E
eDiscovery AI
eDiscovery AI applies large language models to document review inside a litigation workflow a firm is already running. Its Review suite has two parts. Relevance classifies a document set against instructions the reviewer writes in plain language, restates the instruction it was given for each classification, and explains why it categorised the document as it did, replacing the Boolean permutations and seed-set training that Boolean search and technology-assisted review require.
Privilege identifies attorneys and names them in a separate field, sets out which elements of the privilege are present so the strength of a call is visible, and produces a document summary and privilege reasoning in a log entry field that can be used or edited as drafted. Three further suites sit alongside: Early Case Intelligence, covering case insight and case elements; Privacy, covering detection and extraction of personally identifiable information; and Multimedia, covering image comparison, image filtering and facial recognition.
The product is delivered as a plug-in to Relativity and is listed on the Relativity App Hub: a reviewer selects a document set, supplies relevance, issue, privilege and category specifications, submits the documents through the plug-in, and then validates the returned classifications and generates standard performance metrics against them. No indexing or model retraining is required to run the same instructions against additional documents.
The company publishes an extensive body of practitioner material, including fact sheets, whitepapers, case studies and books on AI document review. eDiscovery AI is based in Bloomington, Minnesota.
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 models are the product and there is nothing underneath them to license, which is the A band. Every capability the vendor sells is a classification or extraction produced by a language model: relevance coding against written instructions, privilege determination with named attorneys and privilege elements, early case intelligence, detection and extraction of personally identifiable information, and image comparison, filtering and facial recognition.
There is no repository, processing engine, review platform or production tool being sold alongside them. The delivery architecture settles it rather than leaving it to inference: the product is a plug-in that receives a document set from Relativity, classifies it, and writes results back to a mapped field, so the platform of record belongs to somebody else and what this vendor supplies is the judgement applied to the documents.
The vendor's own framing matches, positioning AI review as the successor to Boolean search and technology-assisted review rather than as a feature added to either. Verified 12 September 2026.
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.
Grounding is real and documented per document, and a figure is published without the test set that would make it testable, which holds this at B. The grounding is unusually concrete for this corpus because it is built into the output rather than described in the abstract: Relevance restates the instruction it was given when making each classification and then explains why it categorised the document as it did, and it does so consistently across every document and every classification.
Privilege goes further, naming the attorneys it identified in a separate field, spelling out which elements of the privilege are present so a reviewer can see the strength of the call, and producing its reasoning as a draft privilege log entry. The published workflow ends in validation, the fourth step being to review the results and generate industry standard performance metrics. A figure is published: consistently achieves 90 per cent recall with excellent precision. **It does not reach A because the A limb asks for measured accuracy with the test set described and the failure modes named, and neither appears.** No corpus, sample, matter type or methodology is given for the recall figure, precision is characterised rather than quantified, and no failure mode is identified.
The Pre/Dicta record at R15 is the contrast: it published a figure, described a test set of more than 50,000 motions across 94 districts, and named its own limits. Verified 12 September 2026.
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 review surfaces and the route back to human judgement are published as part of the workflow, short of any stated threshold, which is B. Oversight is not asserted, it is built into the four published steps: the reviewer specifies the criteria, the model classifies, and step four is to review results to validate document classifications and generate industry standard performance metrics. That is a validation gate with a measurement attached, which is more than most records in this corpus offer.
Underneath it, every classification carries a restated instruction and an explanation, so a reviewer can audit a call rather than accept it, and privilege output is expressly a draft, the log entry field being available to use or edit as needed. The named attorney field exists precisely so results can be validated. What is missing for A is the boundary. Nothing published states a confidence threshold, describes what the system does when a document is ambiguous, sets out an escalation path, or says what proportion of a set a reviewer should sample.
No mode structure is described, and nothing distinguishes a classification the model is confident in from one it is not, which matters on privilege where a single wrong call can waive. Verified 12 September 2026.
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.
The headline result is quoted with no basis stated, and no customer is named on the surfaces read, which is C. The published claim is a performance one rather than a deployment one: consistently achieves 90 per cent recall with excellent precision, and reviews across hundreds of thousands of documents in hours at a fraction of the time and cost of manual review. No matter, no client, no engagement and no volume is attached to any of it, and no method is stated, so a reader cannot tell whether the figure comes from a benchmark, a customer project or an internal test.
