DraftPilot vs Luminance: how they compare in 2026
DraftPilot and Luminance both let legal set standards for contract review and give approved business teams a bounded role. Their differences concern the context and surrounding process. DraftPilot turns existing legal material into playbooks used in Word, with particular controls for later negotiation rounds, reviewer permissions, and exceptions. Its portfolio review and cited research support analysis alongside that editing work. Luminance brings previous concessions, accepted language, and the same counterparty's history into a new negotiation. It combines those precedents with playbooks and structured checklists, then connects review with contract intelligence and workflows spanning intake through signature. DraftPilot fits a team extending a familiar Word process with shared standards and analysis. Luminance offers a wider contract system when the goal is to circulate negotiated knowledge and operational context across legal, procurement, finance, and sales.
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.
DraftPilot's main product is model driven review and drafting inside Word. A selected playbook supplies preferred positions and fallbacks; the AI identifies departures, proposes language, and explains changes to the reviewer. The same models generate playbooks from past work and support conversational drafting, comparison, and research. Mass Review uses AI to answer questions across agreements and connect findings with source language. Conventional functions such as workspaces, permissions, and file conversion support that workflow, but they are not an independent contract management system. Removing the models would remove the review, analysis, and drafting service that customers buy.
Luminance uses models throughout contract interpretation, negotiation and portfolio analysis. Luna Crescent specializes in extraction, classification and other repetitive legal tasks, while additional models handle work that benefits from broader generative capabilities. A routing layer selects the model for each task, and separate validation models test important answers. The repository connects agreements and amendments into context for later questions, and negotiation uses prior concessions and approved positions to generate markups. Workflows turn those findings into contract actions across legal and business teams. The central service depends on model generated understanding of contractual language and relationships, rather than a template library alone.
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 Chat uses a curated legal network containing legislation, secondary sources, and commentary, with general web access excluded from legal research. Its research guide instructs users to specify the jurisdiction and inspect the list of source links used in an answer. Research can then become proposed changes to the contract, subject to reviewer acceptance. Mass Review separately lets users inspect the contract language underlying a table result. Published totals for the research network differ between the FAQ, guide, and trust center. No reproducible accuracy test, source freshness method, or systematic citation treatment results accompany those totals.
Luna Crescent is tested against ContractIQ Bench, with 189,000 manually annotated data points covering provisions such as liability caps, termination rights and confidentiality. Testing includes unseen concepts and blind review by legal specialists. Luminance claims 5 percent higher accuracy than leading general models without an absolute result or named comparators. Separate validation checks important outputs against model agreement, source evidence and task requirements. A failed check can lead to a retry and a visible request for human review. The model is also trained to identify missing information rather than fill the gap. Public sample tasks, a reproducible evaluation set and detailed error rates are not available.
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 enterprise workflow divides authority between legal and approved business reviewers. Legal owns playbooks, permissions, acceptable positions, and escalation rules; procurement or contract managers perform a bounded first review on agreed contract types. Issues outside the approved route return to legal or the appropriate specialist with the clause and business context. The product proposes tracked edits and comments in Word, which authorized reviewers can edit, accept, or reject. DraftPilot expressly describes this arrangement as something other than autonomous contracting. Its control boundary is organizational approval and exception routing, rather than a published numeric model confidence threshold.
Business users can generate and progress routine agreements under legal approved templates and role permissions, with nonstandard terms routed to legal. Proposed negotiation language appears in Word. For important AI outputs, a separate model or panel checks agreement, supporting evidence and task requirements. Every required critic check must pass; a failed check prompts another attempt using the feedback, followed by a review flag if the problem persists. Customer decisions and workflow actions retain an audit trail. The agreement requires manual interpretation of all results, and the AI terms require interfaces that support human oversight of the system's operation and limitations.
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.
