JusticeText vs Matey: how they compare in 2026
JusticeText and Matey both help criminal defense teams work through discovery that arrives as video, audio and documents. JusticeText transcribes body camera footage, interrogations and jail calls into transcripts synced to the recording and answers questions across the evidence. Matey's CrimD ingests a case's discovery, transcribes the media and answers questions with links back to the record. JusticeText's lead is what its terms say about its output: machine transcripts are review aids that must be checked and must not be relied on directly as evidence, and the transcript marks passages where confidence is low. It also names where data sits, on AWS servers in the United States, and imports from Clio, Dropbox and other stores. Its terms also let it tune its own models on customer content. The no training promise on its product page covers third party models only. Matey holds a 2025 ISO 27001 certificate and a 2026 SOC 2 Type 2 report, available through its trust center.
Which one fits
Choose JusticeText if
- Your discovery is mostly recordings in awkward formats. JusticeText converts GTL jail calls, WatchGuard video and other proprietary formats, syncs multiple camera angles by capture time, and produces searchable transcripts in more than 100 languages tied to the recording, with low confidence passages flagged for review.
- You need courtroom exhibits from the footage. JusticeText clips, redacts and captions exhibits from the original video rather than the transcript, which fits its terms: machine transcripts are review aids that must be checked and must not be relied on directly as evidence.
- You want evidence from offices like yours. JusticeText names the Kentucky Department of Public Advocacy and defender offices in Travis, Santa Cruz and Lane counties among others, and imports evidence from Google Drive, Dropbox, OneDrive, Box and Clio.
Choose Matey if
- Your county's security review needs certificates. Matey's trust center, run on Secureframe with continuous control monitoring, offers a 2025 ISO 27001 certificate and audit report and a 2026 SOC 2 Type 2 report on request, and lists controls across access, incident response and confidentiality.
- Your discovery mixes scanned files, email archives, texts and video. Matey's CrimD ingests all of it, transcribes the media, sorts documents into your own folders on arrival, and lets you ask questions in plain language, build timelines and draft motion and trial outlines linked back to the evidence.
- You defend individual clients or run a small firm. Matey says CrimD was built to be affordable for individual criminal defense lawyers, is an affinity partner of the National Association of Criminal Defense Lawyers, and names the Michigan defense firm Manley & Manley as a user.
At a glance
All 15 axes, side by side
The same grid applied to every vendor in the index, graded from public sources. Hover a grade to see what the letter means on that axis.
AI Centrality
How much of the product is actually AI. Whether the machine learning is the mechanism the buyer is paying for or a feature layered onto conventional software, and whether the vendor is specific about which is which.
The models are the engine of the core capability, on an evidence platform with substantial functions that do not use AI. Speech recognition produces the searchable transcripts, synced to the media, in more than 100 languages that the product leads with, and the MirandaAI assistant, summaries, key moments and PDF analysis are model work. Around them sits conventional evidence tooling that works without models: conversion of proprietary formats such as GTL jail calls and WatchGuard video, syncing of several camera angles by capture time, and clipping, redaction and captioning for courtroom exhibits.
CrimD's ingestion, automatic transcription of audio and video, classification of documents into folders on arrival, questions in plain language across the whole case, timeline building and document summaries are all model work. The company describes the platform as a knowledge graph explored by AI. Beside the models, the product includes a file viewer with video annotation.
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.
Output is grounded in the source media, and a failure condition is named with a visible behavior, short of any measurement. Transcripts are synced in time to the original audio and video, so any passage can be checked against the recording. The product FAQ names the conditions under which transcription degrades, overlapping voices, static and background noise, and says the transcript clearly identifies areas of lower confidence so reviewers focus there. No accuracy figure is published, nothing describes how MirandaAI answers are grounded or cited, and the terms disclaim any warranty of transcript accuracy.
Matey's home page says answers to questions are traceable to case evidence, and the product page says users can view and navigate directly to all supporting documents and citations. A post of 31 October 2025 says every answer includes clickable citations that link to the exact page or timestamp in the materials, and that a Citations tab shows every piece of material the AI relied on. The August 2025 funding announcement adds that the platform reads and reasons through actual case materials rather than producing case law, with audit trails. A July 2025 post says Matey answers only from the materials uploaded and claims "No Hallucinations". No accuracy figures, test set or error rate are published, and the product page's claim that its summaries are superior to general language models carries no evidence.
Autonomy and Oversight Model
What the system decides on its own, what a lawyer must approve, and whether the vendor documents where the review point sits. A tool that drafts under review and a tool that files without one are different products and different risks.
A named output carries a categorical limit on use, with a review surface built in. The Terms of Service state that machine generated transcriptions are tools to aid review, not authoritative records of events, and that every transcription must be checked by the user. Users agree not to rely directly on system transcriptions as evidence in a court, arbitration, mediation or other formal proceeding or settlement negotiation. The product supports that check by flagging passages with low confidence and syncing text to the original media, and exhibits are clipped from the original video rather than the transcript. The limit is specific to transcriptions: MirandaAI's timelines and inconsistency findings carry no equivalent stated limit.