One structural fact is real and is recorded rather than credited as a customer: the product is listed on the Relativity App Hub and delivered as a Relativity plug-in, which is a partner relationship with the dominant platform in this lane and is graded on the integration row. Named here as the route by which this row would move and not opened under the sufficiency discipline: the vendor publishes a case studies category alongside fact sheets, whitepapers, videos and books, and a named engagement with a figure and a method in any one of them would lift this to B or A. Verified 12 September 2026.
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.
Nothing is published on how client confidences are handled by a product built to ingest them, which is the D band, and the absence is established rather than untested. Both published documents were read in full on the date shown. The Privacy Notice, last updated 8 January 2025, scopes itself in terms: it applies only to information collected on or through the vendor's websites or through other interactions with the vendor and its clients.
It addresses names, addresses, identifiers, browsing data and marketing preferences. It says nothing about the customer documents submitted for classification. The Terms and Conditions, last updated 23 May 2024, are a generic website terms-of-use template covering content ownership, acceptable use, service interruption and severability, and contain no data provisions at all. So nothing published addresses training on client documents, retention of a reviewed collection, segregation between matters or between clients, or what any model provider may retain. **The irony belongs on the record as a fact rather than a charge: the product's principal function is to identify privileged material so it can be withheld, and the vendor publishes no statement about how it protects the privilege of the documents it reads.** Verified 12 September 2026.
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.
Nothing published addresses the advice line for a product that makes privilege determinations, which is the D band. R15 governs which limbs bite, and one of them is answered: the audience is unambiguous, the product being sold to legal teams and eDiscovery service providers and delivered inside Relativity, so there is no consumer-facing ambiguity to resolve. Every other limb is unaddressed. No statement was located that the vendor is not a law firm, that a classification is not a legal determination, or that a privilege call requires attorney review before it is relied on to withhold a document.
Nothing addresses supervision, competence or the reviewer's own professional obligations, and the two published documents, both read in full, contain no disclaimer of any kind on the point. That gap is sharper here than on most records in this corpus, because a privilege designation is a legal conclusion with a waiver consequence attached, and the published workflow puts the model in the position of making it first. The validation step in the workflow does place a human after the machine, and it is graded on the Autonomy row as a control rather than as a professional-responsibility position, which is what it is. Verified 12 September 2026.
AI Governance and Bias Disclosure
Published governance over model behaviour: who owns it inside the vendor, what is tested before release, and what is disclosed about disparate output across matter types, parties, or populations.
No governance position is published for a system whose output affects legal outcomes, which is the D band. There is no responsible AI page, no set of principles, no framework named, no certification claimed, nobody identified as accountable for AI decisions, no description of what is evaluated before a model changes, and no testing regime beyond the per-project performance metrics a customer generates for itself. Neither published document touches AI at all.
Bias is unaddressed and is squarely live on this estate rather than theoretical. The vendor ships **facial recognition** as a named product feature, alongside detection and extraction of personally identifiable information, applied to litigation collections that contain images of real people; facial recognition is the single AI capability with the most documented demographic performance disparity, and nothing published addresses accuracy across populations, thresholds, or what a false match in a document review would mean.
The relevance and privilege classifiers raise a quieter version of the same question, since a model that reads correspondence to infer legal significance can perform unevenly across writing styles, languages and communication formats, and nothing published considers it. Verified 12 September 2026.
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.
Nothing is published on retention, deletion or access for a system that holds client documents, which is the D band, and both documents that would carry it were read in full. The Privacy Notice's security section is a single paragraph and is weaker than the norm rather than merely thin: it says the vendor takes a number of steps to protect against loss and misuse of information under its control, warns that no internet transmission is completely secure, states that information is sent at the user's own risk, and disclaims responsibility for illegal acts such as hacking by third parties.
No encryption, access control, monitoring or incident practice is described anywhere. Its retention section is criteria-based rather than periodic and is scoped to personal information collected through the website, not to a reviewed document collection. There is no subprocessor list, no security page, no trust centre and no data processing addendum on any surface, and the site navigation, which renders in full and is therefore the page inventory under R20, contains no security page at all.
The Terms and Conditions contain no data provisions. On a product that ingests entire litigation collections, that is the whole published record. Verified 12 September 2026.
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.
