Alexi vs Midpage: how they compare in 2026

The artificial intelligence is the product. The vendor describes itself as a private single tenant AI engine, built originally to generate evidence backed research memos, with a proprietary model layer and a retrieval first architecture. Remove the models and there is no product: memo generation, precedent finding, chronology building and workflow automation are all model driven. Return to A after three consecutive B grades on this axis in the contract cohort, which is the axis behaving as designed rather than drifting.

The artificial intelligence is the product. Midpage is a legal research and brief generation platform where retrieval, synthesis and drafting are all model driven; there is no underlying workflow or document management system that would remain if the models were removed. The company was founded in 2022, after the generative wave rather than before it, and the product is distributed both standalone and as an integration inside ChatGPT, which is a distribution model only an AI native product can have.

Independently measured accuracy with a published methodology, the first such record on the index. Alexi submitted to the 2025 Vals Legal AI Report legal research study, run by an outside evaluator that published its rubric and weights in advance: accuracy at 50 percent, authoritativeness at 40 percent, appropriateness at 10 percent, across 200 United States legal research questions sourced from attorneys at named firms. Per the evaluator's own published results, Alexi scored a 77 percent weighted aggregate, placing second of the four systems measured behind Counsel Stack at 78 percent, and ahead of Midpage at 76 percent and a generalist model at 74 percent, against a lawyer baseline of 69 percent aggregate. Architecture is described rather than asserted, as retrieval first specifically to ground output in primary law rather than model memory. Two qualifications recorded, neither of which removes the A, because the underlying figures are independently produced and checkable by an outsider. First, the vendor's own published account of these results is selective: it leads with 80 percent overall accuracy against a 71 percent lawyer baseline and 79 percent single jurisdiction accuracy described as tied for the highest, which are favourable component scores, and does not state that it placed second on the evaluator's weighted aggregate. A reader relying on the vendor's page would form a different impression from one reading the evaluator's. Second, the evaluator and trade press both record that several major vendors declined to participate and at least one participated but withheld permission to publish, so the comparative field is self selected. Also recorded from the evaluator: all systems measured, this one included, struggled on multi jurisdictional questions and underperformed a generalist model on fifty state statutory surveys.

Independently measured accuracy with a published methodology and published per criterion figures, the second such record on the index. Midpage submitted its standalone research product to the 2025 Vals Legal AI Report legal research study, run by an outside evaluator. The evaluator published its rubric and weights in advance: accuracy at 50 percent, authoritativeness at 40 percent, appropriateness at 10 percent, across 200 United States legal research questions sourced from attorneys at named firms including Reed Smith, Fisher Phillips, McDermott Will and Emery, Ogletree Deakins, Paul Hastings, and Paul Weiss. Midpage scored 78 percent accuracy, 74 percent authoritativeness and 70 percent appropriateness, a 76 percent weighted aggregate, beating the lawyer baseline by 7 points on accuracy and 6 on authoritativeness. Those figures sit on the evaluator's own site and are checkable by an outsider without reference to any vendor claim. The evaluator also published the failures, which is why this is a strong A rather than a marketing one: it recorded three cases where Midpage returned no response at all due to technical issues, and eight cases where it explained it could not locate supporting documents. Also recorded from the same source: all evaluated systems, this one included, underperformed a generalist model when asked to survey all fifty states for a single statute, and struggled on multi jurisdictional questions generally.

Autonomy is claimed and oversight is asserted without a described mechanism. The product runs multi step workflows that carry legal principles and citations through successive stages, and the vendor states that consistent verifiable accuracy is what makes that automation safe, which is an argument for trusting the system rather than a control structure around it. The CEO has spoken publicly about human oversight in the context of a long term vision for AI assisted arbitration. Searched the vendor site, the FAQ, the workflow and product pages and the blog on 29 Aug 2026 and located no description of what a workflow does unaided, no threshold at which it stops or escalates, no review surface a lawyer is given, and no statement of what the vendor commits to when an output is wrong. For a product whose stated advantage is that accuracy carries through each stage of an automated chain, the absence of a published stopping rule is the notable gap.