Axiom's 2025 white paper describes an eight week pilot in which 18 volunteer attorneys used DraftPilot on client work after an evaluation of eight suppliers. Evidence came from surveys, product analytics, participant calls, and feedback sessions. Forty four percent of participants reported time savings in the 40 to 60 percent band, while 16 of 18 reported moderate or significant improvement in work quality. The vendor's case study also separates tasks such as drafting, issue spotting, and summaries. These are reported observations from motivated volunteers, not a randomized benchmark. Raising Cane's provides another named deployment involving real estate positions and lease review.
Current customer examples tie specific organizations to contracting work. AMD reports finding precedent language in under two minutes, Emma Sleep reports twice as many contracts reviewed per quarter, and Avianca claims 90 percent less document review time. Repository examples include Yokogawa's 99 percent faster response to business questions and Trench Group's two hour tariff analysis, compared with two weeks and about €11,000. Workflow examples include ProSapient reducing eight steps to three and Hitachi moving from NDA generation to signature in under five minutes. These are vendor presented customer results, without a common study protocol or dated measurement period. The current customer base exceeds 1,000 enterprises.
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.
DraftPilot states that customer material does not train its models or public models, and its security guide says original contracts are not stored after analysis. Playbooks remain in the customer's workspace, with permissions controlling their use and editing. OpenAI inputs and outputs receive the stated zero retention arrangement. The broader trust center also names Anthropic and lists 30 days for generated redlines and comments, which narrows the general no retention headline. No accessible commitment directly addresses attorney client privilege or work product. The linked customer terms require sign in, and the trust center requests access before releasing the service agreement or DPA.
Each customer has an isolated environment with separate workloads, data and layered access controls. The agreement treats private learning and outputs as customer property and confidential information, and limits support access to service delivery. It also licenses customer data for product improvements, private learning and usage insights; there is no general prohibition on learning from customer content. Private learning stays with that customer, while nonidentifying usage insights can be retained for improvement. Inputs sent to external models are permitted disclosures directed by the customer. Attorney client privilege and work product are not directly protected by a specific clause, and provider retention limits are not stated in the model list.
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 enterprise operating model keeps legal judgment with lawyers and approved specialists. Procurement and contract managers may conduct an initial review only within legal's chosen contract types, positions, and escalation rules. Suggested language remains subject to acceptance, and exceptional issues return to the legal team. This division keeps assistance separate from professional judgment and reserves consequential advice for legal. The research guide also asks the user to state a jurisdiction and intended use. Public pages do not define professional eligibility by jurisdiction or connect those controls to specific competence and supervision duties.
The master agreement prohibits treating the product as legal advice or a substitute for relevant independent or internal legal advice. All results require manual interpretation, and customers must tell third party users about those limits. AI Systems Terms add human oversight duties and describe the intended use as legal document analysis, research, contract analytics and legal workflows. The product also serves procurement, finance, sales and other business functions, with exceptions routed to legal. Specific lawyer competence procedures and supported jurisdiction boundaries are not stated. The license permits professional services firms to use the software when serving their own clients.
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.
DraftPilot's trust center publishes principles covering privacy in product design, human empowerment, and transparency through security certification. It also describes output protection, operational guardrails, and grounding of AI Chat in a verified source network. Those statements give a direction for responsible use but do not identify an accountable model owner, a release evaluation procedure, or results across languages and contract types. An AI Governance Policy is listed among resources that require access approval, so its contents cannot establish additional public controls. Customer playbooks and escalation rules govern a customer's review process; they do not disclose the vendor's own model testing.
AI Systems Terms require ongoing risk management, records of risks and tests, and data governance that considers bias, representativeness and missing data. The model evaluation process includes task benchmarks, complete workflow testing through ALumNI, blind expert review and a human sign off before a reversible production rollout. Luna Crescent releases must clear ContractIQ Bench and expert review before replacing a current version. These controls extend beyond the information security program and address model behavior before release. An individually accountable AI governance owner and results showing uneven performance across matter types, parties or populations are not specified.
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.
