, accuracy of performance, and correction of errors. The agreement does not attach an indemnity, insurance commitment, or enforceable accuracy warranty to CORA AI output. It also excludes responsibility for incomplete or corrupt backups and places independent backup responsibility on the client. India is the defined country for governing law, with informal dispute resolution first. These terms allocate general software risk without promising a remedy for an incorrect contractual recommendation.
Leah's May 2026 Cloud Terms exclude infringement by AI output from the provider's intellectual property indemnity. Attachment D also disclaims output accuracy, completeness and currency, requiring customers to independently verify results. Ordinary cloud service remedies remain: a performance warranty, correction or termination with a refund after an unsuccessful 30 day fix period, and an indemnity for covered service infringement claims. The general liability ceiling is fees paid or payable in the preceding twelve months, with a threefold ceiling for security or DPA breaches and specified uncapped claims. Trials and betas have no indemnity or warranty and a $1,000 cap. These software remedies do not remove the explicit AI output exclusions.
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.
Salesforce users can create, approve, and sign contracts within their CRM, while HubSpot data can generate agreements and feed approval and signature steps. Oracle supports contract creation and management, and Jira tickets initiate creation and approvals. Slack brings contract updates and actions into team conversations; Gmail supports workflows from the inbox. DocuSign, Adobe Sign, and UAE Pass provide signature connections, with Zoho also supporting contract generation and tracking. Custom APIs and integrations are available. Field mappings, authentication setup, synchronization conflicts, and permission propagation are not described, so the connection list does not establish a complete implementation specification for each workflow.
Leah connects contract workflows with Salesforce, Microsoft Dynamics and HubSpot opportunities, while an Outlook add in starts contracts, uploads attachments and triggers approvals that synchronize with the CLM. Signature connections let customers configure signing order, copied recipients and expiry dates, then return executed agreements to the repository. Word supports review and tracked changes. The current CLM page also lists SharePoint, OneDrive, Box, Google Drive, Dropbox and NetDocuments, replacing the earlier absence of a named legal document system. ERP connections include SAP, Oracle, Workday and Coupa. Detailed field mappings, direction and permission inheritance for every connector remain unspecified, especially for the document systems.
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.
AWS cloud hosting is the standard delivery route, with an additional single tenant cloud option and deployment on customer premises. Implementation scope depends on integrations, migration, and customization, and Enterprise includes custom integration and deployment options. The agreement identifies AWS operations as global, including India, Singapore, and the United States, while other processors operate in additional global locations. Cross-border safeguards may include applicable standard contractual clauses. These locations describe the processor network rather than selectable customer residency regions. The division between contract storage, model inference, OCR processing, and backup locations is not specified for each deployment option or subscription tier.
Shared cloud delivery is standard, with single tenant deployment and a private Azure OpenAI environment available for additional isolation. The May 2026 subprocessor schedule adds region-specific hosting arrangements across Microsoft Azure, Google Cloud, and Oracle Cloud. Azure lists Europe, the United States, and Australia; Oracle also includes India, while Google lists Japan and several European jurisdictions. Model providers have their own location lists, selected according to the customer's hosting region where applicable. This distinguishes hosting from model services, but does not establish a complete per-customer map of storage, inference, backups, and support access across each product configuration.
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 company identifies itself as ISO 27001:2022 certified and describes encryption, AWS hosting, role permissions, and restricted production access. Its agreement adds TLS 1.2 or later, internal multifactor authentication, continuous monitoring, security alerts, and backup and recovery measures. On a reasonable written request, the company may provide existing compliance material, certifications, or third-party audit reports instead of a disruptive audit. A current certificate scope, validity period, and directly accessible report are not supplied with these statements. Generic security language and a badge do not establish the scope of a separate SOC 2 examination or an AI-specific assurance program.
A-LIGN's ISO/IEC 27001:2022 certificate covers the information security management system for design, development, operation, maintenance, and support of Leah CLM and Leah Legal as SaaS. Certificate ISMS-CO-032326 was issued March 23, 2026 and expires March 23, 2029. The trust portal provides the certificate directly, alongside a SOC 3 report covering the contract management and Copilot systems from October 2024 through September 2025. That report addresses security, availability, confidentiality, and privacy, with Azure and customer control dependencies excluded from the auditor's examination. Penetration-test material is also available. These attestations concern system controls, not the correctness of an AI legal recommendation.