Searched the vendor site, the product pages and third party coverage on 29 Aug 2026. No published position was located on what the system does unaided, what a lawyer must review, where a workflow stops, or what the vendor commits to when an output is wrong. The evaluator's report records that the product sometimes explained it could not locate supporting documents rather than answering, which is observed behaviour rather than a published oversight model, and it was not treated as one. Rebuttable with a single link to any published statement on human review.

Customer claims stand in for evidence. The vendor states it is trusted by leading law firms and describes buyer roles precisely as CIOs and CTOs, knowledge management leaders, innovation teams, practice group leaders and managing partners, which is useful for a reader but is a market description rather than a deployment record. Searched the vendor site, the blog, the FAQ and the news announcements on 29 Aug 2026 and located no named customer, no case study pairing an organisation with figures and a date, and no method a reader could assess. The strongest quantified material on this property is benchmark performance rather than production outcome, and the two are different things: the Vals figures show how the system performs on a test set, not what changed at a firm that deployed it.

Independent benchmark performance stands where deployment evidence would go. The strongest evidence attached to this vendor is measured test set performance from an outside evaluator, which is real and unusual but is not a production outcome: it shows how the system performs on 200 constructed questions, not what changed at a firm that adopted it. Searched the vendor site, the product pages and third party coverage on 29 Aug 2026 and located no named customer, no case study pairing an organisation with figures and a date, and no assessable deployment method. The evaluator does record that the study questions were sourced from attorneys at named firms, but those firms contributed test material rather than being disclosed as customers, and the two must not be conflated.

CORRECTED 29 Aug 2026 during the trust portal sweep. Previously graded B because no training statement had been located, which was the limb holding it down. The statement exists and was missed: the vendor's FAQ states that nothing leaves the firm's private environment and that a firm's prompts, documents and workflow data never train global models and never mix with other firms, and a document management partner's listing independently records no training on customer data. That answers both the training question and the pooling question in the negative and in plain terms. Segregation was already the strongest element and is now better evidenced: every firm on the private cloud model receives a fully isolated single tenant instance, and the vendor enumerates what is isolated rather than leaving it general, covering retrieval, workflows, memory, security protocols and governance. Memory being named in that list matters, because an AI platform that learns from firm usage could otherwise carry one firm's accumulated intelligence toward another. Supporting controls: AES-256 encryption, TLS 1.2 or higher, single sign on, role based access control and audit logs, under SOC 2 certification. Two limbs are therefore fully answered and the third is not: no retention period or deletion commitment was located, which is recorded on the retention signal row. Graded A on the same basis as Noxtua, where training and segregation were both strong and no retention period was published.

CORRECTED 29 Aug 2026 during the trust portal sweep. Previously graded D on the finding that nothing at all was located on how client confidences are handled. That was wrong: the vendor publishes a security page which was not reached in the original pass, and it answers two of the three limbs this axis tests more precisely than most records here. Training is addressed at both layers and in the negative: Midpage does not use customer data to train or fine tune AI models, and its agreements with AI model providers do not permit those vendors to train on Midpage customer data. Retention is published with actual periods rather than in general terms: web app data including user queries, uploaded materials and generated outputs is held while an account remains active and deleted within 60 days of account deletion or a valid deletion request; for plugins and integrations no submitted queries, uploads or outputs are stored at all, though those workflows may share queries with model providers who may retain them for up to 60 days. Disclosing the model provider retention window rather than only its own is unusually candid. Encryption is specified as AES-256 at rest and TLS 1.2 or higher in transit, and subprocessors are contractually required to maintain measures no less protective. Controls are stated to be independently validated through an annual SOC 2 Type II audit. Held at B rather than A because the third limb is unaddressed: no segregation model between customers, users or matters was located, and attorney client privilege and work product are not treated directly.