Public resources distinguish contract analysis from stored customer configuration. The security guide says playbooks normally reside on AWS in Ireland and describes immediate deletion of OpenAI API inputs and outputs. The AI posture page separately lists 30 days for generated redlines and comments. Administrators use SSO, SCIM, workspaces, and permissions to control access. Twelve subprocessors are named with service roles, including hosting, model, email, analytics, and business operations providers. Encryption is specified for transit and storage. However, a complete deletion process for retained playbooks, a binding incident notification period, and the DPA terms are not available in the readable public material.
Customers can delete data during use, with removal from active stores within 30 days and backups within a further 30 days; faster deletion can be requested. Routine backups occur every 24 hours, remain within the hosting region and are kept for 14 to 28 days under the master agreement. Access follows least privilege, with multifactor authentication, optional single sign on and isolated customer workloads. The subprocessor list names hosting, model, support and operations services. New providers require 30 days notice and allow 15 days to object. The data agreement requires notice of a personal data breach within 24 hours, mitigation and information about the affected records and likely consequences.
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.
DraftPilot links to customer terms on SharePoint, but the linked document leads to a Microsoft sign in page. Its public trust center lists a Master Services Agreement and DPA behind an access request. As a result, no readable contract establishes liability caps, indemnity scope, an AI output warranty, or remedies for an incorrect clause or research answer. This is an access limitation, not evidence that the negotiated agreement lacks those provisions. The published review workflow allocates final decisions to authorized people, but that operational allocation does not reveal what financial responsibility DraftPilot accepts when its service makes an error.
The October 2026 master agreement provides an IP indemnity for the product, with exclusions for unauthorized combinations, continued infringing use and unsupported versions. A performance warranty allows correction, replacement or a refund of unused prepaid fees. General liability is capped at the previous 12 months' fees, rising to three times that amount for specified data obligations. Confidentiality and IP ownership breaches are outside those caps, and certain legally nonexcludable losses remain protected. Claims require notice within nine months. The agreement separately disclaims losses caused by output errors or omissions and treats customer directed model transmissions as permitted disclosures. No insurance commitment is specified.
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 Microsoft Word connection has a described installation and editing path. Users install the add in through AppSource or central IT deployment, open it from the Word ribbon, and work with the agreement already being negotiated. Proposed language becomes native tracked changes, while explanatory comments accompany the edits. Reviewers can accept, reject, or alter individual suggestions and handle later rounds by focusing on counterparty changes. AI Chat can insert drafting or tables into the same file. Workspaces and identity controls manage product access. No comparable public sync specification describes a connection to a legal document management repository.
Negotiation generates context based markups directly in Microsoft Word using approved language, earlier concessions and comparable agreements. The workflow product connects contract actions, tasks and approvals across business teams and lets other assistants access contract capabilities through MCP. Users can initiate analysis, summaries and reviews from connected applications. The platform also names Outlook, DocuSign and LexisNexis connections. Its technical terms allow uploads from document management systems and virtual data rooms. Connector specific configuration, permission inheritance and the exact fields moving in each direction are not explained. These connections bring AI contract work into existing applications while retaining the central agreement record.
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.
DraftPilot is delivered through a Word add in and a browser interface, with hosted services handling analysis and team configuration. Its security guide places default playbook storage on AWS in Ireland and offers United States only hosting on Enterprise. The subprocessor list separately identifies Heroku in Ireland and OpenAI and Anthropic in the United States. Those provider locations do not establish where every model request is processed. The guide's OpenAI zero retention statement addresses persistence, not processing geography. Public materials therefore identify hosting choices and part of the provider chain without a complete regional account for all AI tasks.
The standard hosted product runs in an isolated customer environment on AWS. Customers choose an available AWS data center through the order form, with backups in the same region and recovery objectives of 24 hours for a complete primary data center failure. Additional inference can run on AWS, Azure or Google infrastructure. Azure and Google processing follows an EU or UK hosting choice; other hosting choices use an unspecified international location. Direct OpenAI API processing takes place in the United States. The complete available hosting region list and routing of each model task are not specified, and a storage choice alone does not fix every processing location.