Nothing is published on who bears the loss when the system is wrong, which is the D band, and the way that comes about is worth recording precisely because it is unusual. The Terms and Conditions were read in full. They run to about a dozen short clauses covering content ownership, access to external resources, acceptable use, no waiver, service interruption, service reselling, intellectual property, changes to terms, assignment, contacts and severability. **They contain no limitation of liability, no disclaimer of warranties, no indemnity and no cap of any kind.** Most records in this corpus sit at C because a standard limitation clause disclaims the exposure the product creates; here even that is absent, so nothing is allocated in either direction.
Nothing addresses what happens if a relevant document is coded non-responsive and not produced, or if a privileged document is classified as non-privileged and produced, which is the failure mode with the largest consequence in this workflow and the one the product exists to prevent. No warranty attaches to the published 90 per cent recall figure. No insurance position appears. No customer agreement is published on any surface located. Verified 12 September 2026.
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.
One integration, and it is the one that matters in this lane, documented at the level of what actually moves. The product is delivered as a Relativity plug-in and is listed on the Relativity App Hub, which is a reviewed partner channel rather than a self-declared compatibility claim. What the integration does is described as a workflow rather than named: the reviewer selects a document set inside Relativity, supplies relevance, issue, privilege and category specifications, submits the documents to eDiscovery AI through the plug-in for classification, and receives results written back to a mapped field.
The vendor states that the only configuration required is the prompt instructions and the field to map results to, and that no additional indexing or model training is needed to run the same instructions against a further document set, which is a real statement about how the connection behaves in use. What holds it off A is breadth and documentation. No other platform is named, so a firm on Everlaw, Reveal, DISCO or Nuix has nothing published to work from; no API, developer documentation or connector specification was located; and nothing describes authentication, volume limits or how results are versioned. Verified 12 September 2026.
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.
Cloud delivery is implied and neither the tenancy model nor the region is stated, which is C in its exact terms. Delivery is clear enough in outline: documents are submitted from a customer's Relativity workspace to eDiscovery AI for classification and results return to a mapped field, so processing happens on the vendor's side and the product is a hosted service reached through a plug-in. Nothing beyond that is published.
No cloud provider is named, no region or data centre is identified, no residency option is offered or refused, no tenancy model is described, and nothing states whether a customer's collection is isolated from any other. Nothing distinguishes where documents are held during processing from where model inference happens, and no on-premises or in-tenant option is mentioned. The Privacy Notice contains the only geographic statement located, that the vendor operates in various countries including the United States and countries in the European Union and European Economic Area and that personal information may be accessed from countries outside the United States.
That is a statement about website personal information rather than about a document collection, and it is recorded rather than credited. Verified 12 September 2026.
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.
No independent security attestation was located, and the absence is established through the page inventory rather than assumed. The site navigation and footer render in full and are therefore the inventory under R20: Solutions, Partners, Thought Leadership, Company, Contact, with Privacy Policy and Terms and Conditions in the footer. There is no security page, no trust centre and no compliance page. Note for a future pass that the seed list recorded a security page on the site as present but unconfirmed; **it was checked and no such page exists in the current navigation**, and the Privacy item in the Solutions menu is a product for detecting and extracting personally identifiable information, not a policy surface.
No certification of any kind is claimed anywhere: no SOC 2, no ISO 27001, no HIPAA, no badge, no auditor, no report and no request route. No penetration testing or vulnerability disclosure programme is described. The only security statement on the estate is the Privacy Notice paragraph graded on the stewardship row, which describes no control and disclaims responsibility for third-party hacking. There is accordingly no access flow to grade under R5, because there is nothing to request. Verified 12 September 2026.
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 vendor refers to advanced AI without identifying anything underneath it, which is C. The language across the estate is capability-level and consistent: advanced AI technology, powerful and efficient AI technology, generative AI, and AI review technology that understands grammar and context. No model is named, no version is given, no provider is identified, no hosting arrangement for inference is stated, and nothing commits to notifying a customer when any of it changes.
There is no subprocessor list on any surface, and neither published document names a processor. One architectural fact is disclosed and is worth crediting as far as it goes: the vendor states that no additional indexing or model training is required to run the same instructions against a further document set, which tells a reader the product does not fine-tune on the customer's collection and works by instruction rather than by training.
That is a statement about method, not about supply. The gap is material on this product because documents leave the customer's Relativity workspace and are submitted to the vendor for classification, so a firm is asked to send a litigation collection to an unnamed model. Verified 12 September 2026.
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 information is published at any level, including the unit of charge, which is the D band. There is no pricing page in the navigation and none was located anywhere on the estate. No plan or tier is named, no rate or band appears, no minimum or term is stated, and nothing indicates whether the product is charged per document, per gigabyte, per matter, per classification run or by subscription, which is the first question a litigation support manager would ask of a review tool.