The audience is unambiguously lawyers and law firms, with named buyer roles inside firms and no consumer or non lawyer surface located, which is cleaner than most of this index. The vendor engages publicly with the hallucination problem in filings and positions accuracy as a professional risk question. Searched the vendor site, the FAQ, the blog and the product pages on 29 Aug 2026 and located no published position on the advice line, no treatment of competence or supervision duties, and no statement of jurisdiction limits, despite the product spanning Canadian and US law where the applicable professional rules differ. Recorded at C because the position is inferable from who the product is sold to rather than published.

The stated audience is litigators and law students, which is a lawyer and trainee population rather than a consumer one, and the vendor is explicit about it. That student audience is worth recording: it is the first record on the index whose published audience includes people who are not yet admitted, which is a professional responsibility question of a different shape rather than a UPL problem. Searched the vendor site, the product pages and third party coverage on 29 Aug 2026 and located no published position on the advice line, no treatment of competence or supervision duties, and no jurisdiction limits. Recorded at C because the audience is stated clearly while the position is not.

Principles and evaluation results are published without a governance mechanism. The vendor's substantive contribution here is real and rare: it submitted to an independent third party evaluation and published the results, and it argues publicly that transparency and accountability in legal AI require exactly that rather than marketing claims. Submitting to outside measurement is a governance act. But it is a point in time evaluation rather than a management system. Searched the vendor site, the FAQ, the blog and the news announcements on 29 Aug 2026 and located no AI governance framework, no AI management certification such as ISO 42001, no named owner of model governance, no pre release testing gate, and nothing on uneven output across matter types, parties or populations.

Submitting to independent evaluation is the governance act on this record, and it is a real one. Midpage was one of only four systems that agreed to be measured and named in the Vals legal research study, in a field where the evaluator and trade press both recorded that major vendors declined to participate and at least one participated but withheld permission to publish its results. Agreeing to publication including your own failure cases is a meaningful accountability position. But it is a point in time evaluation rather than a management system. Searched the vendor site and third party coverage on 29 Aug 2026 and located no AI governance framework, no AI management certification, no named owner of model governance, no pre release testing regime, and nothing on uneven output across matter types, parties or populations.

CORRECTED 29 Aug 2026 during the trust portal sweep. Previously graded C because the architecture was doing the work a published policy would normally do, with no encryption specifics, access control detail or attestation located. The vendor's security page and FAQ, not reached in the original pass, supply that detail. Published: AES-256 encryption at rest, TLS 1.2 or higher in transit, single sign on, role based access control, audit logs, support for private VPC deployment, and region specific deployments for firms operating across offices. Architectural isolation was already recorded and stands: a fully isolated single tenant instance per firm covering retrieval, workflows, memory, security protocols and governance. SOC 2 certification underpins the control set, and a Trust Center provides a request route to a security addendum, architecture whitepaper, data processing agreement and audit reports. Not located as of 29 Aug 2026, and why this is B rather than A: a stated retention period or deletion control for research queries, uploaded case files and generated memos, a named subprocessor list, and an incident or breach notification practice.

CORRECTED 29 Aug 2026 during the trust portal sweep. Previously graded D on the finding that no retention period, deletion control, access control detail, encryption statement, subprocessor list, hosting disclosure or incident practice was located. The vendor's security page supplies most of that. Published: AES-256 encryption at rest and TLS 1.2 or higher in transit using industry standard algorithms; a stated retention and deletion practice with a 60 day outer bound following account deletion or a valid deletion request; zero storage of queries, uploads and outputs for plugin and integration workflows; disclosure that model providers may retain submitted queries for up to 60 days; a contractual flow down requiring subprocessors to maintain security measures no less protective than the vendor's own; and independent validation of the whole control set through an annual SOC 2 Type II audit. Additional detail on service providers and data handling is available on request. Not located as of 29 Aug 2026, and why this is B rather than A: a named subprocessor list as distinct from the contractual flow down, a hosting provider or region disclosure, and an incident or breach notification practice.