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.
Amazon Bedrock supplies AI and machine learning processing, and Amazon Textract handles OCR and document processing within the AWS subprocessor role. CORA AI uses an array of pretrained language models and a training process involving legal contracts, materials, precedents, and expert feedback. This identifies infrastructure and broad architecture, while leaving the foundation model families, versions, routing rules, and fine-tuning arrangements unnamed. Subprocessors may change as technical or operational needs evolve. The agreement does not commit to advance model change notices or identify which model handles a particular risk review, summary, or obligation extraction. Provider locations likewise do not assign inference to a particular region.
The May 2026 DPA lists Anthropic, OpenAI, Cohere, and Google AI/ML for Leah functionality, each with a no-storage or no-retention statement and defined processing jurisdictions. Azure supports hosting, translation, and Office services; Oracle and Google add hosting options. Zuva handles document intelligence, and ABBYY is limited to older CLM deployments. The platform routes tasks among language models and allows customer customization. New subprocessors require 30 days' notice, with an objection and termination route. Model versions and the provider selected for a particular generated passage remain unspecified. The regional provider list describes available processing arrangements rather than a complete execution record.
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.
Essentials supports up to three users and 50 contracts each month; Professional allows up to ten users and 200 contracts; Enterprise starts above ten users with 500 monthly contracts. Each base subscription requires a quote. The pricing matrix lists Professional AI risk analysis at $40 per user per month, with up to 100 analyses monthly, while Enterprise includes 20 free reviews. Unlimited storage and distinct signature allowances accompany the plans. Reviewers need no additional license. Integrations, customization, migration, and deployment affect implementation scope, but their charges are not stated. The AI add-on figure therefore does not represent the total cost of running the platform.
The cloud service uses negotiated orders with a default 12-month subscription, automatic renewal, and 30-day nonrenewal notice. Standard, Gold, and Platinum support plans set different support hours, response targets, and availability commitments. Professional services require an order or statement of work, with possible travel expenses and separately quoted configuration work. AI access is described as unlimited subject to fair use, including restrictions on excessive compute, API calls, storage, and transfer. No subscription amount, seat rate, or implementation price is stated. For applicable European switching arrangements, an early termination charge can include the remaining subscription fees despite the right to transfer data.
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 primary audience is corporate legal operations alongside procurement, finance, sales, HR, compliance, and operational teams. Legal workflows include drafting, negotiation, risk review, approval, execution, repository retrieval, and ongoing obligations. Sector offerings include fintech, automotive, manufacturing, healthcare, software, real estate, logistics, and other commercial industries. Templates and guidebooks adapt review to company policies, while repository filters include jurisdiction, expiry, and contract value. Regional offerings span Europe, the Americas, Asia, and the Middle East, but a jurisdiction and language support matrix is unspecified. Litigation research, court filing, and consumer legal representation are not established parts of the contracting service.
Leah publishes dedicated industry pages for CPG and manufacturing, energy and utilities, financial services, healthcare, and pharma and medical devices. It describes its customers as Fortune 500 enterprises in regulated industries. By function it publishes pages for legal leadership, legal operations, sales and revenue, procurement, and finance. The pages carry distinct propositions written for the General Counsel, the contract operations team, the Chief Procurement Officer and the finance leader. The customer roster spans banking, airlines, pharmaceuticals, consumer goods and engineering. No published page says which practice areas, contract types or matters the platform does not support, and none addresses smaller organizations. Law firms appear only indirectly, through managed service partners, rather than as a served segment.
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 DPA allows personal data use for providing, maintaining, securing, and improving the services, subject to customer instructions. Contract files, attachments, and related workflow records fall within that processing scope. The improvement right has no explicit model training exclusion, while advertising profiling and unrelated commercial uses are prohibited. This is a contractual permission for improvement, not a statement that customer contracts actually train CORA AI.
