Contractbook vs Contractify: how they compare in 2026
Both services turn existing agreements into structured data and keep a person in the verification step before automation. Their surrounding workflows differ more than that shared control. Contractbook combines template based drafting and AI clause rewriting with a detailed HubSpot flow, connecting a sales deal to a draft and returning contract information after execution. Contractify places more emphasis on delegating obligations across departments and uses drafting partners alongside its own repository, approvals and signing flows. Plan names alone are misleading: each has a Centralize tier, but Contractbook's package is part of a structure with template and annual signing limits, while Contractify's Centralize tier is capped at five seats and higher packages add signing and richer AI functions. The products organize contract creation and the work after signature around those different allowances.
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.
AI Import reads existing contracts, extracts structured fields and helps turn a collection of files into a usable agreement database. The Contract Assistant adds plain language questions, summaries, risk identification and clause revisions. Both operate inside a wider application with template drafting, collaboration, electronic signatures and ongoing contract management. Templates and configured workflows still handle repeat agreements independently of the assistant. Customers can combine the extracted dates and obligations with reminders, while CRM data populates new agreements. Essential includes the assistant; higher plans add broader data extraction, custom fields, automation and team administration around these AI functions.
Ada reads uploaded agreements and related material, including general terms, addenda and nondisclosure agreements, to suggest parties, dates and renewal details. Users can ask questions about clauses or request a summary, then add the response to the shared contract record. These model functions turn unstructured text into information that drives tasks and reminders. The surrounding repository, approval routes, signature connections and access controls also perform ordinary contract management work. Centralize includes an AI timeline; Collaborate adds summaries and contract chat; Control adds portfolio retrieval and custom prompts. Contractify therefore combines model assisted analysis with a broader workflow and storage application.
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.
AI Import connects extracted data to the text it came from. Selecting a purple field in the sidebar moves the reader to its exact location in the original agreement and highlights the passage. Users can inspect individual values or verify all fields together, and the repository marks completed verification. Import first processes the uploaded files and extracts their contract data, with OCR included for relevant files. This is source based verification of customer agreements, rather than a legal citator. No test set, measured accuracy result or explicit unsupported answer behavior accompanies the Contract Assistant's broader clause recommendations.
Suggested contract values point to the place Ada found them, allowing a reviewer to inspect the supporting text before saving the result. The assistant also draws on agreements and metadata in the customer's environment when answering questions about renewals, suppliers or individual clauses. These features ground extraction and contract questions in source material. They do not establish an independently measured error rate. Version 15 of the service terms warns that automatically generated output can be incomplete or inaccurate and requires customer verification. A current reproducible evaluation of extraction accuracy, invented answers or performance across languages is not specified.
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.
An AI import can be canceled during upload, OCR or extraction, and the canceled file is discarded. After processing, a reviewer checks the proposed data against highlighted source text and marks the fields verified. That verification can become the trigger for a reminder or a move into a shared space. Users need the relevant company permissions to import files and manage custom contract types. Template workflows also support approval steps before signing. These controls give teams review and cancellation surfaces, but the assistant has no stated confidence cutoff or defined escalation path for an answer that cannot be supported.
People verify and save Ada's proposed contract data, and automatic follow up tasks use the approved values. A user can place chat responses on the summary page and assign follow up to the responsible parties. Contract approval and signature flows add separate business review steps, while administrators control who can edit or manage agreements. The service terms require verification and human intervention, and prohibit using Ada for automated decisions under Article 22 of the GDPR. This gives reviewers identifiable control points. A confidence threshold that stops a review, an AI failure escalation route and a correction procedure after an incorrect automated task 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.
Bizzkit's compliance officer describes saving 15 to 20 hours extracting data from about 50 legacy data processing agreements. That is a named example of AI extraction in use, with the time estimate supplied by the customer. Lenus separately describes reducing contract preparation from 15 minutes to five through templates and integrations with Salesforce, Greenhouse and HiBob. Those automation results are not presented as a measurement of the newer Contract Assistant. GANNI and Pave also discuss repository and extraction benefits. No dated comparative study isolates the assistant's effects on review quality or legal outcomes.
