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Luminance
Luminance is a contract lifecycle platform covering generation, negotiation, analysis, compliance and investigation for corporate legal teams and law firms. It is sold across legal, compliance, procurement, sales, finance, HR and marketing functions. It was founded in Cambridge in 2015 by mathematicians. It runs a multi model architecture the vendor calls a Panel of Judges, combining foundation, fine tuned and proprietary models.
In June 2026 it introduced Luna Crescent, its own legal intelligence model, trained on a curated selection of roughly 3.4 million legal concepts and data points drawn from more than 220 million verified legal documents. Luna is deployed inside the vendor's own AWS environment, which the vendor states reduces reliance on external model providers and limits exposure to additional subprocessors. Each customer receives a dedicated single tenant instance, and on premises deployment is available.
Luminance, head to head
Side by side on the same 15 capability axes and 12 legal signals: where the two part company, and what neither one publishes.
Alternatives to Luminance
Vendors in the same categories as Luminance whose graded profiles look most alike, with a line on what each product does.
Similar is not the same, so check that each one does the job you need. No vendor pays for placement.
- CCentariCentari is a deal intelligence platform for transactional law firms and investment funds.
- AAracor AIAracor is a deal platform that reads the documents behind a transaction and ties every finding to the language it came from.
- SSpellbookSpellbook offers AI contract review and drafting for transactional lawyers, delivered mainly as a Microsoft Word add in and also working in Google Docs.
- TThoughtRiverThoughtRiver is an AI contract review platform for corporate legal teams and the law firms that serve them, from ThoughtRiver Ltd of Cambridge, England.
- ZZuvaZuva is contract analysis AI from the team that built Kira Systems.
- GGavelGavel, formerly Documate, makes two legal products under its own name.
Ordered by how closely the graded profiles match across the 15 capability axes, inside the same categories. See how each axis is graded in the methodology.
Capability grades
All 15 axes, graded from public sources on the date shown. 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.
The artificial intelligence is the product, and the vendor owns much of the stack. Founded by mathematicians in 2015, it runs a multi model architecture it calls a Panel of Judges, combining foundation, fine tuned and proprietary models. It ships its own legal intelligence model, Luna Crescent, trained in house and deployed in its own environment. Remove the models and there is no product.
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.
Substantive disclosure with a real gap. The vendor publishes ContractIQ Bench, a proprietary benchmark of 189,000 manually annotated and reviewed data points assessing interpretation of named provision types, including liability caps, termination for convenience and confidentiality obligations. It is tested on held out documents and concepts excluded from training, with blind evaluations by legal experts alongside. It publishes a result, 5 percent higher accuracy than leading general purpose models on contract understanding, and a speed figure of 200 to 400 tokens per second.
It also states that the model is trained to prioritize faithful extraction and to identify absence rather than invent an answer. Two gaps remain. The published figure is a relative difference with no absolute accuracy rate and no named comparator models, so a buyer cannot tell what the 5 percent is measured against. And the benchmark is proprietary, with no sample tasks or rubric published, so an outsider cannot inspect or run it again.
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.
A real published commitment with a described control mechanism, short of the full structure. The Panel of Judges architecture is itself an oversight design and is documented: multiple models analyze each clause independently and reach consensus, which the vendor states reduces hallucination risk. Outputs are described as traceable, and Traffic Light Analysis ranks deviation risk visually so a reviewer sees where to look.
The vendor publishes a position piece arguing that human in the loop alone is insufficient and that systems must be designed for accuracy and transparency. Not located: where the review point sits when the product negotiates with a counterparty directly, the threshold at which it escalates to a lawyer, and what the vendor commits to when an output is wrong. The first gap matters because the product sends agreements to counterparties and negotiates on the customer's behalf.
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.
Real deployment evidence with substance, short of attribution and method. Named customers appear in vendor and trade material including Hitachi, AMD, BBC Studios, Yokogawa and Koch, alongside a stated base of more than 700 organizations across 70 plus countries and all four of the Big Four consultancies. A customers page is published. The recurring figure, negotiation time reduced by up to 90 percent, is a vendor claim carrying a hedge and is not tied to any named customer, dated, or accompanied by a method.
Searched the site, the customers page, the press releases and the resources index and located no case study pairing a named organization with figures and a date.
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.
Substantive published commitments, short of the full picture. Segregation is the strongest element and is documented precisely: each customer receives a dedicated single tenant instance with complete isolation and no mixing of data. Access control is documented in depth, including that vendor staff cannot view customer documents without explicit authorization given through the user interface, with all access tracked and audited.
Encryption is specified to the key management service, cipher and rotation practice. Two gaps remain. No prohibition on training with customer content is published anywhere in vendor material, which stands out for a vendor that trains its own models and publishes a figure of 220 million legal documents. Attorney client privilege and work product handling is not addressed directly.
