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Midpage

Legal research platform built for litigators and law students doing in depth research, covering case law from United States federal and state courts plus tribal and military courts, statutes and regulations, and selected administrative decisions. Also generates briefs. Available as a standalone product and through a bespoke integration inside ChatGPT. Founded 2022. Participated in the 2025 Vals Legal AI Report legal research study, an independent third party benchmark, where it was evaluated on its standalone research product and scored 78 percent accuracy, 74 percent authoritativeness and 70 percent appropriateness for a 76 percent weighted aggregate, against a lawyer baseline the study measured at 69 percent aggregate and 71 percent accuracy.

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Midpage, 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.

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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.

AA on AI CentralityThe artificial intelligence is the product. Remove the models and there is nothing left to sell.

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. 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.

Source: Vendor Published
AA on Citation Accuracy and Hallucination DisclosureMeasured accuracy is published with the test set described and the failure modes named. Output grounds to primary authority the reader can open, citation status is checked, and the system states when it found no support.

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.

Accuracy is independently measured, with a published method and published figures for each criterion. 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 50 percent, authoritativeness 40 percent and appropriateness 10 percent. The study used 200 United States legal research questions 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. That beat the lawyer baseline by 7 points on accuracy and 6 on authoritativeness. The figures sit on the evaluator's own site, where anyone can check them. The evaluator also published the failures: three cases where Midpage returned no response because of technical issues, and eight where it explained it could not locate supporting documents.

All evaluated systems, this one included, did worse than a general model when asked to survey all fifty states for a single statute, and struggled on questions spanning several jurisdictions.

Source: Third Party Estimated
DD on Autonomy and Oversight ModelNo oversight structure is published for a system that drafts, advises, or acts on a client matter.

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.

No published position is published 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 behavior rather than a published oversight model, and it was not treated as one.

Source: Operator Verified
CC on Operational and Outcome EvidenceCustomer logos and unattributed testimonials stand in for evidence, or results are quoted with no basis stated.

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.

Independent benchmark results stand where deployment evidence would go. The strongest evidence attached to this vendor is test set performance measured by an outside evaluator. That is real, but it is not a production outcome: it shows how the system performs on 200 constructed questions, not what changed at a firm that adopted it. The vendor site, product pages and third party coverage were searched. No named customer, case study pairing an organization with figures and a date, or assessable deployment method is published.

The study questions came from attorneys at named firms, but those firms supplied test material and were not disclosed as customers.

Source: Vendor Published
BB on Privilege and Confidentiality PostureSubstantive published commitments on confidentiality and training use, short of the full picture: commonly silence on segregation between users or matters, or on what the underlying model provider may retain.

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.

The vendor's security page answers two of the three questions precisely. Training is addressed at both layers: Midpage does not use customer data to train or fine tune AI models, and its agreements with model providers do not let them train on Midpage customer data. Retention is published with actual periods. Web app data, including queries, uploads and outputs, is held while an account is active and deleted within 60 days of account deletion or a valid deletion request.

Plugins and integrations store no queries, uploads or outputs, though those workflows may share queries with model providers, who may keep them for up to 60 days. The page discloses the providers' retention window as well as its own. Encryption is AES-256 at rest and TLS 1.2 or higher in transit, subprocessors must maintain measures no less protective, and an annual SOC 2 Type II audit validates the controls. The third question is unanswered.

No separation model between customers, users or matters is published, and attorney client privilege and work product are not addressed directly.

Source: Vendor Published
CC on UPL and Professional Responsibility PostureA boilerplate disclaimer sits in the terms while the marketing describes the product in advice terms, or the intended audience is left ambiguous.

UPL and Professional Responsibility Posture

Whether the vendor is clear that it supplies a tool rather than legal advice, who its audience is, and how it addresses unauthorized practice of law, competence and supervision duties, and jurisdiction limits. ABA Formal Opinion 512 is the reference point. Where the advice line is not the duty a product raises, the axis is read through the nearest professional duty it does raise: judicial conduct rules and the reviewing duty for products sold only to courts, and the duty to bill for time actually spent for products that draft time entries.