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 public trust center names SOC 2 Type II and ISO 27001, with an ISO 27001:2022 certificate and a SOC 2 report listed as resources. Both require access approval, so their audit periods, organizational scope, and qualifications are not visible in the accessible pages. GDPR and UK GDPR are presented as compliance frameworks rather than independent security certifications. Additional resources include a network diagram and CAIQ Lite questionnaire, also behind requests. Product pages specify AES 256 encryption at rest and TLS 1.2 in transit. These published controls support the security description but do not replace examination of the underlying reports.
ISO 27001:2022 covers the information security management system for development, sales, support and operation, including the Cambridge technical headquarters, remote workers and cloud processing. SOC 2 Type II examinations cover security, availability and confidentiality, alongside independent penetration tests. Contractual measures include encrypted storage and transport, nightly operating system updates, daily backups, least privilege access and a dedicated data protection officer. Senior leaders review the security program quarterly, and a security advisory board supports it. Audit information and certificates are available through the contractual review process. The auditor names, report dates and examination periods are not specified in the current assurance statements.
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 main FAQ identifies OpenAI as the provider behind the contract workflow. The trust center supplies a broader inventory: GPT 4 Turbo with an April 2024 version identifier, and Anthropic Claude 3.5 Sonnet with an October 2024 identifier, both accessed through APIs. The subprocessor list confirms both companies and associates them with AI services. The security guide explains OpenAI's zero retention arrangement, but does not extend that provider specific statement expressly to Anthropic. Public material does not map every feature to its active model or commit to customer notification when a model changes. The inventory therefore discloses providers without a complete change framework.
Luna Crescent is a family of proprietary legal models developed from a general foundation model and specialist contract training. It works alongside other models selected by task through benchmarks and expert review. The subprocessor register identifies AWS, Microsoft Azure and Google Cloud for inference inside cloud environments, plus direct OpenAI API processing in the United States. The AI terms distinguish models hosted within infrastructure from requests sent to an external model provider. New subprocessors require advance notice, but the individual foundation models, versions and task routing remain unspecified. No equivalent notice commitment covers every model substitution within an existing provider.
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.
DraftPilot Pro starts at £7,200 per year for a minimum of three users, equivalent to £2,400 per user annually. A separate Customer Success Advisory Fee applies without a published amount. Everyday review and chat are unlimited under the package, while Mass Review includes an allowance and optional additional capacity. Pro includes playbooks, workspaces, identity controls, onboarding, and optimization support. Enterprise uses a negotiated organization package with tailored deployment and ongoing support. The posted subscription amount is therefore a real entry point, but it is not the complete first year cost because advisory charges and additional portfolio analysis remain unspecified.
Subscription allowances measure the number of files held in the product, and each version counts as a separate document. Annual uploads are subject to a fair use ceiling of twice the contracted document allowance, regardless of later deletion. Fees, payment timing and the initial term are set in the order form rather than a public rate table. Renewal ordinarily repeats the initial term unless either party gives 90 days notice. The standard increase ceiling is the annual Consumer Prices Index change plus three percentage points, unless the order form says otherwise. Assisted implementation and extra module prices are not specified.
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.
DraftPilot primarily addresses corporate legal departments handling repeatable commercial agreements. Its enterprise workflow also supports procurement teams and contract managers operating within legal's approved boundaries. The playbook materials cover agreements such as NDAs, services contracts, statements of work, data processing terms, and reseller arrangements. Axiom's deployment extends the audience to lawyers delivering client services, while Raising Cane's demonstrates lease and real estate work. The FAQ describes review across more than 58 languages, including applying a playbook in a different language from the agreement. That breadth is not accompanied by a jurisdiction by jurisdiction account of supported law or tested performance.
Legal, procurement, finance, sales, executive and HR teams use negotiation, repository analysis and workflows across commercial agreements. The license also permits professional services organizations to use the product for their clients and includes terms for United States government customers. The legal suite defines Corporate, Diligence and Discovery applications, while the AI terms describe legal document analysis, research, analytics and related legal workflows. Examples span NDA creation, supplier review, liability positions, tariffs and renewal obligations. Precise firm size segments, supported research jurisdictions, language limits and excluded practice areas are not stated. Current product positioning extends across an enterprise's contract work.