Searched the vendor site navigation, the FAQ, the product and workflow pages, the blog and the news announcements on 29 Aug 2026. No published indemnity, liability cap, carve out, warranty on output or insurance position was located, and no customer terms of service or master agreement was located as published on the property. Recorded as a pure absence on the surfaces reached. Worth noting the shape of the gap: this vendor stakes its positioning on measured accuracy and on reducing the risk of hallucinated citations reaching a filing, and publishes nothing about who bears the loss if one does.

Searched the vendor site navigation, the product pages and third party coverage on 29 Aug 2026. No published indemnity, liability cap, carve out, warranty on output or insurance position was located, and no customer terms of service was located as published on the property. Recorded as a pure absence on the surfaces reached. The exposure is worth naming: this is a litigation research product whose output is authority bound for filings, in a market where the published sanctions record for fabricated citations is growing, and nothing published addresses who bears the loss.

One integration is named and none is documented. A product integration with iManage is announced, which is the legal specific document management connector that matters most for a firm facing research product and which several better resourced vendors on this index lack. Searched the vendor site, the FAQ, the product pages and the news announcements on 29 Aug 2026 and located no integrations index, no other named connector for practice management, court filing or Microsoft Word, and no documentation describing what the iManage integration moves, in which direction, or what an administrator configures. Recorded at C because the connection is announced rather than documented.

One integration is named and none is documented, and the one named is unusual. The product is accessible inside ChatGPT through what the evaluator describes as a bespoke integration, which is a distribution channel into a general purpose assistant rather than a connection into a firm's own systems. Searched the vendor site, the product pages and third party coverage on 29 Aug 2026 and located no legal document management connector such as iManage or NetDocuments, no practice management or court filing integration, no Microsoft Word add in, and no documentation of what the ChatGPT integration passes or what an administrator configures. For a product whose buyers are litigators inside firms, the absence of any firm system connector is the notable gap.

Deployment model is stated clearly with partial residency detail, which is the B band. Two models are published and the difference between them is meaningful: a private single tenant environment per firm as the default, and private cloud deployment for firms wanting complete ownership and control of their own data. Single tenancy by design is stronger than most of this index offers and it is stated as architecture rather than as an enterprise upsell. What is missing is geography: searched the vendor site, the FAQ and the product pages on 29 Aug 2026 and located no named regions, no customer selectable residency, and no statement of where processing happens as distinct from where data is stored, which matters for a vendor operating across both Canadian and US jurisdictions.

Searched the vendor site, the product pages and third party coverage on 29 Aug 2026, and ran targeted searches for security or infrastructure documentation without reaching any. Nothing was located on the deployment model at all: no tenancy statement, no hosting provider, no region, no residency option, and no statement of where processing happens. The product is evidently cloud delivered and reachable through a browser and through ChatGPT, but that is inference from how it is sold rather than a published position, and inference earns nothing on this axis.

CORRECTED 29 Aug 2026 during the trust portal sweep. Previously graded D on the finding that no independent security attestation of any kind was located and no trust portal existed. That was wrong on both counts. The vendor publishes a dedicated security page stating SOC 2 certification, and operates a Trust Center reached through a request access flow, which it states carries a security addendum, an architecture whitepaper, a data processing agreement and audit reports. That is a self serve request route to substantive diligence material rather than a sales gate, and the document set named is broader than most on this index. SOC 2 certification is separately corroborated on the vendor's own platform pages, its about page, its FAQ and by a document management partner's technology listing. Supporting controls published on the FAQ: AES-256 encryption, TLS 1.2 or higher, single sign on, role based access control, audit logs and support for private VPC deployment. Short of an A because no coverage period, audit scope, report date, SOC 2 type designation or named auditing firm was located, and because the certification is asserted on marketing pages rather than evidenced by a certificate reached in this pass.