The stated audience is litigators and law students, a population of lawyers and trainees rather than consumers, and the vendor is explicit about it. The student audience is worth noting, because it includes people who are not yet admitted, which raises a professional responsibility question of a different shape rather than an unauthorized practice problem. The vendor site, product pages and third party coverage were searched.

No published position on the advice line, no treatment of competence or supervision duties, and no jurisdiction limits are published. The audience is stated clearly and the position is not.

Source: Vendor Published
CC on AI Governance and Bias DisclosureResponsible AI principles are published without a mechanism, a testing regime, or anything a buyer could audit.

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.

Submitting to independent evaluation is the governance act here, 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. The evaluator and trade press both recorded that major vendors declined to take part, and at least one took part but withheld permission to publish its results. Agreeing to publication, including your own failure cases, is a meaningful accountability position.

But it is a single evaluation, not a management system. The vendor site and third party coverage were searched. No AI governance framework, AI management certification, named owner of model governance or testing regime before release is published, and nothing on uneven output across matter types, parties or populations.

Source: Vendor Published
BB on AI Safety and Data StewardshipSubstantive published policy covering most of the ground, short of the full set: commonly no named subprocessor list or no stated incident practice.

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.

The vendor's security page covers most of the ground. It publishes AES-256 encryption at rest and TLS 1.2 or higher in transit using industry standard algorithms. It states a retention and deletion practice with a 60 day outer limit after account deletion or a valid deletion request. Queries, uploads and outputs from plugin and integration workflows are not stored at all, and the page discloses that model providers may keep submitted queries for up to 60 days.

Subprocessors are contractually required to maintain security measures no less protective than the vendor's own, and the whole control set is validated by an annual SOC 2 Type II audit. More detail on service providers and data handling is available on request. Three things are not published: a named subprocessor list, as distinct from the contractual requirement; a hosting provider or region; and an incident or breach notification practice.

Source: Vendor Published
DD on AI Liability and RecourseNothing published on who bears the loss when the system is wrong.

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.

No published indemnity, liability cap, carve out, warranty on output or insurance position is published, and no customer terms of service is published 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.

Source: Operator Verified
CC on Practice Systems Integration DepthIntegrations are listed as logos or marked as coming, with no documentation an implementer could use.

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 is named and none is documented. The product is available inside ChatGPT through what the evaluator calls a bespoke integration, which is a distribution channel into a general assistant rather than a connection to a firm's own systems. The vendor site, product pages and third party coverage were searched. No document management connector such as iManage or NetDocuments, practice management or court filing integration, or Microsoft Word add-in is published, and nothing documents what the ChatGPT integration passes or what an administrator configures. For a product sold to litigators inside firms, the lack of any connector to firm systems is the main gap.

Source: Vendor Published
DD on Deployment Model and Data ResidencyNothing published on where the software runs or where client data sits.

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 vendor site, product pages and third party coverage were searched. Nothing is published on the deployment model: no tenancy statement, hosting provider, region, residency option or statement of where processing happens, and the security page names no host or region. The product is evidently delivered from the cloud, through a browser and through ChatGPT, but that is inferred from how it is sold, not a published position.

Source: Operator Verified
BB on Security Certifications and Trust CenterCertification is real and stated, short of accessible evidence: a named standard without scope, date, or a way to obtain the report.

Security Certifications and Trust Center

Independent attestation a buyer can pull without a sales call: SOC 2, ISO 27001, penetration test summaries, a trust center with current reports and named scope rather than a badge image.

The vendor states directly on its security page 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.

A customer of this vendor, GC AI, separately publishes that Midpage is SOC 2 Type II compliant, which corroborates the vendor's own statement. No coverage period, audit scope, report date or named auditing firm is published, and no trust portal exists; the route is a request to the vendor.

Source: Vendor Published
DD on Model Supply Chain DisclosureNothing published about the model supply chain a customer inherits.

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.

No model, provider, hosting location or subprocessor is published, 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.