Meat & More uses Contractify to centralize agreements and attachments, delegate tasks and receive notices for commercial leases and supplier contracts. Its legal case describes more than 200 agreements previously tracked in spreadsheets, over 50% less time spent on legal follow up and more than €40,000 avoided on sales agreements in one department. These are results for the contract management workflow, without a stated study date or measurement method. Vivaldis also describes centralized access and timely notifications. Ada's separate efficiency illustration compares manual registration with assisted analysis, but does not identify a customer or a current model evaluation behind that comparison.
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.
Section 9.12 of the service terms bars AI model training on retained platform data unless the customer gives consent in writing or through the application. Confidential information is limited to service delivery and remains protected after termination. AI imports start in the user's private contract view, while sharing depends on the application's space permissions. Google Cloud hosts platform data and Azure hosts the language model, both with EU locations in the processor list. Privilege and work product handling are not addressed directly, and the terms do not specify what the model provider retains from individual prompts or responses.
Customer information remains the customer's property, and the service terms impose continuing confidentiality obligations on both parties and their staff or subcontractors. Contract access can be restricted by individual agreement, folder or project. Section 3.4 permits model training only with prior, separate written consent, while the AI clause and DPA state a prohibition on using uploaded data for training. AI providers must also exclude training or keep it disabled. Prompt processing can involve temporary retention for abuse prevention. Return and deletion obligations apply at exit, but attorney client privilege, work product handling and enforcement of source system ethical walls are not specified.
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.
The service is restricted to business activity and is not offered to consumers. Section 8 describes the supplied templates as drafting inspiration rather than legal advice, and the company profile makes the same tooling distinction for the product. Legal teams can control templates, approvals and shared spaces while other employees generate routine agreements. The customer remains responsible for using suitable agreements and deciding whether electronic signatures are appropriate. No jurisdiction specific competence guidance or named professional supervision standard accompanies the assistant. Its explanation and rewriting features therefore sit inside the customer's own legal review and contracting responsibilities.
Ada's output is expressly described in the service terms as neither legal nor commercial advice, and customers remain responsible for verifying it. The same clause prohibits using the AI functions for automated decisions under Article 22 of the GDPR without human intervention. Product instructions give that responsibility a concrete step: a person verifies and saves proposed contract values before they drive follow up. Legal teams can retain oversight while distributing routine tasks to other departments. Named professional conduct rules, jurisdiction specific supervision duties and limits on which legal questions the assistant may answer are not set out.
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.
Contractbook's trust center describes security policies, change management and an incident response program. Management reviews that security program at least annually, and production data is restricted in development and testing environments. The AI features separately support source highlights, user verification and consent for model training. None of these materials sets out an AI release evaluation process, a responsible AI framework or results showing uneven performance across contract types or user groups. The page titled AI Policy Page is a company and product profile for automated readers, rather than a policy assigning accountability for the behavior of the language model.
Contractify's July 2026 AI implementation guide describes ground rules for human review, permitted data and product limits, illustrated through Ada. It explains that a person validates extracted information and that answers draw on the customer's agreements and metadata. The account of Ada's initial pilot names time saved, extraction accuracy and correction volume as criteria. That historical pilot is separate from a continuing evaluation program for the current model stack. An accountable AI governance owner, release approval framework and results on uneven output across languages or contract types are not specified. The security program concerns infrastructure and data protection.
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.
Customers can remove or archive their own data through the application and request removal at termination. Signature verification information has separate retention rules and generally requires all signers' consent before deletion. The privacy policy gives a general service data retention period with legal exceptions, while the processor list identifies providers, roles and locations. Space permissions, encrypted storage, logging and a trust center incident plan add operational controls. Confidentiality breaches require prompt notice under the terms. A specific retention window for assistant prompts and outputs, together with a deletion schedule at the model host, is not stated.
