Luminance vs Pactly: how they compare in 2026
Luminance emphasizes negotiation intelligence drawn from approved positions, earlier concessions and related agreements. Pactly's review is organized around explicit playbook positions, while Projects supplies a structured table for questions across contracts. The distinction becomes sharper at the point where an AI proposal is accepted. In negotiation review, AI Legal Index identifies Luminance's independent checking of proposed work and escalation to a person as a different control from Pactly's user acceptance of Assist edits. Neither approach removes the lawyer's role in choosing a position. Luminance's Spotlight organizes agreement families and portfolio intelligence; Pactly shows reasoning, quotations and human corrections in individual result cells. Teams choosing between them are selecting how prior contractual context, repeated analysis and human review should fit together, alongside their wider contract workflow.
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.
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.
Models identify clauses and concepts for playbook review, generate proposed revisions and extract values across contract collections. Assist adds questions about a contract's text and history, with proposed edits and comments in Word. Projects applies the same questions to many agreements and returns a structured table with reasoning and source passages. These are core analysis functions alongside the conventional platform: questionnaires generate approved templates, workflows route approvals, signatures execute agreements and reminders track renewals. Those administrative features do not depend on generative output. Projects is available separately, while Growth and Ultimate include it within an unspecified fair use allowance.
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.
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.
Projects connects an extracted value to reasoning, a quoted source passage and a document view that highlights the relevant text. Users can correct a value, preserve the original AI extraction and mark a result as verified. The guidance names concrete failure modes, including confusion between effective and commencement dates, loss of qualifiers in compound liability caps and missing values in drafts with placeholders. Word review also exposes the clauses behind each playbook assessment. No reproducible benchmark or measured error rate accompanies these mechanisms. The terms expressly warn that AI answers can be incomplete or wrong and require checking against the source.
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.
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.
Assist never applies a contract edit or comment silently: proposed changes require acceptance and enter Word as tracked changes. A reviewer can reject, revise or copy the proposal, and a support message is not sent without the user's choice. Playbook results can be Uncertain, returning the decision to a human; accepted deviations carry a written justification. Projects preserves corrected and verified values during reruns and identifies outdated results when a column question changes. The external MCP connection is read only and cannot create, modify, delete or send signature requests. Standalone Word generation remains described as an upcoming release rather than an existing unrestricted action.
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.
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.
A September 2022 case study identifies Virtuos and its Senior Legal Counsel, Johnathan Yong, and describes an NDA process before and after adopting Pactly. Requests previously took several days or sometimes a week across Word, shared drives and email. Following template questionnaires, legal review and DocuSign execution, reported median finalization fell to two hours and median completion of a signed agreement to twelve hours. Yong describes feedback more than two months after implementation. The account explains the workflow change and measured contract type, although it does not provide the sample size. It measures contract automation rather than the accuracy of today's generative review features.
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.
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.
The service agreement protects nonpublic customer data as confidential information and preserves customer ownership. Its improvement license nevertheless permits analysis of service information involving customer data during the term and use of anonymized aggregate customer data for lawful business purposes afterward. Public marketing says contracts never train AI models, without the same express restriction in the agreement. Sensitive groups can hide contracts from nonmember administrators, but deliberate sharing and project membership can widen access. The provider list explains where contract data travels. No specific attorney client privilege, work product or accidental disclosure protection is stated for lawyers using these features.
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 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.
Pactly's agreement says the company is not a law firm, use creates no attorney client relationship and the service does not solicit legal advice. It separately warns that AI answers may be wrong and makes the customer responsible for comparison with the source. Product guidance describes the reviewer accepting edits and resolving uncertain playbook findings, and the company explicitly rejects a fully automatic robot lawyer role. Corporate legal departments are its principal audience, with business users working through forms and approvals. The material does not map the controls to named bar guidance or publish jurisdiction specific professional responsibility limits.
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.
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.
Published AI guidance explains how customers verify results, handle uncertain findings and correct extraction mistakes. Release notes describe feature changes, and security materials identify a data protection officer and engineering responsibilities for incidents. These do not establish an AI governance program with an accountable model owner, release testing criteria or results on uneven behavior across languages, populations or contract categories. Positive and negative playbook examples help customers configure review, rather than disclose Pactly's own evaluation program. No formal bias assessment, model card or governance framework accompanies the descriptions of Assist, Projects and playbook review.