Source: Operator Verified
DD on Commercial TransparencyNo pricing information published at any level, including the unit of charge.

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 is published, no rate is published, no unit of charge is stated and no tier structure appears. No free trial or self serve entry point is published on the vendor's own property, and no third party pricing figure is published 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.

Source: Operator Verified
BB on Firm and Practice CoverageSegment and practice coverage is described with substance, short of the boundaries: what is supported is clear, what is not is left open.

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.

Practice focus and jurisdictional coverage are both stated with substance. The practice position is narrow and explicit: the product is built for litigators, and the evaluator independently confirms it focuses on litigator workflows, with responses suited to the research questions litigation produces. Jurisdictional coverage is listed by court system: United States federal and state courts, tribal courts and military courts, plus statutes, regulations and selected administrative decisions.

Naming tribal and military courts is precise. Two things are missing. The segment is described by practice type without addressing firm size. No statement of what the product does not cover is published; the measured weakness on fifty state surveys and questions spanning several jurisdictions comes from the evaluator, not the vendor.

Source: Vendor Published
Sources on file

4 public documents

The public pages on file for Midpage, 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.

Legal Signals

What each signal means

A 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.

Confidentiality and Privilege

Client Data in Training

Can material a lawyer puts into this product be used to train a model?

Never, in policy only

A public policy or trust page states no training on customer content, with no matching term located in the published agreement.

The vendor's security page addresses training at both layers. Midpage says it does not use customer data to train or fine tune AI models, and that its agreements with model providers do not let those providers train on Midpage customer data. The second is a contractual limit on third parties rather than a policy the vendor could change alone. The product is also reached through ChatGPT. For plugin and integration workflows, the vendor says it stores no queries, uploads or outputs, while acknowledging those workflows may still share submitted queries with model providers, who may keep them for up to 60 days.

That is a candid account of what happens when the product is used through another surface. The commitment sits on the security page rather than in a published customer agreement.

Source: Vendor PublishedMidpage does not use customer data to train or fine-tune AI modelsAs of Aug 29, 2026Evidence

Prompt and Output Retention

How long does the product keep what a lawyer typed, and can that be set to zero?

Customer controlled, no zero option

The customer controls the retention window, by product configuration or by contractual instruction, but zero retention is not stated as available.

The vendor's security page publishes retention in detail. Web app data, expressly including user queries, uploaded materials and generated outputs, is held while an account is active and deleted within 60 days of account deletion or a valid deletion request. The customer triggers deletion, and a published maximum applies to it. Plugins and integrations store no submitted queries, uploads or outputs at all. Model providers may keep submitted queries for up to 60 days, a disclosure about a third party's window.

Deletion on demand with a published maximum is control over how long data persists. Zero retention, though, belongs to the plugin and integration surface; it is not a setting a customer can choose for the web app.

Source: Vendor PublishedWe delete web app data within 60 days of account deletion or a valid deletion requestAs of Aug 29, 2026Evidence

Ethical Walls and Matter Segregation

Does retrieval respect the firm’s ethical walls, or can the model read across them?

Not addressed

No located public material addresses walls or matter level segregation.

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.

Source: Operator VerifiedAs of Aug 29, 2026

Third Party Request and Subpoena Notice

If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?

Not addressed

No located term or policy addresses third party requests for customer data.

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.

Source: Operator VerifiedAs of Aug 29, 2026
Accuracy and Authority

Primary Law Corpus Provenance

Where does the law in this product come from, and does the vendor have the right to use it?

Jurisdictions only

Coverage is described by jurisdiction with no identification of the underlying corpus.

Coverage is described by jurisdiction and court system with 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, regulations and selected administrative decisions. What is missing is provenance. The vendor site, product pages and third party coverage were searched on 29 Aug 2026. No named source or publisher, license or public domain basis, completeness statement for each court system, or update schedule or lag was located.

The word selected in front of administrative decisions is itself an undefined boundary. Coverage is stated while its basis is not.

Source: Vendor PublishedAs of Aug 29, 2026Evidence

Good Law Verification

Does the product tell you when the authority it just cited has been overruled?