AI subprocessors may keep prompt data for abuse prevention for at most 30 days, subject to longer legally required retention. The DPA requires return or secure deletion within 30 days after processing ceases or the agreement ends, with written certification. Routine database backups have several intervals, extending to an annual copy kept for one year. Access controls distinguish user roles and restrict contracts, folders and projects. Named subprocessors have stated functions and locations, and new providers require notice. A suspected or known personal data breach must be reported immediately and within 48 hours, with investigation, mitigation and coordinated communications.
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 limits liability to fees paid in the 12 months before the first claim arose. It excludes lost profit, business opportunity, third party liabilities, data loss and several other categories of loss, and supplies the service as is. Death or personal injury caused by negligence, fraud and fraudulent misrepresentation are outside the stated limitations. The customer, rather than the vendor, gives the agreement's indemnity. Contractbook promises customary insurance without naming its amount or scope. These provisions do not provide a specific warranty or recovery route for a mistaken AI clause explanation, extraction or revision.
The terms promise material conformity with the agreement and give DB2 options to contest an intellectual property claim, modify the software or refund the unused fee after taking it back. General liability is capped at the greater of the previous 12 months' fees and €25,000, with exceptions for death, injury, fraud, intent and gross negligence. A confidentiality breach carries €5,000 compensation. The DPA separately provides mutual indemnities for its breach, limited by insurance payment or previous annual fees. AI output still requires customer verification; a specific remedy for an incorrect AI answer and the insurer's policy scope are not stated.
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 HubSpot integration moves deal and company data into contract templates and can synchronize negotiated values back after signing. Setup requires defined template fields, the appropriate Contractbook template or company permissions, and specified HubSpot CRM, product library and marketplace rights. The administrator connects the accounts through Integrations and accepts the requested permissions, then configures triggers and actions. HubSpot quotes can become attachments, and its widget displays contract status and activity. Disconnecting unpublishes related automations without deleting generated files. Salesforce, API access, Zapier and Make extend other workflows, with availability and charges varying by plan.
JuriBlox and Clausebase provide drafting connections, while Nitro Sign and DocuSign support signature flows. The JuriBlox arrangement moves from template based contract preparation into Contractify approval, signing and follow up. The public API supports personal access tokens or OAuth authorization, and webhooks send resource identifiers that an integration uses to retrieve full records. Webhook signatures, retry timing and manual redelivery are specified. These are usable components for connecting business systems. Detailed field mapping, permission behavior and failure handling for the named drafting and signature connectors are less explicit than the general API mechanics.
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.
Contractbook runs as an online contract workspace with organization accounts, shared spaces and individual access rights. The subprocessor list places Google Cloud platform hosting and Azure language model hosting in the EU. It also identifies United States services for email, messaging, monitoring, traffic management and integrations, so the EU hosting entries do not describe every supporting data flow. The privacy policy permits transfers outside the EU and EEA with safeguards. No country selection, customer hosted installation or private tenancy option is specified, and the available material does not allocate storage and processing locations separately for each subscription plan.
The hosted application keeps primary data in DigitalOcean's Frankfurt facility and backups in Amsterdam and Dublin. The current provider register distinguishes storage from AI processing: OpenAI is in the United States, Mistral handles text recognition and structure in France, and Microsoft Azure processes AI work in Switzerland. Other providers support signatures, customer service, analytics and communications. The DPA sets conditions for international transfers and incorporates named recipients. The main storage locations are therefore more specific than a general European hosting claim, but customer region selection, deployment alternatives and residency differences between subscription packages are not 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 security page states SOC 2 compliance and describes recurring penetration tests, encrypted credentials, verified accounts and two factor signing. A Secureframe trust center offers a SOC 2 report through a request control and lists security policies covering access, change management, risk and incident response. Its public material does not identify the assessment period, report type, auditor or detailed system scope. The separate Openli profile could not be accessed, so any material there remains unknown. Customer signatures and identity controls support contract execution, while the SOC 2 claim addresses service controls rather than measured accuracy of the AI assistant.