The only commercial route published is a demonstration booking, repeated as the call to action on every page, with a telephone number and a support address as the sole contacts. Under R10's closing discipline a page that only invites a sales conversation is an absence and belongs in this note alone, so no VendorPricing row is written for this record. Recorded because it sharpens the point rather than softens it: the vendor's central commercial claim is that review is completed at a fraction of the time and cost of conventional manual review, and no figure anywhere allows a buyer to test that against what a contract-attorney review would actually cost. Verified 12 September 2026.
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.
Coverage is described by capability rather than by who the product serves, and the breadth is claimed without being evidenced, which is C. What is published is a product taxonomy: four suites covering early case intelligence, review, privacy and multimedia, each with named components. The buyer is identified only in general terms, as legal professionals and legal teams, with a Partners page indicating that eDiscovery service providers are a channel, and the Relativity plug-in delivery implying a firm or provider already running that platform.
Beyond that, nothing. No practice area is named, no matter type is identified as suited or unsuited, no firm segment or size is addressed, and no distinction is drawn between what a law firm, a corporate legal department and a service provider would each use. There is no jurisdictional statement of any kind, which matters more than usual on a product making privilege determinations, since privilege doctrine and the treatment of in-house counsel communications differ materially between United States federal practice, state practice and other jurisdictions, and nothing published says which the privilege classifier is built for. Verified 12 September 2026.
2 public documents
The public pages on file for eDiscovery AI, 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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ediscoveryai.com/review7 signals
Ethical Walls and Matter Segregation, Primary Law Corpus Provenance, Good Law Verification and 4 more
Read Sep 12, 2026
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ediscoveryai.com/privacy-policy4 signals
Client Data in Training, Prompt and Output Retention, Third Party Request and Subpoena Notice and 1 more
Read Sep 12, 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?
A published agreement or policy exists and none of it addresses the question either way, or the document that would answer it could not be read and the summary names the retrieval limit. The summary states which shape the silence takes: an improvement right granted that never names training, or no improvement right granted at all.
A published policy exists, it grants an improvement right, and it never names training, which is this value's first shape. Both published documents were read in full on the date shown. The Privacy Notice, last updated 8 January 2025, lists among its purposes the use of personal information for analytical purposes and to research, develop and improve programs, products, services and content. That is an improvement right that says nothing about model training either way.
Two scope points belong in the reading and neither rescues the position. The notice scopes itself to information collected on or through the vendor's websites or through other interactions with the vendor and its clients, so it does not clearly reach the document collections submitted for classification at all. And it names as a source of personal information the vendor's clients with whom it provides services, so client-supplied material is contemplated somewhere in its scope without being addressed on this question.
The Terms and Conditions, last updated 23 May 2024, are a website terms-of-use template with no data provisions. **No customer agreement is published anywhere on the estate.** One adjacent architectural statement is recorded and not credited: the vendor states that no additional model training is required to run the same instructions against a further document set, which describes method rather than a commitment.
Prompt and Output Retention
How long does the product keep what a lawyer typed, and can that be set to zero?
No located public material states how long prompts and outputs are retained.
No located public material states how long submitted documents, prompt instructions or returned classifications are retained. The Privacy Notice does carry a retention section, and it does not reach this question: it is scoped to personal information collected through the website, sets no period, and gives only criteria, being the length of the ongoing relationship, any legal obligation, and whether retention is advisable in light of the vendor's legal position.
Nothing addresses the document collection itself. Nothing states whether a customer's classified set is deleted at the end of a matter, whether the instructions written for a review are retained, whether returned classifications and privilege log drafts persist on the vendor's side after being written back to Relativity, or whether a customer can require deletion. The Terms and Conditions contain no data provisions at all.
The question has particular force on this product because documents leave the customer's own review platform and are submitted to the vendor for processing, so the retention answer determines whether a second copy of a litigation collection exists and for how long. Both published documents were read in full and no customer agreement is published.
Ethical Walls and Matter Segregation
Does retrieval respect the firm’s ethical walls, or can the model read across them?
No located public material addresses walls or matter level segregation.
No located public material addresses walls or matter-level segregation. Nothing published describes a permission model, user roles, access groups, conflict screening, or separation between one customer's document set and another's. The Privacy Notice, read in full, says only that the vendor takes a number of steps to protect against loss and misuse of information under its control, and the Terms and Conditions contain no access provisions.