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 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.
Pactly describes encrypted storage and transport, monitoring, backups, vulnerability testing and separate production and test environments. Administrators can require two factor authentication, and high criticality incidents trigger notice to affected customers or all customers when the affected group cannot be identified. A public supplier register details processing functions and regions with advance change notice. The terms provide sixty days to retrieve data after termination, followed by requested deletion with an anonymized aggregate exception. Assist attachments expire after seven days, but ordinary chat history, backup deletion and underlying AI provider retention lack a complete fixed schedule. No definite breach notification deadline is stated.
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 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.
The service agreement includes an indemnity for third party claims involving patents, copyright or trade secrets infringed by the service, subject to stated exclusions and control of the defense. Available remedies include replacement, modification, a license or termination with unused fees returned. General liability is capped at fees paid in the preceding twelve months and excludes data inaccuracies and several categories of loss. AI answers are expressly described as potentially incomplete or wrong, with verification assigned to the customer. There is no separate output accuracy warranty or AI insurance promise. Availability remedies have separate claim deadlines and exclude beta features.
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.
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.
The Word plugin uploads an agreement for playbook review, displays matched clauses and proposed fixes, inserts approved language as tracked changes and records review decisions between rounds. The MCP connection exposes eight read only tools for contract text, metadata, parties, playbooks, clauses and account information to external clients such as Claude and Cursor. Public instructions specify API key or OAuth authentication, administrator consent, filters, returned fields and request limits. Separate APIs can generate contracts from templates and support webhooks. DocuSign and Adobe Sign support execution, while the Ultimate plan's SharePoint connection is described as backup only rather than general document synchronization.
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.
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.
Core hosting, compute and Bedrock inference use AWS in Singapore by default, with Malaysia for specified Malaysian customers. Structured data in MongoDB Atlas remains in Singapore for all customers. The supplier table separately identifies United States processing for document conversion, OCR, Cerebras inference and fallback Anthropic or OpenAI services, plus Langfuse monitoring in Germany and Cloudflare's global edge. Those routes make regional hosting different from exclusive regional processing. The SLA also recognizes fully managed private deployments, without a standard public price for them. Singapore and Malaysia have separate service entry points, and the published provider map identifies functions as well as locations.
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.
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.
Pactly identifies ISO 27001 certification in its product, pricing and trust materials and offers its certificate, security whitepaper and penetration test results on request. The public trust FAQ describes Amazon's certified data centers when explaining ISO coverage, so infrastructure attestations need to be distinguished from Pactly's own claim. No openly supplied certificate names its current auditor, validity period and exact company scope. SOC, PCI and FISMA references in the infrastructure section concern AWS rather than a separate Pactly audit. Security practices include vulnerability scans, access logging, staff training and incident response, without resolving that certification scope question.
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.
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.
Pactly names AWS Bedrock for core inference, Cerebras for tasks requiring low latency, and Anthropic and OpenAI as fallback providers when Bedrock is unavailable. The supplier register identifies processing locations and also lists Langfuse for AI monitoring. Customers can subscribe to at least thirty days' written notice before a new subprocessor is engaged and raise an objection during that period. Exact production model families and versions are not supplied for each feature, nor is there a promise to notify every model version change within an existing provider. External MCP clients bring their own model relationship in addition to Pactly's built in AI.
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.
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.
Standalone Projects starts at $69 a month for one user, fifty documents and 250 monthly runs, or $690 annually with 3,000 runs available immediately. Larger packages, additional documents and extra runs have published charges. The wider CLM starts at $99 per user monthly on an annual plan; Growth is $139 with five users minimum and Ultimate $179 with ten. Their monthly AI review allowances are ten, fifty and one hundred respectively. Growth and Ultimate include Projects under fair use without a numerical allowance. Enterprise, migration and some implementation services require a quote. Projects has a fourteen day trial, while the CLM trial lasts thirty days.
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.
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.