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.
A boilerplate structure sits in the terms while the product is sold well beyond lawyers. Dedicated solution pages target compliance, executive, sales, procurement, finance, human resources and marketing teams alongside legal, and the product negotiates contracts on a customer's behalf. Searched the site, the solution pages, the published terms and conditions, the privacy policy and the resources index on 29 Aug 2026.
No position on advice versus tooling, no treatment of competence or supervision duties, and no statement of jurisdiction limits is published, despite operation in more than 70 countries. The tool is marketed to marketing and HR departments.
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.
Principles and architecture are published without a governance mechanism a buyer could audit. What exists is real and substantial: a published white paper on how the AI is built, a named Director of AI who writes technical material under his own name, and a research team based in Cambridge. There is also a described validation regime through ContractIQ Bench, and a security advisory board of named external experts. That board governs security rather than model behavior, and no equivalent exists for AI governance.
Not located: a named owner of model governance, a testing gate before release as distinct from benchmark results, an AI management certification such as ISO 42001, or anything on uneven output across matter types, parties or populations.
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.
Substantive published policy covers most of the ground in specific detail. The security FAQ describes AWS Key Management Service encryption at S3 and EC2 level with AES-256 keys rotated regularly, TLS 1.2 or higher in transit, and dedicated single tenant instances. It describes role based and division level permissions configured by the customer under least privilege, configurable password and session timeout policy, mandatory staff security training, threat detection through Darktrace's Enterprise Immune System and Juniper firewalls, and an incident management process covering detection, mitigation and communication.
Backups are stated precisely: nightly to a secondary AWS data center in the same region, encrypted, and kept at least 14 days. Not located: a retention period or deletion control for customer documents in normal operation as distinct from backups, and a named subprocessor list.
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.
Liability is addressed only through published terms carrying a standard structure. Terms and conditions are published openly alongside a privacy policy, cookie policy and anti slavery statement, so a buyer can read the allocation of loss before entering a sales process, which keeps this above a pure absence. Searched those documents, the security page and the security standards white paper entry point and located no indemnity running to the customer for third party claims arising from output, no warranty on output, no stated liability cap figure and no insurance position.
Worth noting the product negotiates with counterparties on a customer's behalf, which raises the recourse question more sharply than a review only tool.
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.
Integrations are asserted at platform level with no documentation an implementer could use. The vendor describes connecting intake, negotiation, workflow and repository intelligence in one platform, and a Collaborate product exists for working with counterparties, and third party sources reference Microsoft Word and Outlook working surfaces. What is not published on the vendor's own property, after checking the platform pages, the technology page, the security page and the resources index, is any integrations page, any named connector for document management, contract lifecycle, e signature, CRM or ERP, and any description of what an integration moves or what an administrator configures. For an enterprise platform sold to procurement and finance functions, that absence is notable.
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 deployment model is stated clearly, with partial residency detail. Three things are published and specific: a dedicated single tenant AWS instance per customer with complete isolation, deployment within the customer's own environment as an alternative to the hosted option, and backup to a secondary AWS data center within the same region, which confirms data stays in region. The vendor states AWS global infrastructure provides a solution tailored to geographic requirements.
What is missing is the list: no named available regions, no statement of which regions a customer may select, and no statement of where processing happens as distinct from where data is stored.
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.
Certification is real and stated with correct nouns, short of accessible evidence. ISO 27001:2022 is named with its version and described as certification. The SOC 2 Type 2 language is precise: the vendor says it successfully completed a SOC 2 Type 2 examination assessing controls related to security, availability and confidentiality, which names the trust services criteria in scope. Regular independent third party penetration testing is stated.
A named external security advisory board, including a former Director General of MI5 and two former Darktrace executives, is published with full biographies. What is missing is the evidence route: no trust portal is published, no report is downloadable or requestable through a published flow, and no coverage period, report date or auditor name is published as of 29 Aug 2026. A security standards white paper is published, the nearest thing to an evidence route.
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 supply chain is partly disclosed and the architecture is described in depth. The vendor publishes that it runs a multi model Panel of Judges combining foundation, fine tuned and proprietary models, that it continuously evaluates and selects the best model for each task, and that its own model Luna Crescent is deployed inside its own AWS environment. It states the consequence in the customer's terms: owning the model reduces reliance on external model providers, limits data exposure to additional subprocessors, and protects customers from third party availability, pricing and access disruption.
Hosting is named as AWS. Not published is which foundation models sit in the panel, from which providers, or which tasks route to them, and no subprocessor list or change notification commitment is published. A buyer knows the shape of the chain and its own model, but not the third party links in it.
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.
No pricing page exists on the property, no rate is published, no unit of charge is stated and no tier structure appears. Every commercial path terminates in a demo request. No free trial or self serve entry point is published, and no third party pricing figure is published either.