Security controls include encryption in transit and at rest, database access restrictions, temporary file links, two factor authentication, activity logging and annual penetration testing. The security sheet names ISO 27001 and other certifications held by DigitalOcean, and points to Amazon's certificates. Those attestations concern hosting providers rather than a defined Contractify service scope. Contractify's terms offer current security material and any available independent reports on request once per contract year, while penetration test results are also available on request. A specific independent certification, audit period or assurance report covering Contractify itself is not identified.
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.
Microsoft Azure hosts the large language model used for the product's AI functions, with the processor list assigning that service an EU location. Google Cloud is separately responsible for storage and platform hosting. The application combines document import, OCR, field extraction and a conversational contract assistant, but the specific model name and version are not identified. The terms require customer consent before retained platform data is used for model training. A general notice rule for contractual updates does not provide a specific commitment to notify customers about model replacements or changes to the inference supply chain.
The current subprocessor register identifies OpenAI and Microsoft Azure as generative AI service providers. It also names Mistral for optical character recognition and document structure analysis, and Meilisearch for vector retrieval. Processing locations distinguish OpenAI in the United States, Mistral in France and Azure in Switzerland. The terms require provider training to be excluded or disabled and limit temporary abuse monitoring retention. Customers receive notice of new subprocessors under the DPA. Exact model families and versions, the routing of a particular task among providers and a commitment to notify customers of model substitutions are not specified.
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.
Essential, Centralize and Accelerate include one, five and ten users, with annual signed contract allowances of 100, 350 and 500. Template limits are five, 15 and 25. The current pricing page shows no base subscription amount; a company profile updated in March 2026 gives a starting rate of €89 per month. The pricing FAQ lists five extra users at €50 per month, or €600 annually. Automation and provisioning are optional for Centralize and included in Accelerate, while several integrations cost extra. Custom setup uses a quote, and the terms provide for upgrades or additional charges when usage limits are exceeded.
Subscriptions charge for a package and seats, with annual advance billing. Centralize has a fixed maximum of five seats shared between users and viewers. Collaborate starts at five users and Control at ten, with user and viewer seats billed separately. Signing allowances are 200 and 500 respectively in those higher plans, while stored contracts are unlimited. Adding seats requires an administrator to confirm a billing warning; deleting or blocking a user does not itself reduce the contracted quantity. Downgrades need 30 days notice before renewal. Subscription amounts, extra seat rates and implementation charges still require the customer's quote.
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.
Small and midsize sales, legal, HR and operations teams use the platform for standard recurring agreements such as NDAs, sales contracts and employment agreements. The Lenus case describes legal counsel setting templates and boundaries for colleagues across several markets. Bizzkit uses extraction for legacy data processing agreements, while GANNI and Pave describe contract visibility and renewal work. The company focuses on European markets and also offers industry pages for government, healthcare, construction and procurement. Its own profile excludes legal advice and simple one off signing as its intended role, without supplying a jurisdiction by jurisdiction support matrix.
Legal, finance, procurement, management and IT teams use the service for their organization's agreements. Its legal workflow gives counsel oversight across entities while other departments own tasks and signing responsibilities. Named examples include commercial leases, supplier agreements, sales contracts and employment information. Ada handles contract data, summaries and questions, with language coverage described broadly rather than through a tested language list. Draft creation also relies on connections such as JuriBlox and Clausebase. Specific law firm segments, jurisdiction boundaries and unsupported agreement types are not defined, and the standard license is for internal business use.
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?
Section 9.12 prohibits use of retained platform data for AI model training unless the customer consents in writing or through the platform. Section 9.1 separately refers to anonymized development data where consent has been given. The general service processing license covers delivery, maintenance, fixes, security and legal obligations. It does not override the express training consent requirement, and no default training permission is stated for a new customer.