Pactly primarily serves corporate legal departments, including solo counsel and small teams across Southeast Asia and other Asia Pacific markets. Larger organizations can configure approval routes, business intake and administrator controls. Supported examples include NDAs, services, procurement, leases, employment and software licenses; Projects extends analysis to loan agreements, insurance and related portfolios. Sales, HR, finance and procurement can participate without turning the product into a consumer legal advice service. The company explicitly describes most customers as internal legal departments rather than firms. No measured language coverage or comprehensive jurisdiction matrix defines where AI interpretation is most reliable.
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 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.
The agreement permits analysis of service information involving customer data during the subscription for improvement and development. It also allows anonymized customer data to enter aggregate datasets used for lawful business purposes during and after the term, with safeguards against reidentification. Marketing separately promises that contracts never train AI models. The published agreement does not repeat that prohibition or exclude model improvement from its permission.
This records the contractual scope, not a claim that Pactly actually feeds every raw agreement into a shared training process.
Prompt and Output Retention
How long does the product keep what a lawyer typed, and can that be set to zero?
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.
Contract data remains retrievable for sixty days after termination. The standard terms then provide deletion on written request, excluding anonymized data already combined into aggregate datasets; online plans may delete after the same access window. Assist attachments expire after seven days, but a complete schedule for normal chat history, backups and provider copies is absent. The upcoming standalone Word generation description gives a thirty day file expiry, which should not be treated as the lifetime of all current AI outputs or contracts saved to the repository.
Ethical Walls and Matter Segregation
Does retrieval respect the firm’s ethical walls, or can the model read across them?
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.
Pactly uses its own groups and roles rather than inheriting a document management system's matter walls. Sensitive groups hide contracts even from nonmember administrators, but an authorized person can deliberately share a contract outside the group. Projects creates another boundary: every project member sees all present and future project documents, even when the normal repository link is unavailable. Administrators can see all projects.
This is a described access model with important widening rules, not a promise that an original contract restriction automatically follows every AI analysis surface.
Third Party Request and Subpoena Notice
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
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.
The service agreement incorporates Pactly's law enforcement request policy for compelled disclosure of customer data. That policy requires evaluation of governmental requests and notification to the customer where legally permitted, allowing an opportunity to seek protective measures. It applies to hosted and fully managed deployments, while excluding self hosted or customer managed solutions. Foreign authorities are directed through applicable legal and diplomatic channels.
No report of request volumes or outcomes accompanies this commitment, and the general privacy notice's legal disclosure permissions do not replace the more specific customer data policy.
Primary Law Corpus Provenance
Where does the law in this product come from, and does the vendor have the right to use it?
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.
The analysis context is the customer's agreements, playbooks, approved clauses and related files. Projects reads each row's main contract and supporting amendments or schedules; Word review uses configured positions and fallback language. These are customer supplied materials rather than a catalog of primary law or licensed legal commentary. Pactly does not name an external research corpus, describe the source rights behind general model knowledge or supply an update process for legislation and case law. The public subprocessor list identifies processing suppliers, not a legal content licensing arrangement.
Good Law Verification
Does the product tell you when the authority it just cited has been overruled?
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.
A source passage in Projects establishes where a contract value came from, and playbook review identifies the agreement language relevant to a configured rule. Neither function determines whether a case remains good law or legislation has changed. No licensed citator, subsequent history service or independent treatment signal is described. The legal team maintains its own clause positions and decides whether they remain appropriate.
Contract source highlighting and a verified cell marker therefore support review of supplied material without establishing the continuing validity of an external legal proposition.
Refusal and Uncertainty Behavior
What does the product do when the answer is not in the corpus?
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.
Playbook review includes an Uncertain result when a clause cannot be conclusively assessed, directing a person to decide. Each position also defines what happens when no relevant clause is found: compliant, not compliant or uncertain, according to the customer's chosen rule. Projects treats placeholders such as an unfilled name as not found and explains common interpretation failures. These are described negative and uncertainty states rather than a general guarantee of refusal. A wrong configuration of the absent clause rule can still produce a misleading result.
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 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.