Not addressed

No located public material addresses whether authority is checked for subsequent history.

The vendor site, product pages and third party coverage were searched on 29 Aug 2026. Nothing addresses whether returned authority 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.

Valid in that sense means the source exists and supports the point, which is not the same as the source still being good law. For a research product, this absence sits inside the product's design rather than outside it.

Source: Operator VerifiedAs of Aug 29, 2026

Refusal and Uncertainty Behavior

What does the product do when the answer is not in the corpus?

Not addressed

No located public material addresses what the product does when it cannot ground an answer.

Abstention behavior was observed and measured by an independent evaluator rather than documented by the vendor. The Vals legal research study recorded eight cases where Midpage said it could not locate the right documents and explained why the available sources did not support an answer, rather than inventing one. The evaluator gave partial credit for the quality of those explanations. It separately recorded three technical failures where no response came back at all, which is not principled abstention and is not counted as such.

The vendor itself publishes nothing on this: the vendor site and product pages were searched on 29 Aug 2026, and no described no answer path or confidence signal was located. The observed behavior is favorable, but nothing commits the vendor to keeping it.

Source: Third Party EstimatedAs of Aug 29, 2026Evidence

Fabricated Citation Record

Does a public court record exist addressing fabricated or hallucinated legal citations in output from this product?

None located

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

Source: Operator VerifiedAs of Aug 29, 2026Evidence
Professional Responsibility

Bar Guidance Alignment

Has the vendor engaged in public with the ethics opinions its buyers are bound by?

Not addressed

No located public material engages with bar or ethics guidance.

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.

Source: Operator VerifiedAs of Aug 29, 2026

Billing and Fee Posture

Does the vendor address what happens to the bill when the work takes an hour instead of six?

Not addressed

The product sits inside a lawyer to client fee relationship and no located public material addresses billing, fee or disclosure treatment, with no savings claim published either.

The vendor site, product pages and third party coverage were searched on 29 Aug 2026. No per matter record of AI assisted work for fee purposes was located, and no guidance on billing, fees or client disclosure. No time savings or efficiency claim was located either. The vendor's 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 bill.

Source: Operator VerifiedAs of Aug 29, 2026

Outside Counsel Guideline Readiness

Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?

On request only

The material exists behind a sales conversation or an executed agreement.

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. No subprocessor list is published and no model provider is named; only the terms binding them are.

Source: Vendor PublishedAs of Aug 29, 2026Evidence

Court Disclosure Support

If a judge’s standing order requires an AI disclosure, can the product produce one?

Not addressed

No located public material addresses court disclosure or verification certification.

The vendor site, product pages and third party coverage were searched on 29 Aug 2026. Output carries citations to primary law by design, so what was relied on is visible in the work product. No export for each document covering model used, sources retrieved and human verification together was located, and no model is named anywhere, so the model used could not be stated. Nothing beyond the citations in the output was located. This output is likely to reach a court, which makes the absence of a disclosure trail more consequential.

Source: Operator VerifiedAs of Aug 29, 2026
Contact

Correct a record, or ask how something was graded

Every grade and every signal on this index is drawn from public sources and dated. If a record is wrong, out of date, or missing an artifact the index did not locate, send the source and it will be reviewed and the record redated. Vendors are welcome to submit documentation. Nothing on this index is for sale, including a listing, a placement, or a grade.

AI Legal Index

The AI Legal Index is an independent index that tracks changes to AI vendors in legal. It holds 430 vendors across 9 categories, each graded on the same 15 capability axes and recorded against 12 legal signals, from public sources. No vendor pays for inclusion, placement, or rating.

Index Status
Last index update
October 14, 2026
The AI Legal Index is an editorial reference. It is not a regulatory body, not a law firm, and nothing published here is legal advice or a recommendation to retain or avoid a vendor. Records are verified against published sources, bar guidance and public court records. Where a record reads not addressed, the material was not located in public sources on the date shown. See the Methodology page for evaluation standards and limitations.
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