Section 3.4 of the service terms permits training on uploaded content only after prior, separate written consent. The agreement's AI clause and the DPA also state that uploaded data will not train models, and provider training must be contractually excluded or kept disabled. Contractify uses customer material in prompts for that customer's own environment. A separate consent is also required before particular files are used to investigate a technical issue.
Prompt and Output Retention
How long does the product keep what a lawyer typed, and can that be set to zero?
Customers may remove or archive their data at any time through the platform under section 9.4, and may request removal of their own data when the agreement ends. Signature verification information follows a separate rule requiring signer consent. The privacy policy supplies a broader service data retention period with legal exceptions. No explicit zero retention setting or separate fixed period for assistant prompts and answers is specified.
AI providers may retain prompt data for abuse prevention for up to 30 days, with an exception for longer legal obligations. The application keeps contract information during service, and routine database backups include an annual copy retained for one year. Personal data must be returned or securely deleted within 30 days after processing stops or the agreement ends. A separate application chat history period or customer setting for prompt retention is not specified.
Ethical Walls and Matter Segregation
Does retrieval respect the firm’s ethical walls, or can the model read across them?
AI imports are private in the importing user's contract view until shared directly or moved to a shared space. Space access separates viewing, contract management and space management, while external collaborators receive view rights only. Company user groups can also receive access, with direct permissions surviving removal from a group. This is Contractbook's own access model, without an identified connection that inherits a firm's document system ethical walls.
Access can be granted or restricted at the contract, folder or project level, with administrator, manager, user and viewer roles. Control adds custom privilege sets, and administrators can block users or reassign responsibilities. The terms limit generated content to the same customer's environment. These are Contractify's own permissions; inheritance of a connected document system's matter walls and enforcement of those external permissions during AI retrieval are not specified.
Third Party Request and Subpoena Notice
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
Section 9.8 requires written notice before legally compelled disclosure whenever possible. The confidentiality clauses also permit information to be supplied to other signers of an agreement completed through the platform. The privacy policy covers legal obligations and requests from authorities. No transparency report accompanies these commitments. The separate Disclosure Policy concerns security vulnerability reporting and does not describe the handling of subpoenas or other demands for customer contracts.
The DPA requires Contractify to inform the customer before processing personal data to meet a legal requirement, where the law permits. Its breach provisions also coordinate legally required notifications and allow the customer to comment before disclosure when possible. The privacy statement permits disclosure to authorities or in legal proceedings. A broader process for nonpersonal confidential material, a challenge policy and a transparency report are not specified.
Primary Law Corpus Provenance
Where does the law in this product come from, and does the vendor have the right to use it?
AI Import processes the customer's legacy agreements and points extracted fields back to text in those files. The contract assistant also works with the selected agreement, while customers can create templates or use the vendor's template library. No licensed case law or statute collection is identified for those functions. The supplied templates are drafting material, and the agreement expressly distinguishes them from legal advice for the customer's situation.
Ada draws on the customer's uploaded contracts, attachments, general terms, addenda and stored metadata. Extracted values point to their source, and questions can retrieve clauses or renewal information from those agreements. Customer ownership remains intact under the service terms, with a limited right for Contractify to perform the service. An external legal authority collection, its licensing basis and the underlying model training corpus are not identified.
Good Law Verification
Does the product tell you when the authority it just cited has been overruled?
The platform's verification feature checks extracted information against the source contract, with highlighted passages and a completed verification marker. It does not track judicial treatment of cases or statutory amendments. The assistant can explain and rewrite clauses, but no connection to a legal citator or warning that an authority has been overturned is specified. Renewal reminders and signature status concern the agreement's lifecycle, rather than the legal status of an authority.