One point of architecture is recorded because it bears on where the question sits rather than answering it: the product runs as a plug-in to Relativity, so the review platform's own permissions and workspace boundaries govern who can see a document inside the customer's environment, and what is unaddressed is what happens on the vendor's side once a set has been submitted for classification. Nothing published states whether collections from different customers or different matters are isolated during processing, and no subprocessor or infrastructure statement exists that would let a reader infer it.
Established as an absence on the surfaces read: the four solution pages, the review workflow and both published legal documents.
Third Party Request and Subpoena Notice
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
Published terms or policy address disclosure to authorities or in response to legal process, and no commitment or reservation regarding customer notice is located anywhere. The vendor has told the customer that data can leave and has said nothing about whether the customer hears of it.
Disclosure to authorities is addressed and customer notice is absent, which is this value. The Privacy Notice states twice, once in its general sharing section and again in the California section, that the vendor may share personal information to comply with a court order or other legal process or requirements, or to protect the safety of users or others, or to protect its own rights or the rights of others. It goes further than most in the same breath, adding that it may share or use personal information for any other legally permitted business purpose upon its sole discretion.
Nothing anywhere commits the vendor to notify a customer of a demand, reserves discretion over whether to notify, promises to seek a protective order, or sets any timeframe. No transparency report exists. The scope limit is recorded and does not change the value: the notice governs personal information collected through the website rather than a submitted document collection, so for the litigation material the product actually processes the position is not addressed at all, no customer agreement being published. On a vendor holding a second copy of an opponent's production, that is a live question.
Primary Law Corpus Provenance
Where does the law in this product come from, and does the vendor have the right to use it?
Sources are identified without stating the licence or rights basis.
The working corpus is identified unambiguously and nothing behind it is, which is this value. What the product reads is the customer's own document set and nothing else: the reviewer selects the documents, writes the relevance, issue, privilege and category specifications, and submits that set through the Relativity plug-in for classification. There is no external legal corpus, no caselaw database and no reference collection, and the vendor makes no coverage claim that this signal would otherwise test.
The rights position on the customer side is not stated anywhere, no published document addressing what the vendor may do with a submitted collection, and no customer agreement exists on the estate. Behind the classification sit unnamed models: no provider, no version, and nothing about what they were trained on, which matters here because a privilege classifier's judgement about attorney-client communications is a function of what it learned privilege looks like.
One architectural statement is credited as far as it goes: the vendor states that no model training is required to run the same instructions against additional documents, so the customer's collection is not itself used to build a model for that review.
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.
No located public material addresses whether authority is checked for subsequent history, and on this product class the question does not arise in its usual form. The product cites no cases, statutes or regulations to a reader. It classifies documents from a litigation collection against instructions the reviewer writes, explains why it classified each one, identifies attorneys, sets out privilege elements and drafts privilege log entries.
Nothing it produces is a proposition about the state of the law that a lawyer would check for later treatment. The nearest adjacency is the privilege determination, which applies a legal doctrine rather than citing an authority, and nothing published states which jurisdiction's privilege law the classifier is built around or how doctrinal change would be reflected. That is recorded here rather than graded, and the jurisdictional half of it is graded on the Firm and Practice Coverage row.
Recorded so the row states the position rather than leaving a reader to infer it from the product category. The four solution pages, the review workflow and both published legal documents were read on the date shown.
Refusal and Uncertainty Behaviour
What does the product do when the answer is not in the corpus?
No located public material addresses what the product does when it cannot ground an answer.
No located public material addresses what the product does when it cannot classify a document with confidence. What is published is explanation rather than abstention, and the distinction matters because the explanation is genuinely good. Every classification carries a restatement of the instruction the model was given and an account of why the document was categorised as it was, and privilege output sets out which elements of the privilege are present so a reviewer can see the strength of a call.
Those let a reviewer disagree with an answer; they do not describe the system declining to give one. Nothing published states that a document can be returned unclassified, flagged as borderline, routed for human decision, or accompanied by a confidence score. The privilege elements field is the closest thing to a graded output on the estate, and it grades the legal strength of the claim rather than the model's certainty about its own reading, so it is recorded here rather than treated as a confidence signal.
The gap is real on a workflow that runs across hundreds of thousands of documents in hours, where the ambiguous document is the one a reviewer most needs surfaced.
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.