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?
DraftPilot's FAQ says neither it nor OpenAI uses customer data to train models. Its security guide extends that position to contracts and interactions, while the trust center repeats a no training policy. The public customer terms lead to a sign in page and the service agreement requires access approval, so no matching contractual prohibition was verified. The policy is explicit, but the readable evidence does not establish the scope of a binding customer term.
The master agreement licenses customer data for product improvements, private learning, usage insights and outputs. Private learning means recognizing new clauses and contract types from customer training; it belongs to the customer, remains confidential and is not shared across customers. Nonidentifying usage insights may be retained indefinitely for improvement. No general training prohibition overrides those rights. Inputs used with additional model features may also be transmitted to the named provider at the customer's direction.
Prompt and Output Retention
How long does the product keep what a lawyer typed, and can that be set to zero?
The AI posture page distinguishes original contract analysis, marked as having no retention, from generated redlines and comments, which it assigns a 30 day period. The security guide separately says playbooks are stored and OpenAI API inputs and outputs are deleted immediately under its zero retention agreement. These statements concern different data layers. No public setting lets a customer shorten the stored suggestion period or apply zero retention across playbooks and generated work.
Customers can delete data at any time. Active data stores remove it within 30 days, with backup removal within a further 30 days and expedited deletion available on request. The agreement also provides a 30 day period for retrieving and deleting data after the term ends. Routine backups have a separate 14 to 28 day retention period. No setting guarantees zero retention across application records, logs and external model processing.
Ethical Walls and Matter Segregation
Does retrieval respect the firm’s ethical walls, or can the model read across them?
Workspaces organize individual and team playbooks, and administrators determine who may view, use, or edit them. This gives legal a way to separate ownership of approved positions from business use of those positions. The public instructions do not establish matter based retrieval restrictions, conflict walls, or inheritance of a document management system's permissions. Playbook access controls therefore provide a narrower form of separation than a documented ethical wall around client files.
Each customer instance isolates workloads and data through logical, technical and access controls. Administrators configure roles, multifactor authentication and single sign on, while support access is limited to service delivery and may follow additional customer policies. The product applies its own access controls around the contract workspace. No current commitment describes inheriting an external document system's permissions at retrieval time or enforcing a law firm's matter level ethical walls.
Third Party Request and Subpoena Notice
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
No readable public commitment establishes whether DraftPilot tells a customer before responding to a subpoena or other demand for customer material. The current terms and privacy links lead to SharePoint sign in, while the trust center's service agreement and DPA require access approval. Its security controls and no training policy do not answer this notice question. The finding records the access limit and does not determine what the negotiated agreement might promise.
The confidentiality clause requires notice of legally required disclosure where lawful, giving the customer a reasonable opportunity to respond. Luminance must cooperate with reasonable efforts to resist, limit or delay disclosure at the customer's expense. A separate clause also requires prompt notice and cooperation when responding to a subpoena or judicial, administrative or arbitral order. No aggregate transparency report is specified.
Primary Law Corpus Provenance
Where does the law in this product come from, and does the vendor have the right to use it?
The research guide describes a curated network containing legislation, secondary sources, and legal commentary across more than 150 jurisdictions; the FAQ gives a larger jurisdiction total. Answers expose the links used, so the reviewer can inspect their immediate basis. A public inventory of named collections, licensing permissions, and update schedules is not supplied. The product therefore describes geographic reach and source categories more clearly than the rights and maintenance arrangements behind the research network.
Contract answers draw on customer agreements, amendments, negotiation history and the platform's standard legal concepts and clauses. Luna Crescent separately learns from more than 3.4 million proprietary legal data points, with an evaluation set of 189,000 annotated points. The customer retains its data and private learning. The sources and rights behind the general training collection, and any primary law collection used for legal research, are not identified individually or accompanied by an update schedule.