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.
Who the product serves is documented precisely across two dimensions, each with its own published pages. Six industries: manufacturing, financial services, pharmaceutical, technology, insurance and chemical. Eight business functions: legal, compliance, executive, sales, procurement, finance, human resources and marketing. Both law firms and corporate legal departments are addressed, with a stated base of more than 700 organizations across more than 70 countries including all four Big Four consultancies and named enterprises.
An academic program is published as a separate segment. The practice boundary is clear from the structure and consistent throughout: this is contract work end to end, from generation through negotiation to post execution analysis and investigation, and nothing on the property claims litigation or research capability it does not have.
5 public documents
The public pages on file for Luminance, with the recorded signals each one supports and the date it was last read. Open any of them and check the reading against the record.
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luminance.com/security3 signals
Prompt and Output Retention, Ethical Walls and Matter Segregation, Outside Counsel Guideline Readiness
Read Aug 29, 2026
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Primary Law Corpus Provenance, Refusal and Uncertainty Behavior
Read Aug 29, 2026
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Fabricated Citation Record
Read Aug 29, 2026
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luminance.com1 signal
Billing and Fee Posture
Read Aug 29, 2026
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Client Data in Training
Read Sep 6, 2026
Legal Signals
What each signal meansA signal records what public sources say on the date shown. It is not a grade and it is not a recommendation. Where a signal reads Not addressed, it means the index did not locate the material in public sources on that date, which is a statement about disclosure rather than about the product.
Client Data in Training
Can material a lawyer puts into this product be used to train a model?
Public material states that customer content trains, refines or personalizes models, with no matching term located in the published agreement. Any de identification, anonymization or aggregation qualifier is recorded in the summary.
Public material states that customer content from the platform trains the model. The vendor's press release of 17 February 2022 says its AI has been exposed to more than 100 million documents and is also learning from the interactions between humans and the documents. It says the AI learns from every NDA or supplier agreement negotiated within Luminance, every clause that causes an M&A transaction to fall apart and every piece of data culled during eDiscovery.
The May 2023 Ask Lumi release repeats that the Legal Pre-Trained Transformer learns solely from legally verified documents, now put at more than 150 million. No aggregation, anonymization or deidentification qualifier is stated, and nothing published says whether a customer can decline or whether learning from one customer's negotiations stays with that customer. The published terms and conditions and privacy policy carry no matching term in either direction.
The statement is dated, and the vendor's current pages describe the training data without repeating the sentence about learning from customer negotiations; that reflects age, not a withdrawal. A vendor statement of what its model learned from is a stated position rather than silence.
Prompt and Output Retention
How long does the product keep what a lawyer typed, and can that be set to zero?
Retention is acknowledged in public materials with no stated period.
Retention is acknowledged and partly quantified without a period for the primary system. The security FAQ states each customer instance is backed up nightly to a secondary AWS data center in the same region, encrypted, and kept for a minimum of 14 days, which is a real published figure and a floor a buyer can plan against. What was not located as of 29 Aug 2026 is any retention period for documents, prompts or outputs in normal operation, any customer control over that window, or any deletion commitment. A minimum backup retention states how long data persists after deletion rather than how long it is held.
Ethical Walls and Matter Segregation
Does retrieval respect the firm’s ethical walls, or can the model read across them?
The product maintains its own permission model, documented, requiring the firm to keep it aligned.
The product maintains its own documented permission model. Between customers, isolation is architectural: each has a dedicated single tenant instance, stated to ensure complete isolation with no mixing of data. Inside a customer, the vendor publishes division level permissions administered by the customer under least privilege, role based configuration, and customer configurable password and session timeout policy. Vendor staff cannot view customer documents without explicit authorization given through the interface, with all access tracked and audited.
Division level permissions are the nearest published equivalent to a wall. No document management integration was located whose permissions retrieval could inherit at query time, and conflicts and ethical walls are not addressed as such.
Third Party Request and Subpoena Notice
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
No located term or policy addresses third party requests for customer data.
Searched the published terms and conditions, the privacy policy, the security page and its FAQ, and the security standards white paper entry point on 29 Aug 2026. No clause committing to notify a customer of a government or law enforcement request for their data was located, and no transparency report was located. Noted for a future reader: the single tenant and on premises deployment options materially change what a vendor could produce in response to such a request, but the vendor does not make that argument in published material and it is not recorded as a value here.
Primary Law Corpus Provenance
Where does the law in this product come from, and does the vendor have the right to use it?
No located public material identifies the corpus behind the product’s answers.
The training data is contract and legal document data behind a proprietary model rather than primary law, and it is quantified in detail without being sourced. Published: more than 220 million verified legal documents the platform has been exposed to over a decade, and a curated training selection of roughly 3.4 million legal concepts and data points. Its breadth is described as spanning virtually every industry, including complex agreements, difficult file formats and obscure drafting styles.