Damien Charlotin's AI Hallucination Cases database contained no entry naming Pactly on October 16, 2026. The database concerns reported court decisions involving fabricated AI material and does not capture every private error in contract analysis. Pactly principally supports corporate agreements rather than preparation of court authorities, which limits what that incident record can say about its usual work. Its terms independently warn that AI answers may be incomplete or incorrect. No named court incident is therefore a limited reporting observation, not a validation of model accuracy.
Bar Guidance Alignment
Has the vendor engaged in public with the ethics opinions its buyers are bound by?
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.
Pactly explains that it is not a law firm and requires people to verify AI answers against source text. Its review guidance describes accepting tracked edits, recording deviations and resolving uncertain results. These are practical controls for legal work, but the materials do not map them to a named professional ethics opinion, bar rule or regulator's jurisdiction specific AI guidance. References to Singapore privacy law and a data protection officer address data regulation rather than a lawyer's professional obligations when serving a client.
Billing and Fee Posture
Does the vendor address what happens to the bill when the work takes an hour instead of six?
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.
The principal buyer is a company's own legal department, with sales, procurement and HR using forms and approvals around that team's contracts. The Virtuos case measures internal NDA turnaround, and the product's savings claims concern corporate workloads and staffing capacity. Those examples do not involve a lawyer billing an external client for AI assisted work. Published subscription and run charges describe Pactly's software fees, without a client invoice method, pass through rule or accounting of billable legal time. Law firm fee treatment is not part of the described workflow.
Outside Counsel Guideline Readiness
Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?
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.
A public provider register identifies data categories, functions and regions, including core Bedrock inference, fallback Anthropic and OpenAI services, and AI monitoring. Customers can subscribe to change notices and object before a new supplier is engaged. The trust page offers security reports and a certificate on request, while service terms and the law enforcement policy provide additional diligence material. No dedicated client consent pack or outside counsel AI disclosure form is supplied. Counsel would still need to distinguish the contractual improvement permissions from the marketing training promise.
Court Disclosure Support
If a judge’s standing order requires an AI disclosure, can the product produce one?
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.
Projects can export values, reasoning and source references to Excel, and produce a PDF preserving the table's visual labels. Human corrections and verifications record who acted and when inside the application, but the help guide expressly says the Excel export omits that sign off marker. Word review retains tracked edits and written justifications for deviations, while account activity is available through logs. These records preserve parts of the process without a combined export of model version, exact prompts, source context and human approval 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
Which one fits
Choose Luminance if
- Negotiation should draw on prior concessions and related agreements.
- Agreement families are central to portfolio analysis.
- Independent AI checks and escalation support your proposed review process.
Choose Pactly if
- Explicit positions and examples are the starting point for each review.
- Analysts need a table showing the support behind individual answers.
- A small published analysis plan suits the initial portfolio exercise.
In summary
Luminance
Luminance combines negotiation in Word with intelligence from related agreements and prior concessions. Spotlight organizes portfolio information, and its AI architecture checks proposed work before further action or human escalation.
Pactly
Pactly turns preferred positions and examples into versioned review playbooks. Projects adds repeatable portfolio questions with supporting excerpts, while Assist drafts changes that the user must accept.
Questions buyers ask
How does Pactly decide whether a playbook position is satisfied?
Positions include standards, examples and drafting instructions. A result can be compliant, noncompliant or uncertain, with matched clauses and reasoning available to the reviewer. Missing language can have different meanings depending on the position. From the AI Legal Index, based on each vendor's own published materials as of October 16, 2026. No vendor pays for placement.
Why do related agreements matter in Luminance?
A negotiated position can depend on earlier concessions, amendments and related contractual commitments. Luminance uses that context in negotiation and organizes agreement families through Spotlight. From the AI Legal Index, based on each vendor's own published materials as of October 16, 2026. No vendor pays for placement.
Do both systems require a person to read every proposed edit?
Pactly Assist cannot apply its own edits; the user decides what to accept. Luminance describes checking and retry mechanisms with escalation to a person when the automated path does not establish agreement. 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 Pactly add for a repeatable analysis project?
For repeated questions across an agreement collection, AI Legal Index highlights Pactly's structured result cells and retained human corrections. Those controls support a reviewed dataset while Luminance emphasizes contractual relationships and negotiation context.
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.
Negotiation checking and portfolio extraction are different tasks; their controls should be evaluated within the feature being used.