CORRECTED 29 Aug 2026 during the trust portal sweep, superseding an earlier correction in the same session. The row was first graded D on the basis that no attestation was located anywhere, then raised to C when a customer of this vendor, GC AI, published that Midpage is SOC 2 Type II compliant. Both readings were working around the fact that the vendor's own security page had not been reached. It has now. The vendor states directly that its controls are independently validated through an annual SOC 2 Type II audit, which supplies the cadence as well as the standard, and states that on request it can provide SOC 2 documentation, questionnaire responses and additional detail on service providers and data handling. That is a published request route to substantive diligence material rather than a sales gate. The earlier observation that a buyer should not have to learn a vendor's security posture from a competitor's blog no longer applies and is withdrawn: the vendor publishes it itself. Short of an A because no coverage period, audit scope, report date or named auditing firm was located, and no trust portal exists, the route being a request to the vendor.

The vendor refers to proprietary models without identifying what sits underneath them. Published: a proprietary model layer the vendor brands as Alex, described as trained specifically on law rather than general purpose, and a retrieval first architecture. That tells a buyer the shape of the stack and that a specialist layer exists. Searched the vendor site, the FAQ, the product pages and the blog on 29 Aug 2026 and located no named foundation model or provider underneath the proprietary layer, no statement of where models run, no subprocessor list, and no commitment to notify customers when the supply chain changes. A private single tenant environment narrows the exposure question without answering it.

Searched the vendor site, the product pages and third party coverage on 29 Aug 2026. No model, provider, hosting location or subprocessor was located, and no commitment to notify customers of supply chain changes. The evaluator's report distinguishes Midpage's standalone research product from its ChatGPT integration, which tells a reader the product runs independently of that channel, but nothing published identifies what powers the standalone product. A buyer cannot determine from published material which company processes their research queries.

Checked the vendor site navigation, the FAQ, the product and workflow pages and the blog on 29 Aug 2026. No pricing page was located, no rate is published, no unit of charge is stated and no tier structure appears. Every commercial path located terminates in a demo or contact request. No free trial or self serve entry point was located, and no third party pricing figure was located either.

Checked the vendor site navigation, the product pages and third party coverage on 29 Aug 2026. No pricing page was located, no rate is published, no unit of charge is stated and no tier structure appears. No free trial or self serve entry point was located on the vendor's own property, and no third party pricing figure was located either. Noted for a reader: the product being reachable through a ChatGPT integration may mean some access runs on that platform's commercial terms rather than the vendor's, which published material does not clarify.

Segment and practice coverage is described with substance, short of the boundaries. The buyer is law firms specifically, and unusually the vendor names the roles inside them: CIOs and CTOs, knowledge management leaders, innovation teams, practice group leaders and managing partners. Practice coverage spans litigation, transactional, operational and administrative work, with a published practice area treatment for personal injury covering case file summarisation, chronology building and memo drafting. Jurisdictional scope is Canada and the United States. Not located as of 29 Aug 2026: any statement of which firm sizes or practice areas the product is not built for, and any enumeration of jurisdictional coverage at state or provincial level, which for a research product is the boundary a buyer needs most.

Practice focus and jurisdictional coverage are both stated with real substance. The practice position is narrow and explicit: purpose built for litigators, with the evaluator independently confirming the product is focused on supporting litigator workflows and that its responses are tailored to the research questions litigation practice actually produces. Jurisdictional coverage is enumerated by court system rather than claimed broadly, spanning United States federal and state courts, tribal courts and military courts, plus statutes, regulations and selected administrative decisions. Naming tribal and military courts specifically is a level of precision no other record on this index reaches. Short of an A because the segment is described by practice type without addressing firm size, and because no statement of what the product does not cover was located, with the independently measured weakness on fifty state surveys and multi jurisdictional questions coming from the evaluator rather than the vendor.