Searched on 12 September 2026, on the product name with a vendor qualifier and on the corporate name, against published trackers of decisions on AI-generated fabricated citations including coverage of the Damien Charlotin AI Hallucination Cases database and two independent sanctions trackers, for any court order, opinion or disciplinary record addressing fabricated or hallucinated legal citations produced by this product.
None located. This is a statement about the public record on that one subject as of the date shown, and under R119 this signal records fabricated citations and nothing else, so it is not a litigation history and no other proceeding involving the vendor would appear here. Two notes for a future reader. The vendor's name is the name of the practice area, so a bare search returns the general eDiscovery sanctions literature and every query needs a vendor qualifier.
And this product does not generate citations to authority at all, so the exposure this signal tracks is not the shape this product presents; its analogous failure mode is a misclassified privileged document, which no tracker records.
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.
No located public material engages with bar or ethics guidance. No bar opinion is named on any surface read, ABA Formal Opinion 512 does not appear, no state guidance on generative AI in legal practice is referenced, and nothing maps the product to any rule of professional conduct. Nor is professional responsibility referred to in general terms, which is what separates this from the tier above: neither published document mentions professional obligations, competence or supervision, and the product pages address efficiency, accuracy and cost rather than duty.
The absence is worth stating plainly because the product operates in the one part of legal AI where a professional-conduct framework already exists and is well developed: privilege review sits directly on the duty of confidentiality, and technology-assisted review has a decade of judicial and bar commentary on defensibility behind it. Named here as a surface not opened under the sufficiency discipline, and as the likeliest place the position would be found if it exists: the vendor publishes a substantial practitioner library of fact sheets, whitepapers, case studies and books on AI document review.
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.
Cost savings are the central claim and nothing addresses billing or disclosure, on work that sits squarely inside a fee relationship. The claims are repeated across the estate: document reviews completed in a fraction of the time and cost of conventional manual review, hundreds of thousands of documents reviewed in hours, and the important documents identified immediately at a fraction of the cost. Document review is the paradigm case this signal was written for.
It is among the largest line items in litigation, it is conventionally billed to the client either as attorney time or as a vendor cost passed through, and replacing it with machine classification changes that number by an order of magnitude. Nothing published addresses what happens to the bill, whether AI-assisted review is identified on an invoice or in a budget, or whether the client is told. No pricing is published at all, so a firm cannot even see what the substitution costs.
One route the vendor could take and does not is recorded: the workflow already generates per-project performance metrics for validation, which is the nearest thing on this estate to a per-matter record of AI-assisted work, and it is presented as a defensibility artifact rather than a billing one.
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.
No located public material supports a client-side disclosure obligation, and none of the three artifacts this signal looks for exists. There is no subprocessor list on any surface. No model provider is named anywhere, so a firm asked by a client which third party processed its documents could not answer from anything published. There is no data processing addendum, no security exhibit, no certification and no client-facing disclosure pack that could be forwarded.
The value is not on-request, because nothing indicates such material exists behind a sales conversation: there is no security page, no trust centre, no compliance contact and no request mechanism published, and the site navigation renders in full so that is the inventory. The two documents that do exist were read in full and neither serves: the Privacy Notice is a website notice that scopes itself away from client document collections, and the Terms and Conditions are a website terms-of-use template with no data provisions.
This matters more than the bare grade suggests on a product delivered through Relativity, because the firm's client is often a corporate legal department with its own outside counsel guidelines governing exactly this question.
Court Disclosure Support
If a judge’s standing order requires an AI disclosure, can the product produce one?
Some elements of the record are available, short of a document level export.
Several elements of a record exist and no document-level export is described, which is this value, and the elements here are the strongest in this lane because defensibility is the discipline this product class already lives under. Per document, the output carries the classification, a restatement of the instruction the model was given, and an explanation of why the document was categorised as it was, produced consistently across every document and every classification.
Privilege adds more: the attorneys identified and named in their own field, the elements of the privilege present, and a document summary with the privilege reasoning drafted as a log entry. At the project level the published workflow ends in validation and the generation of industry standard performance metrics, which in this field means recall and precision against a sample, and which is precisely what a party is asked to produce when an AI-assisted review is challenged.
What is missing is the model. Nothing identifies which model produced a classification, no version or provider is named, and nothing records when the model or the instructions changed mid-review, so the one element a court would need to assess reproducibility is absent. No disclosure template, certification form or ESI-protocol guidance was located.