A separate benchmark set has 189,000 manually annotated data points. Not published is where any of it came from or on what rights basis it was assembled. Trade coverage notes that many documents in the training base were not publicly disclosed. Scale and character are described, while the source and license basis are not.
Good Law Verification
Does the product tell you when the authority it just cited has been overruled?
No located public material addresses whether authority is checked for subsequent history.
Searched the site, the six platform product pages, the technology page and the resources index on 29 Aug 2026. No material was located addressing whether authority carries a treatment signal or whether subsequent history is checked, and no commercial citator license was located. Noted for context: this is a contract lifecycle product whose grounding is contract language and the customer's own precedent rather than case law, so a citator is largely outside its design.
Refusal and Uncertainty Behavior
What does the product do when the answer is not in the corpus?
The vendor describes refusal or abstention behavior in public materials.
The vendor documents abstention as an explicit design objective. The proprietary model is trained to prioritize faithful extraction from source documents, and where information is not present it is designed to identify that absence rather than invent an answer; the vendor says this is what instills trust for legal professionals. Vendor material separately describes flagging what is absent as well as what is present as a capability advantage.
No published evaluation of the abstention behavior itself was located as of 29 Aug 2026: the ContractIQ Bench results address interpretation accuracy rather than refusal rate.
Fabricated Citation Record
Does a public court record exist addressing fabricated or hallucinated legal citations in output from this product?
No court order, opinion or disciplinary record addressing fabricated or hallucinated legal citations produced by this product has been located as of the date shown. This is a statement about the public record on that one subject, not a finding about the product, and this signal is not a litigation history.
No court order, opinion or disciplinary record naming this product has been located as of 29 Aug 2026. Instrument searched: the AI Hallucination Cases database maintained by Damien Charlotin, which tracks court decisions worldwide involving AI generated hallucinated content and records the AI tool implicated where it is known. Also checked published 2026 sanctions summaries and secondary sanctions trackers. The entries located name filers, and in some rows other products, rather than this one.
This is a statement about the public record on the date shown and not a clearance. Note that this is a contract lifecycle product rather than a litigation or research tool, so its output is unlikely to reach a court filing as cited authority, and note that the database is weighted toward US filings while this vendor is UK founded and operates across 70 plus countries.
Bar Guidance Alignment
Has the vendor engaged in public with the ethics opinions its buyers are bound by?
No located public material engages with bar or ethics guidance.
Searched the site, the insights and white papers indexes, the press releases and the resources hub on 29 Aug 2026. No engagement with any named ethics opinion or professional guidance was located, including ABA Formal Opinion 512, US state bar guidance, and Solicitors Regulation Authority or Law Society guidance given the company's UK base. The vendor publishes substantial thought leadership on AI reliability, including a piece arguing that human in the loop alone is insufficient, which engages with the professional risk question in substance while naming no guidance a buyer is bound by.
Billing and Fee Posture
Does the vendor address what happens to the bill when the work takes an hour instead of six?
Public materials claim time savings without addressing billing or disclosure, and the product sits inside a fee relationship between a lawyer and a client where those savings would change the bill.
Savings are claimed with nothing published on the client's side of the equation. The recurring published claim is negotiation time reduced by up to 90 percent, alongside speed framing throughout including a stated four times faster generation than generalist tools. Searched the site, the platform pages, the customers page and the resources index on 29 Aug 2026 and located no per matter record of AI assisted work intended for fee purposes, and no guidance on billing, fee or client disclosure treatment. The vendor sells to law firms as well as corporate teams, so the firm side of that question applies.
Outside Counsel Guideline Readiness
Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?
No located public material supports a client side disclosure obligation.
Substantial security material is published openly, including a detailed security FAQ, named certifications, a named external security advisory board and a security standards white paper, all reachable without a sales conversation. But no subprocessor list, no statement of which model providers see customer content, and no consent or notification pack for clients that a firm could forward was located as of 29 Aug 2026.
The vendor states that owning its model limits data exposure to additional subprocessors, which is an argument about the shape of the chain rather than a disclosure of it. No list exists to point to.
Court Disclosure Support
If a judge’s standing order requires an AI disclosure, can the product produce one?
No located public material addresses court disclosure or verification certification.
Searched the site, the platform product pages, the technology page and the security page on 29 Aug 2026. Vendor material states outputs are traceable and that all data access is tracked and audited, so elements of an access trail exist. But no per document export covering model used, sources retrieved and human verification together was located, and the model used would be difficult to state in any case given the Panel of Judges architecture routes tasks across multiple models.
Noted for context: this is a contracting product rather than a litigation product, so a judicial AI disclosure order is less likely to reach its output.