The assistant extracts contract parties and dates, identifies clauses and produces summaries from agreements in the customer's workspace. Source references help a person check an extracted value against that agreement. These functions do not include checking subsequent treatment of court decisions or whether a statute has been superseded. A citator connection, authority status warning or jurisdiction specific good law check is not part of the stated workflow.
Refusal and Uncertainty Behavior
What does the product do when the answer is not in the corpus?
Reviewers can inspect AI extracted fields beside highlighted source passages and verify them individually or together. They can also cancel an import during processing, which discards the file. These controls let a person check the extraction, but no explicit unsupported answer response or confidence indicator is described for the conversational assistant. The option to stop an upload is a user action, not a model refusal when information is insufficient.
Ada can answer whether a requested clause appears in an agreement and show where extracted information came from. A person verifies the proposed values before saving them, and the terms warn that generated output may be incomplete or inaccurate. An explicit abstention response for unsupported questions, a confidence threshold or a defined route for unresolved uncertainty is not described; reporting that a clause is absent is a narrower function.
Fabricated Citation Record
Does a public court record exist addressing fabricated or hallucinated legal citations in output from this product?
No court order or disciplinary record concerning fabricated legal citations from Contractbook appears in the AI Hallucination Cases database. The product extracts data from customer agreements and offers questions, summaries and clause revisions within its contract workspace. That database result does not measure extraction or drafting accuracy. Its source highlights support a user's review of contract data, without constituting a check of every legal assertion produced by the assistant.
The AI Hallucination Cases database contains no tool entry naming Contractify, DB2 Value Creation or Ada as of October 15, 2026. The assistant sits within a contract management platform used by legal and business teams for approval, signing and renewal work. Its stated AI functions cover extraction, summaries and agreement questions, with reviewers responsible for checking proposed values before they enter the shared contract record.
Bar Guidance Alignment
Has the vendor engaged in public with the ethics opinions its buyers are bound by?
The service terms limit the platform to business users and explain that the template library does not provide legal advice. Legal departments can control templates, permissions and review steps for other employees. No named bar opinion, jurisdiction specific competence requirement or product mapping to professional ethics guidance accompanies these controls. The statement that the service is a business tool does not specify how a lawyer should record supervision of its AI functions.
The AI terms require customers to verify output, disclaim legal advice and rule out automated decisions under Article 22 of the GDPR without human intervention. Contractify's AI implementation guide also discusses human validation and European AI Act considerations for deployments. These are general operating and regulatory responsibilities. A named bar opinion, legal professional conduct rule or jurisdiction specific guidance on lawyers' use of the assistant is not identified.
Billing and Fee Posture
Does the vendor address what happens to the bill when the work takes an hour instead of six?
The stated buyers are business teams managing their own sales, employment, supplier and compliance agreements. Named legal customers include internal counsel at Lenus, GANNI and Pave, and the product describes savings in their contract administration. Bizzkit reports less manual extraction work on legacy agreements. No law firm client billing workflow is identified in the current buyer materials, and those savings relate to the organization's own time and contracting costs.
The standard license covers the customer's internal business purposes, and the legal team examples concern managing the organization's own agreements. Meat & More reports over 50% less time on legal contract follow up, while Ada's efficiency examples compare the buyer's administrative cost with assisted work. Those savings concern an internal department's workload. A law firm's fee to an external client is not part of the described transaction or deployment.
Outside Counsel Guideline Readiness
Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?
The processor register names Google Cloud for platform hosting and Azure for the language model, both in the EU, alongside supporting providers and their locations. Customer terms set a training consent requirement and confidentiality duties. The data processing agreement is generated through a workflow that requests customer details and acceptance of terms. No separate client consent pack or exact model version inventory accompanies the public processor register.
The legal hub identifies service providers, hosting locations and processing functions, including OpenAI, Azure, Mistral, DigitalOcean and signature providers. The DPA requires notice when a new subprocessor is engaged and binds those providers to equivalent protections. Security material and available reports can be requested annually, and customer audits are allowed under the DPA. A ready made client disclosure memorandum or outside counsel guideline response package is not specified.