Attachment D permits use of inputs and outputs to train or improve AI features solely for the customer's benefit. The same agreement treats both as Customer Data. The trust portal excludes generalized model training, and the DPA says Anthropic, OpenAI, Cohere, and Google store or retain no Customer Data for Leah functionality. Private customer improvement is therefore permitted even though generalized training and retention by those model providers are restricted.
Prompt and Output Retention
How long does the product keep what a lawyer typed, and can that be set to zero?
Personal data remains for as long as needed to operate the service, meet legal obligations, resolve disputes, and enforce agreements. Written requests at termination can trigger return or deletion within a commercially reasonable timeframe. Backup copies persist under unspecified schedules, with legal, security, and audit exceptions. No routine duration is assigned specifically to prompts, generated summaries, or review outputs while the subscription remains active.
Inputs and outputs are Customer Data under the AI terms. Export is available during the subscription, and deletion follows a request after termination within 60 days, with backup and legal exceptions. The DPA permits access, return, or deletion of personal data during service but sets no routine prompt history duration. Zero retention at named model providers does not define how long Leah keeps its own conversation, output, or audit records.
Ethical Walls and Matter Segregation
Does retrieval respect the firm’s ethical walls, or can the model read across them?
Department and user permissions limit visibility into contract status, approvals, obligations, and renewals. The DPA also specifies role permissions, least privilege, and restricted production access. Neither provision explains how CORA AI retrieval enforces a law firm's matter walls or inherits permissions from an external document system. Single tenant deployment separates organizations, but does not by itself establish boundaries between conflicting matters inside one organization.
Leah describes role permissions, restrictions on the data agents may access, single tenant deployment and a private Azure OpenAI environment. These establish claimed controls for separating customer information and limiting access. Its trust portal also describes least privilege and reviews of staff access. The materials do not explain how retrieval enforces a barrier between separate legal matters inside one customer organization, or how permissions inherited from an external document system constrain an agent's answer. Corporate tenant isolation should not be assumed to provide a law firm's matter conflict controls.
Third Party Request and Subpoena Notice
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
The DPA requires prompt notice when a data subject requests access, correction, deletion, or another personal data right. That obligation concerns individuals exercising privacy rights, not subpoenas or government demands for customer contracts. The software terms and privacy provisions do not establish a separate commitment to tell customers before responding to compulsory legal process. Breach notifications are also a different event and do not settle this question.
Section 19 permits legally required disclosure of confidential information, including Customer Data. Where law permits, the recipient must give reasonable advance notice and cooperate at the discloser's expense to seek confidential treatment. Inputs and outputs are covered as Customer Data under the AI attachment. The obligation therefore reaches customer AI material as well as uploaded contracts, without a separate transparency report or history of government demands accompanying it.
Primary Law Corpus Provenance
Where does the law in this product come from, and does the vendor have the right to use it?
Risk review uses customer guidebooks uploaded in Word or PDF, company playbooks, and the contract being analyzed. CORA AI's training description also refers to broad datasets of legal contracts, materials, and precedents. It does not identify a primary law collection, its licensing basis, or an update schedule for individual sources. A company policy guidebook supplies contractual positions, but does not establish the origin or currency of legal authorities.
Leah uses the customer's contracts, internal policies and playbooks to answer questions and guide its agents. Those materials are an internal reference base, not an identified external legal corpus. The vendor also refers to established legal precedents, without naming a case law database, jurisdiction, publisher or licensing arrangement. No update schedule accompanies that reference. Source links to a customer's agreement can establish the origin of a commercial term, but do not establish the provenance or rights basis of any external legal authority used in an answer.
Good Law Verification
Does the product tell you when the authority it just cited has been overruled?
CORA AI scans agreements for risky clauses and deviations from a company's guidebook, then presents severity labels and suggested revisions. No case treatment indicator or connection to a named legal citator accompanies that review workflow. Regular legal updates are a general training claim rather than a check on an authority's subsequent history. The human review recommendation concerns critical decisions and does not describe automatic verification that cited law remains valid.