The product page describes deploying large numbers of AI agents across millions of documents. The check it offers the lawyer is that answers and timelines link back to the supporting evidence, which a Citations tab lists. The funding announcement and a post of 16 October 2025 mention audit trails that record every step. Matey's blog says the answer should not replace the lawyer's review but point the lawyer to the material that needs review (May 2026), that lawyers still lead strategy (August 2025), and that whoever uses AI in legal work is responsible for verifying what it produces (October 2025). No override, no threshold at which the system defers to a person, and no limit on what its output may be relied on for is described.
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.
Named deployments with figures, short of any method. The vendor publishes case studies and rollout stories naming the Kentucky Department of Public Advocacy, the Santa Cruz County, Lane County, Travis County, Lehigh County and Siskiyou County defenders, Kansas Holistic Defenders, and private firms including Rossen Law and Nicholson Goetz & Otis. It quotes chief defenders in Harris County and Montana by name. Rossen Law says the product cut video review and trial preparation time by at least two thirds. No figure states how it was measured, over what caseload or period.
A release of 23 September 2025 names the Michigan criminal defense firm Manley & Manley, PLLC as a user. It quotes one of its trial attorneys on condensing 34,000 pages of discovery to 10 relevant pages and finding a body camera statement during cross examination. The True North pro bono program, announced on 18 November 2025, quotes Joe Trigilio of Loyola's Project for the Innocent and investigator Ryan Fleming of Variant Investigations and Consulting, without figures. The headline figures, 90 percent faster discovery review, more than $40,000 saved per case, 30 hours of discovery in 30 minutes and three times faster trial preparation, are attributed only to an unnamed public defender office or carry no customer, and no method is given. The site's other quotes are from an unnamed public defender and deputy director.
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.
Confidentiality is asserted in general terms, while the agreement permits model tuning from customer content. The product page says data remains confidential, the customer controls access and deletion, content is encrypted on U.S. servers, and evidence is never used to train third party machine learning models. The Terms of Service contain no confidentiality clause protecting customer content. The content license is limited to providing the service, but a separate Machine Learning clause authorizes calibrating data models and improving algorithms while processing user content. The privacy policy permits sharing deidentified aggregate data with research partners and funders. Nothing addresses privilege or defense work product, which is what public defenders' notes, tags and clips are.
The security page promises the highest security standards, encryption in transit and at rest, role based access, multifactor authentication and data anonymization and masking. Matey's FAQ says the company has special agreements with Microsoft and other entities to ensure confidentiality, without saying what they provide. Blog posts from July 2025 to April 2026 say Matey does not train its models on customer data and that role based access keeps sensitive cases compartmentalized. The website terms say the platform is governed by separate service agreements or customer contracts, and the website privacy policy points to a separate platform privacy policy and End User License Agreement. The agreement and platform privacy policy that govern the product are not published. Nothing public addresses which outside providers handle case material, or how privileged material and work product are treated.
UPL and Professional Responsibility Posture
Whether the vendor is clear that it supplies a tool rather than legal advice, who its audience is, and how it addresses unauthorized practice of law, competence and supervision duties, and jurisdiction limits. ABA Formal Opinion 512 is the reference point. Where the advice line is not the duty a product raises, the axis is read through the nearest professional duty it does raise: judicial conduct rules and the reviewing duty for products sold only to courts, and the duty to bill for time actually spent for products that draft time entries.
A clear position on what the output is and is not, with a defined audience, short of supervision duties. The terms state that transcriptions are review aids and not authoritative records, must be checked, and must not be relied on directly as evidence, and both the terms and privacy policy say JusticeText cannot answer requests for legal advice. The audience is attorneys, and the privacy policy collects each user's law licensing state. The terms disclaim any representation that the service is appropriate or lawful in a given location, including under court orders. Nothing addresses an attorney's competence or supervision duties when relying on MirandaAI analysis.
No published page states what the product is and is not, or that its answers and analysis are not legal advice. A Matey blog post of 3 November 2025 says the system is designed around the core ethical duties of competence, confidentiality, supervision and candor to the court, without saying how the product supports a defense lawyer's supervision and competence duties. The website terms limit use of the site to people at least 18 years old. The agreement that governs the product is not published.
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.
No governance position is published on the vendor's own site. The product's Built for responsible review section covers data security only, and no responsible AI policy, testing regime or accountable owner is published. A submission by the vendor hosted by MIT Solve acknowledges that speech recognition engines are less accurate on African American Vernacular English. That is a disclosure of uneven output, but it is not on the vendor's own site and is not dated.
No AI governance framework, owner, testing before release or bias disclosure is published. Matey's trust center lists security and operational controls, the funding announcement claims full explainability, and a post of 25 November 2025 says everything Matey does is auditable and explainable, not a black box. A post of 6 November 2025 says objectivity is built into every layer of the system. None of these describes how the models are governed. The product analyzes witness statements and body camera footage.