Court Disclosure Support
If a judge’s standing order requires an AI disclosure, can the product produce one?
Imported agreements retain extracted fields, highlighted source passages and a verification state that users can inspect in the contract view. The application also tracks versions, collaboration and signature activity. These elements provide part of the record of a user's review, without a specified export connecting each AI response to its model version and a named human verifier. No court specific certification form or complete AI disclosure bundle is described.
Proposed contract values link to their source and are verified before saving, while version control and an audit trail preserve parts of the contract workflow. Security logging also covers sensitive user actions and API activity, and customers can request an export of their data. The service does not specify a per agreement package identifying the model used, retrieved sources and the person who verified each generated passage for a court filing.
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 Contractbook if
- HubSpot deals should populate drafts and receive contract information after signing.
- The team needs template drafting and AI clause rewriting in the contract workspace.
- Defined template and annual signing allowances fit the team's workload.
Choose Contractify if
- Legal needs oversight while business departments own renewal and obligation tasks.
- JuriBlox or Clausebase already supplies the contract drafting workflow.
- The repository needs unlimited stored agreements with granular project and folder access.
In summary
Contractbook
Contractbook brings drafting, review, execution and an agreement repository into one workspace. Users build contracts from templates, collaborate on approvals and use a Contract Assistant to answer questions or rewrite clauses. The AI Legal Index highlights how AI Import attaches extracted fields to source highlights and requires verification before those fields drive automation. A HubSpot workflow maps deal information into drafts and sends contract data back after signature. Shared spaces organize access and collaboration, while new imports initially remain private. Subscription tiers distinguish seats, template counts and annual signing volumes, so their allowances affect both contract creation and ongoing management.
Contractify
Contractify emphasizes organizing agreements and assigning the follow up work they create. Ada suggests parties, dates and renewal information from contracts and attachments, points reviewers to the source, and turns approved values into tasks. The AI Legal Index identifies that link between validated data and assigned responsibilities as a defining workflow. Chat responses can also become summaries shared with colleagues. Drafting partners include JuriBlox and Clausebase, while Nitro Sign and DocuSign support execution. Plans include unlimited stored contracts but separate user, viewer and signing allowances. Document, folder and project permissions let legal and business departments work within one repository.
Questions buyers ask
What must a person check before automation?
Contractbook asks users to verify extracted fields against source highlights. Contractify lets a person inspect and save Ada's proposed values, then creates follow up from the approved data. Neither workflow makes every generated answer automatically correct. From the AI Legal Index, based on each vendor's own published materials as of October 15, 2026. No vendor pays for placement.
Does Contractify include the same drafting workflow?
Contractify names JuriBlox and Clausebase as drafting connections before its approval, signing and follow up stages. Contractbook creates contracts from templates within its workspace and offers clause rewriting through its Contract Assistant. From the AI Legal Index, based on each vendor's own published materials as of October 15, 2026. No vendor pays for placement.
Do the two Centralize plans mean the same thing?
No. Contractify Centralize has at most five seats shared between users and viewers and excludes the signing features in higher plans. Contractbook Centralize has its own allowances for users, templates and annual signatures. The shared label does not establish equivalent scope. From the AI Legal Index, based on each vendor's own published materials as of October 15, 2026. No vendor pays for placement.
Does unlimited contract storage remove other limits?
Contractify includes unlimited stored contracts, but still distinguishes paid seats, AI functions and signing allowances. Contractbook also differentiates subscriptions through specific plan allowances. Storage capacity alone therefore does not describe what a team can create, sign or automate. 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.
These are two products in the contract review and drafting category. Contractify's own Contractbook comparison establishes the pairing; product details were checked against each company's current material. Neither company reviewed this page, and no hands on output test was performed. Contractbook belongs to Scrive; Contractify joined Anchr in 2024.