Leah describes no citator, treatment signal or currency check, and does not say whether legal authority is reviewed for later history. The platform manages contracts, obligations and procurement workflows rather than retrieving case law, so a citator is not part of what it sells. The vendor does refer to Leah operating against established legal precedents, without identifying any source. That is the one place the product invokes primary authority, and no verification step is described for it.
Refusal and Uncertainty Behavior
What does the product do when the answer is not in the corpus?
Critical, high, medium, and low labels prioritize the contractual significance of a detected issue. They do not measure the model's confidence or describe what happens when an answer lacks support. Mandatory compliance criteria can stop a contract from advancing, but that workflow restriction is separate from an AI refusal to answer. The risk and summary workflows do not specify an unsupported-answer response or a grounding threshold shown to reviewers.
The home page and the AI governance page describe no explicit path for Leah to decline to answer or abstain, and no confidence or grounding rating. The governance loop does produce rejections. Approvals, escalations and rejections are applied automatically according to the customer's rules. Those are policy outcomes set by configured guardrails, not the model declining because it cannot ground a response. Neither page says what Leah does when the customer's own contract set or playbook does not cover the question in front of it.
Fabricated Citation Record
Does a public court record exist addressing fabricated or hallucinated legal citations in output from this product?
No court finding involving Contractzy, CORA AI, or The Legal Capsule appears in the AI Hallucination Cases database as of October 15, 2026. The current name and former brand produced no relevant match across its 2,191 entries. This dated result concerns reported proceedings. It does not establish that generated clauses or legal assertions are accurate, or rule out a proceeding outside that collection.
Neither Leah nor ContractPodAi appears in the AI Hallucination Cases database maintained by Damien Charlotin. Its entries concern court decisions involving hallucinated content, with tool names recorded where available. Leah's principal workflows cover commercial contracting, procurement, and related legal work rather than preparation of court submissions. That product setting helps explain the limited relevance of litigation records, but a missing entry is not a measure of the accuracy of its contract answers or redlines.
Bar Guidance Alignment
Has the vendor engaged in public with the ethics opinions its buyers are bound by?
The CORA AI introduction encourages customers to involve their legal departments when aligning implementation with regulatory requirements. Product guidance also recommends human review for critical decisions. These directions do not engage with a named bar opinion, client consent standard, or professional competence rule. The intended corporate legal audience and collaboration with nonlawyer departments are clear, while a jurisdiction-specific ethics mapping for use of AI in legal work remains unspecified.
Leah publishes nothing that engages with bar or ethics guidance. That includes ABA Formal Opinion 512, state bar guidance in the United States, and Solicitors Regulation Authority or Law Society material. The company is headquartered in London and sells into legal departments across North America, Europe, Asia and Australia. Its published compliance material covers regulation and security frameworks, namely GDPR, CCPA, HIPAA, SOC and ISO. None of it addresses the professional conduct obligations that bind the lawyers using the product.
Billing and Fee Posture
Does the vendor address what happens to the bill when the work takes an hour instead of six?
CORA AI is positioned for corporate departments managing their employer's contracts, alongside procurement, sales, finance, and HR. Faster review, metadata extraction, and obligation tracking reduce those teams' own administrative costs. That workflow does not ordinarily create a bill from outside counsel to a client. Subscription charges and AI add-on units price the software, while no client time-entry adjustment or legal fee disclosure feature is described for the core corporate use case.
Leah serves corporate legal, contracting, procurement, and finance teams, and also supports legal services delivered to clients. Pinsent Masons Vario adopted the platform for its Managed Legal Services and Consulting work, including contracting support for customers' internal legal departments. Corporate efficiency figures concern operating cost, while the firm's use can affect client service delivery. The platform records agent actions and policy decisions, but gives no specific method for adjusting client fees or disclosing saved lawyer time.
Outside Counsel Guideline Readiness
Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?
The DPA names AWS, Razorpay, DocuSign, Zoho Sign, emSigner, Digio, OnlyOffice, and Mailgun with locations and purposes. AWS includes Amazon Bedrock for AI processing and Textract for OCR, giving procurement teams a concrete starting point for provider disclosure. Foundation model versions and a client consent package are unspecified. Subprocessors may change with operational needs, without a separate advance-notification period or customer objection process in the listed terms.