CORRECTED 29 Aug 2026 during the trust portal sweep. Previously recorded as silent on the finding that no statement existed either way, with the vendor's compounding intelligence language noted as the nearest thing. The statement does exist and was missed. The FAQ states that nothing leaves the firm's private environment and that a firm's prompts, documents and workflow data never train global models and never mix with other firms. A document management partner's technology listing independently records no training on customer data. Read together these answer both questions this signal asks: whether customer content trains the vendor's models, and whether one customer's material can benefit another. The commitment sits on a public FAQ and a partner listing rather than in a customer agreement reached in this pass, and the vendor's Trust Center is stated to carry a data processing agreement that would presumably carry it contractually. Recorded at policy never on that basis. The earlier reading of the compounding intelligence language now reads correctly as consistent with this: a firm's accumulated intelligence stays inside its own single tenant instance, which the vendor states includes memory.

CORRECTED 29 Aug 2026 during the trust portal sweep. Previously recorded as silent on the finding that no statement existed either way, with the note observing that the ChatGPT distribution channel added an unaddressed layer. The statement exists on the vendor's security page, which was not reached in the original pass, and it covers both layers. The vendor states it does not use customer data to train or fine tune AI models, and separately that its agreements with AI model providers do not permit those vendors to train on Midpage customer data. The second is a contractual constraint on third parties rather than a policy the vendor could revise alone. The distribution point raised earlier is also partly answered: the vendor distinguishes plugin and integration workflows, stating it does not store queries, uploads or outputs from them while acknowledging those workflows may still share submitted queries with model providers, who may retain them for up to 60 days. That is a candid account of what happens when the product is reached through another surface, and it is more than most vendors disclose about their own layer, let alone a partner's.

Searched the vendor site, the FAQ, the product pages and the blog on 29 Aug 2026, and ran a targeted search for a security page or trust centre. No public material states how long research queries, uploaded case files or generated memos are retained, whether a firm controls the window, or whether deletion is available. The vendor states the firm owns and controls its data within its private environment, which addresses who controls it rather than for how long it is held. Material here includes uploaded case files and medical records by the vendor's own description of personal injury use, so the retention question is sharp.

CORRECTED 29 Aug 2026 during the trust portal sweep, and this now reads as one of the two strongest retention disclosures on the index. Previously recorded as not addressed on the finding that no public material stated a period, a control or a deletion route. All three exist on the vendor's security page. Published: web app data, expressly including user queries, uploaded materials and generated outputs, is held while an account remains active and deleted within 60 days of account deletion or a valid deletion request, so the customer triggers deletion and a published outer bound applies to it; for plugins and integrations no submitted queries, uploads or outputs are stored at all; and model providers may retain submitted queries for up to 60 days, which is a disclosure about a third party's window that almost no vendor makes. Recorded at customer controlled on the same basis as GC AI, where deletion on demand was treated as control over how long data persists, and this record is stronger because a maximum is published alongside the right. Short of the top value because the zero retention path is a property of the plugin and integration surface rather than a setting a customer can select for the web app, which is the closest any record on this index has come to that value without reaching it.

The product maintains its own documented separation model, and at the customer boundary it is architectural rather than policy based: each firm receives a private single tenant AI environment, with private cloud deployment available. That is strong separation between firms. What is not addressed is separation inside a firm, which is where ethical walls actually operate: no material was located on whether retrieval respects matter level permissions per user, and the iManage integration is announced without any statement that it inherits that system's access model at query time. For a firm facing product that connects to a document management system, that is the limb this signal exists to test.

Searched the vendor site, the product pages and third party coverage on 29 Aug 2026. No vendor material addresses segregation of any kind: not between customers, not between users, not between matters. No document management integration was located whose permissions the product could inherit at query time. Noted for context: a research tool that retrieves from published primary law rather than from a firm's own repository raises this question less sharply than a product indexing client documents, though brief generation from uploaded material would raise it.

Searched the vendor site, the FAQ, the product pages and the blog on 29 Aug 2026, and ran a targeted search for published terms, a privacy policy or a trust centre. No clause committing to notify a firm of a government or law enforcement request for its data was located, and no transparency report was located. No published customer agreement or data processing agreement was reached on the property.