Good Law Verification
Does the product tell you when the authority it just cited has been overruled?
DraftPilot gives users a source list for research answers and asks them to identify the relevant jurisdiction. Those links allow inspection of the cited material, but the public research guide does not describe subsequent case history, treatment flags, or a licensed citator. A real source can still be superseded or limited by later authority. No product mechanism for resolving that separate currency question was identified in the research, FAQ, or trust material.
Negotiation and repository answers are grounded in contracts, amendments and earlier agreed positions. The AI terms also include legal research among the product's intended functions. No named commercial citator, subsequent history calculation or treatment flag accompanies that research description. Source grounded validation checks whether a response follows the supplied evidence, which is separate from checking whether a legal authority remains valid.
Refusal and Uncertainty Behavior
What does the product do when the answer is not in the corpus?
The trust center describes grounding and output safeguards, but it does not specify an abstention response when the curated network cannot support an answer. The Issues Report assigns risk to contract departures; that risk describes the agreement against a playbook, rather than model confidence or missing support. Reviewers can reject suggestions and inspect sources, yet those human controls do not show that the system itself refuses an unsupported legal assertion.
Luna Crescent is trained to identify information that is absent from the contract rather than invent it. Differential Validation separately checks important responses through independent model agreement or a source grounded critic. A failed check can trigger a retry using the identified problem; continued failure results in a review flag. The current explanation describes those behaviors without a public evaluation of their refusal rate or missed unsupported answers.
Fabricated Citation Record
Does a public court record exist addressing fabricated or hallucinated legal citations in output from this product?
The AI Hallucination Cases database maintained by Damien Charlotin contains no entry naming DraftPilot or Draft Pilot. The database concerns judicial decisions involving hallucinated AI material and records implicated tools when identified. DraftPilot does provide legal research as well as contract drafting, so source accuracy remains relevant even though its principal workflow concerns negotiation. The absence of a named case does not test its research answers, proposed clauses, or handling of later legal authority.
The AI Hallucination Cases database contains no court or disciplinary entry naming Luminance as the source of fabricated legal citations as of October 15, 2026. Luminance's principal workflows concern contracts, but its AI terms also include legal research. The AI Systems Terms require human oversight, and the master agreement assigns the customer responsibility for manually interpreting and using output, including checking its relevance to the particular legal task.
Bar Guidance Alignment
Has the vendor engaged in public with the ethics opinions its buyers are bound by?
DraftPilot gives legal control over approved positions, access rights, and exceptions, and it describes a supervised role for business reviewers. Those operating controls address practical oversight, but the published enterprise and research materials do not map them to a named bar opinion or jurisdiction's professional conduct guidance. In particular, no client consent method or fee treatment framework is tied to a specific professional rule. Product supervision should therefore be distinguished from demonstrated guidance alignment.
Professional services customers can identify mandatory requirements imposed on technology providers by their governing body before the order is signed. The master agreement commits Luminance to meet those requirements when compatible with applicable law, and permits regulatory access and assistance in specified circumstances. All output still requires manual interpretation. The agreement does not map these commitments to a named bar opinion or a particular lawyer ethics rule.
Billing and Fee Posture
Does the vendor address what happens to the bill when the work takes an hour instead of six?
Axiom's published DraftPilot offering attaches a $250 monthly technology fee to qualifying client engagements and explains that its lawyers use the tool to save time on contract work. Its white paper explicitly presents those gains as a client benefit. This identifies a disclosed software charge reaching the client through the legal service arrangement, rather than only an internal corporate efficiency claim. DraftPilot's own subscription pricing is separate, and no universal billing policy for other customers is stated.
Luminance licenses its product both for internal business work and for services delivered to clients. Current customer examples include faster precedent retrieval, shorter review and fewer workflow steps, while corporate deployments also report operational savings. The contract permits customers to earn revenue from the resulting output. No guidance connects the time saved to a law firm's client invoice, and the workflow audit trail is not presented as a legal time billing record.
Outside Counsel Guideline Readiness
Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?