Attachment B includes the DPA, processing details, transfer mechanisms, and a subprocessor list by purpose, location, and product. Model providers are Anthropic, OpenAI, Cohere, and Google, alongside hosting, signatures, support, and integration suppliers. Codestone, Freshworks, Oracle, and Totango appear in the May 2026 list. New providers require 30 days' notice and permit objections. The AI terms separately disclose customer-specific training permission and require independent output review.
Court Disclosure Support
If a judge’s standing order requires an AI disclosure, can the product produce one?
Tracked revisions, version history, contract audit trails, and approval records preserve parts of the drafting and review process. Legal teams can see changes and updates as agreements move through the lifecycle. Those records do not establish a per-contract export identifying the model, retrieved sources, and a human's verification of each AI result. The platform addresses commercial contract execution; a court filing disclosure or certification workflow is not specified.
The audit stage of Leah's published governance loop logs every decision. Each entry records what the agent did, why, under which policy, with what data and with what outcome. The records are described as tamper resistant, immutable and ready for any audit. That gives the action, the rule, the inputs and the result for each action. The published description of the log does not include the model. The platform chooses among several language models for each task and identifies no model or version, so the log does not show which system produced a given passage.
No export built for court disclosure or AI use certification is described. The audit framing is regulatory and internal rather than judicial.
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.
- Good Law Verification
- Refusal and Uncertainty Behavior
- Bar Guidance Alignment
Which one fits
Choose Contractzy if
- Your contract team needs to turn extracted obligations into owned tasks and deadline tracking.
- Reviewers want editable risk guidebooks alongside the agreement's approval and signature process.
- Contract hosting on the customer's premises is part of the deployment requirement.
Choose Leah if
- Procurement and finance processes need to share the context held by the contracting system.
- Legal staff want a helpdesk that answers contract questions with attached sources.
- The deployment will connect agents to ERP, procurement, and identity systems through a phased rollout.
In summary
Contractzy
Contractzy concentrates its AI functions on review, summaries, extraction, and obligations within its contract platform. Its guidebooks can be uploaded or generated and then edited before becoming the basis for risk checks. The AI Legal Index highlights how extracted commitments become assigned tasks with dates and status tracking. This connects review work with contract administration after signature. Deployment choices include a dedicated cloud environment or installation on customer premises, while the ordinary plans define user and agreement allowances.
Leah
Leah combines contracting, legal, procurement, and finance in an agent platform connected to enterprise systems. Its CLM includes Word redlining against playbooks, conditional approval routing, signature integrations, and a searchable repository. Source attached helpdesk answers are one specific capability identified by the AI Legal Index. Agents also support commercial work beyond the agreement itself, including supplier processes and financial operations. Configuration follows the customer's policies and connected systems, with a phased implementation across functions.
Questions buyers ask
Where does Leah extend beyond ordinary contract administration?
Its platform also handles procurement, finance, and shared services work. The stated design connects those operations to contract obligations and legal exposure, rather than keeping contracting as a separate repository. From the AI Legal Index, based on each vendor's own published materials as of October 15, 2026. No vendor pays for placement.
Can Contractzy allocate the work created by a signed agreement?
Yes. Its obligation workflow extracts commitments and supports assignment, due dates, status tracking, and reminders. Those functions help teams follow the agreement after review and signature. From the AI Legal Index, based on each vendor's own published materials as of October 15, 2026. No vendor pays for placement.
How does Leah support contract questions from business teams?
Its legal helpdesk answers questions using contract context and attaches sources. The CLM repository also provides search, obligation tracking, and renewal alerts. From the AI Legal Index, based on each vendor's own published materials as of October 15, 2026. No vendor pays for placement.
Are the products limited to corporate legal departments?
Both address business contracting. Leah also has an identified law firm deployment through Pinsent Masons' Managed Legal Services, which uses the platform in client delivery. That use extends its audience beyond internal company operations. From the AI Legal Index, based on each vendor's own published materials as of October 15, 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.
Leah is the current brand for ContractPodAi. Its broader commercial platform and Contractzy's contract workflow overlap in CLM, while their scope outside contracting differs. Neither product's automated output removes the need for accountable legal review.