Searched the vendor site, the product pages and third party coverage on 29 Aug 2026, and ran targeted searches for published terms or a privacy policy without reaching one. 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.

Coverage is described by jurisdiction with no identification of the underlying corpus. The product answers questions requiring reference to US federal and state laws, regulations and judgments, per the benchmark it was measured on, and vendor material describes analysing millions of documents including case law, statutes and secondary sources across Canada and the United States. Searched the vendor site, the FAQ, the product pages and the blog on 29 Aug 2026 and located no named source or publisher for the primary law, no licence or public domain basis, no jurisdiction by jurisdiction coverage list, and no update cadence or lag. For a research product this is the axis where provenance matters most, and the strongest published statement is a volume claim.

Coverage is described by jurisdiction and court system with unusual precision, and the sources behind it are not identified. Published coverage spans case law from United States federal and state courts, tribal courts and military courts, plus statutes and regulations and selected administrative decisions. Enumerating tribal and military courts is more specific than any other coverage statement on this index. What is missing is provenance: searched the vendor site, the product pages and third party coverage on 29 Aug 2026 and located no named source or publisher, no licence or public domain basis, no completeness statement per court system, and no update cadence or lag. The word selected in front of administrative decisions is itself an undefined boundary. Recorded at the jurisdictions only value because coverage is stated while its basis is not.

Searched the vendor site, the FAQ, the product and workflow pages and the blog on 29 Aug 2026. No material was located addressing whether authority returned carries a treatment signal, whether subsequent history is checked, or whether any commercial citator is licensed. The vendor's published accuracy work concerns whether a cited authority is valid and real, measured as the rate of valid primary law citation, which is a different question from whether that authority is still good law. First genuine research product on the index to record this absence, and unlike the contract vendors before it the signal is squarely inside this product's design rather than outside it.

Searched the vendor site, the product pages and third party coverage on 29 Aug 2026. No material was located addressing whether authority returned carries a treatment signal, whether subsequent history is checked, or whether any commercial citator is licensed. The independent evaluator measured authoritativeness, defined as whether cited sources are relevant and valid and support the statements made, and scored this product at 74 percent. Validity in that sense means the source exists and supports the proposition, which is not the same as the source still being good law, and the two were not conflated. Second research product on the index to record this absence where it sits inside the product's design rather than outside it.

Searched the vendor site, the FAQ, the product and workflow pages and the blog on 29 Aug 2026. No published material describes what the product does when it cannot ground an answer, and no explicit no answer path was located. The vendor does state that each firm gets its own accuracy signals, which suggests some confidence surface exists in the product, but nothing located describes what those signals are, whether they are exposed to the user, or how they behave when retrieval returns nothing. Recorded as not addressed rather than at the confidence value because the signals are mentioned without being described.

Abstention behaviour is observed and quantified by an independent evaluator rather than documented by the vendor, which is a first on this signal. The Vals legal research study recorded that in eight cases Midpage acknowledged it was unable to locate the right documents and explained why the available sources did not support an answer, rather than fabricating one, and the evaluator awarded partial credit for the quality of those explanations. Separately and distinctly, it recorded three cases of pure technical failure where no response was returned at all, which is a different thing from principled abstention and is not counted as such. Recorded at the weakest value because the vendor itself publishes nothing on this: searched the vendor site and product pages on 29 Aug 2026 and located no described no answer path and no confidence signal. A reader should weigh the observed behaviour, which is favourable, against the absence of any commitment that it will persist.

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. Worth noting the exposure here is real rather than theoretical: this is a litigation research product whose output is memos and precedent for filings, so unlike the contract vendors preceding it on this index its output can reach a court as cited authority.

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. The exposure is direct for this vendor: a litigation research and brief generation product produces exactly the material that reaches filings as cited authority.

Searched the vendor site, the FAQ, the blog and the news announcements 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 Law Society of Ontario or Federation of Law Societies of Canada guidance given the vendor's Canadian base. The vendor publishes substantial material on the rise of hallucinated citations in filings and on the professional risk that creates, which engages with the consequence the guidance addresses without engaging with the guidance itself.