A public register names 12 providers and their roles, including OpenAI, Anthropic, hosting, email, analytics, and business support services. The trust center also exposes policy summaries and lists a service agreement, DPA, security reports, and governance policy for access requests. These resources provide material for vendor diligence. They do not include a complete client notification or consent package explaining how a law firm's proposed use satisfies a particular client's outside counsel requirements.
The current list identifies AWS, Azure, Google Cloud and OpenAI for hosting or inference, plus named support and operations providers. It distinguishes processing inside cloud infrastructure from inputs sent directly to OpenAI and states broad processing locations. The data agreement requires 30 days advance notice of a provider change, with 15 days for objections. No separate client consent or outside counsel AI disclosure template accompanies the legal suite.
Court Disclosure Support
If a judge’s standing order requires an AI disclosure, can the product produce one?
Word tracked changes and comments preserve proposed revisions, while research answers expose their source links and the Issues Report identifies clauses, problems, risk, and possible responses. These are useful components of a review record. Inserted changes appear under the user's Office name, so the file alone does not label which work came from AI. No single export combines the generating model, retrieved authorities, and human verification for a court disclosure.
Workflows keep an audit trail of actions and decisions, and the AI terms require proportionate event logs retained for the agreement's duration. Important responses can carry a validation result or a request for review, with contract evidence behind the answer. The legal agreement also provides assistance to regulators. A per document export combining the exact model used, retrieved sources and a person's verification is not specified.
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
Which one fits
Choose DraftPilot if
- The deployment starts with an existing Word negotiation process and controlled reviewer groups.
- Lawyers want to focus later reviews on incoming changes while refining the playbook.
- The team needs portfolio questions and cited research beside its drafting workflow.
Choose Luminance if
- New negotiations should incorporate concessions previously made to the same counterparty.
- Review needs to connect with intake, signature, and enterprise contract intelligence.
- Procurement, finance, and sales should use the contractual context accumulated across agreements.
In summary
DraftPilot
DraftPilot focuses on the agreement in Word, applying positions derived from prior markups, templates, policies, or signed contracts. A later round can isolate the counterparty's changes while the lawyer continues to refine the playbook. The AI Legal Index identifies this connection between ongoing negotiation and editable review standards. Assigned business reviewers work within legal's boundaries, and the platform adds drafting chat, source linked research, and tabular analysis across groups of contracts.
Luminance
Luminance combines negotiation standards with the history of previous agreements, including concessions and language accepted with the same counterparty. That use of counterparty context is the finding highlighted by the AI Legal Index. Its negotiation tools create markups in Word, apply structured checklists, and route exceptions to legal. The broader platform connects negotiation with portfolio intelligence and contract workflows, making contract information available to commercial departments as well as the legal team.
Questions buyers ask
What previous negotiation information does Luminance bring forward?
It describes comparisons with earlier liability positions, concessions, and wording accepted with the same counterparty, as well as relevant precedents from the wider agreement portfolio. From the AI Legal Index, based on each vendor's own published materials as of October 16, 2026. No vendor pays for placement.
Can business users participate in both review processes?
Yes. Both describe legal approved positions and permissions for business teams, with exceptions returning to legal. The products therefore overlap in controlled delegation even though their surrounding platforms differ. From the AI Legal Index, based on each vendor's own published materials as of October 16, 2026. No vendor pays for placement.
Does Luminance need a formal playbook for every proposed markup?
Its negotiation product describes using precedent and context to generate Word markups even when a formal playbook position does not yet exist. It also supports approved templates, fallback language, and structured checklists. From the AI Legal Index, based on each vendor's own published materials as of October 16, 2026. No vendor pays for placement.
What does DraftPilot Mass Review return?
It organizes answers across a contract set in a table. A user can inspect the underlying contract language for a result, connecting the portfolio view with the relevant agreement text. 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.
Both products combine AI proposals with organizational review controls. Luminance's broader enterprise scope and DraftPilot's Word process are purchase scope distinctions, not claims that either product's legal conclusions are inherently correct.