Searched the vendor site, the product pages and third party coverage on 29 Aug 2026. No engagement with any named ethics opinion or professional guidance was located, including ABA Formal Opinion 512 and state bar guidance. Worth noting given the stated audience includes law students, where a published position on supervised use in an academic setting would be a natural place for such engagement and none was located.

Savings are claimed with nothing published on the client's side of the equation, and this vendor's framing lands closer to the billing question than most. Published: fewer corrections and fewer write offs, a stated 13 percent accuracy lift reducing time lawyers spend revising AI output, and cutting costs while freeing time for higher value tasks. Write offs are a billing concept, so the vendor is explicitly connecting AI quality to what a firm can bill. Searched the vendor site, the FAQ, the blog and the news announcements 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 buyer here is a law firm billing clients by the hour, so the question applies squarely.

Searched the vendor site, the product pages and third party coverage on 29 Aug 2026. No per matter record of AI assisted work intended for fee purposes was located, and no guidance on billing, fee or client disclosure treatment was located. Distinct from most records on this index in that no time savings or efficiency claim was located either: the vendor's published positioning and the evidence attached to it are about research accuracy rather than speed, so there is no savings claim to weigh against the client's side of the equation. Recorded as not addressed rather than at the savings claims value for that reason.

CORRECTED 29 Aug 2026 during the trust portal sweep. Previously recorded as not addressed on the finding that no trust centre, subprocessor list, model provider statement or client facing pack existed. A Trust Center does exist, reached through a request access flow on the vendor's security page, and the vendor states it carries a security addendum, an architecture whitepaper, a data processing agreement and audit reports. A published DPA and audit reports are precisely what a firm responding to a client AI clause needs, and an architecture whitepaper goes further than most vendors offer at any access tier. Recorded at on request on that basis rather than at the subprocessor value, because the specific artifact this signal names was still not located: no subprocessor list and no statement identifying which model providers see client content. The private single tenant architecture remains a genuine partial answer to what such a clause asks, since it bears on where client content goes, and the vendor now has a route through which a firm could obtain the supporting documents.

CORRECTED 29 Aug 2026 during the trust portal sweep. Previously recorded as not addressed, with the note stating a firm could not assemble a response to a client AI clause from anything published. That is no longer accurate. The vendor states that on request it can provide SOC 2 documentation, questionnaire responses, and additional detail on service providers and data handling, which is an explicit offer of the three artifacts a firm most often needs. Published without any request at all: an express no training commitment binding both the vendor and its model providers, retention periods including the model providers' own 60 day window, encryption specifics, and a contractual flow down requiring subprocessors to maintain measures no less protective. A firm could answer most of a standard client AI clause from the public page and obtain the rest through the stated route. Recorded at on request rather than the subprocessor value because no subprocessor list is published and no model provider is named, only the terms binding them.

Some elements of a disclosure record are available. Output is evidence backed by design, with memos citing primary law and the vendor publishing an independently measured rate of valid primary law citation, so what was relied on is visible in the work product itself and its reliability has an external figure attached. Vendor material also describes citations carrying through each stage of a multi step workflow. Two elements are missing: no per document export covering model used, sources retrieved and human verification together was located, and the model is described only as a proprietary layer so the model used could not be stated. Noted for a reader: this is one of the few products on the index whose output plausibly reaches a filing, so a judicial AI disclosure order could reach it.

Searched the vendor site, the product pages and third party coverage on 29 Aug 2026. Output carries citations to primary law by design, so what was relied on is visible in the work product, but no per document export covering model used, sources retrieved and human verification together was located, and no model is identified anywhere in published material so the model used could not be stated. Recorded at not addressed rather than partial record because nothing beyond the citations in the output itself was located. Noted for a reader: of all products on this index, this one's output is among the most likely to reach a court, which makes the absence of a disclosure trail more consequential here than for the contract vendors.