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 privacy policy states that information is stored encrypted on AWS servers in the United States and encrypted in transit, gives users a right to deletion completed in most cases within 30 days, and names categories of providers (hosting, transcoding, storage, databases, crash monitoring, payments) with AWS and Stripe named. The product page adds multi factor authentication and single sign on and says customers control access and deletion. Breach notification is promised only as required by law, the terms reserve retention and destruction under internal policies that are not published, and no full subprocessor list, including any AI or speech recognition provider, is given.
Matey's trust center shows that the company maintains a data retention and disposal policy and removes customer data on request in line with agreed customer requirements. It keeps production data out of development and testing unless debugging a customer issue requires it, has an incident response plan and vendor risk management, and has bought cybersecurity insurance. The security page adds encryption, role based access and data masking. The policies themselves, any retention period, any subprocessor list and any breach notification commitment are not published. The website privacy policy expressly excludes the platform and names only website tools such as Webflow, Google Analytics and HubSpot.
AI Liability and Recourse
What the vendor stands behind contractually when its output is wrong. Indemnities, caps, carve outs, insurance, and whether any of it is published or only reachable through a negotiated agreement.
Liability is addressed only through limitations that disclaim the exposure the product creates. The terms provide the system as is, disclaim any warranty of transcript accuracy, disclaim liability for any legal action or court decision resulting from transcripts or machine learning output, cap liability at the amount paid or $100, and require users to indemnify JusticeText. No vendor indemnity or insurance position is published.
The agreement that governs the product is not published, so nothing states who bears the loss when an answer or timeline is wrong. The website terms, effective 1 January 2025 and last updated 1 August 2025, cap liability at $100 and provide the site as is, but apply only to the website and say so.
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.
Named connections exist, short of documented depth. The product page shows imports from Google Drive, Dropbox, OneDrive, Box and the Clio practice management system, and the privacy policy describes the cloud storage integrations and Google API use. The platform also takes in the proprietary formats defense discovery arrives in, including GTL jail calls, For The Record courtroom recordings, AV Viewer and WatchGuard. What each connection moves, and whether results flow back to Clio or case management, is not documented.
Matey's FAQ says the platform integrates seamlessly with existing legal software and supports various legal tools and databases, but no integration is named or described in the FAQ or in the 2026 blog posts. Evidence arrives by upload.
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 hosting model and region are stated, with no options and no tenancy detail. The privacy policy states that information is stored in encrypted form on servers in the United States operated by Amazon Web Services, and the product page repeats that content is stored on encrypted U.S. servers. No tenancy model, deployment option or separate processing location for speech recognition or AI providers is stated.
No deployment option, hosting provider, region or residency is stated on the security page or in the FAQ. The FAQ's reference to special agreements with Microsoft does not say where case data is stored or processed.
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 located. The vendor describes encryption, multi factor authentication and single sign on but names no audit or standard, which matters for a product holding criminal discovery.
The trust center, run on Secureframe with continuous control monitoring, offers a 2025 ISO 27001 certificate, the 2025 initial certification audit report and a 2026 SOC 2 Type 2 audit report on request. It lists controls across change management, availability, confidentiality, incident response, network and access security. The security page and about page label their badge SOC 2 Non-CPA. The auditor and the scope of the certification and of the audit are not stated, and the reports are available only on request.
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 product page says evidence is never used to train third party machine learning models, and the terms say third party tools execute some functionality and may access user content. No speech recognition engine, language model or provider is named on the product page or in the terms, and no change notification is described.
The product page refers to the industry's most capable AI and a densely connected knowledge graph, and Matey's FAQ mentions special agreements with Microsoft and other entities. A July 2025 post says Matey did not put an interface on OpenAI's API and call it a legal assistant, and that it fine tunes its pipeline for legal nuance, evidence structure and discovery formats. No model, provider, hosting location or change notice is named.
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.
The pricing structure is described without figures. The Terms of Service describe monthly and annual subscriptions that renew automatically, usage limits on processing time that can block further processing until the next term, free initial access for a period or amount of usage, and no refunds. No price, rate or plan is published; access starts through an interest form.
No price, tier or unit of charge is published. Matey's FAQ says CrimD was built to be affordable for individual criminal defense lawyers, and a post of 30 July 2025 says Matey charges no fees per gigabyte, offers unlimited hosting, and includes processing and AI features at no extra cost. Every route to a figure is a demo or sales request.
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.
The vendor serves public defender offices and private criminal defense attorneys, and covers body camera footage, interrogations, jail calls, dashcam, courtroom recordings and written discovery, with transcription and translation in more than 100 languages and support for named proprietary formats. It does not state which jurisdictions it serves, which evidence types it handles poorly beyond noisy audio, or whether it suits civil or prosecution use.
The core buyer is criminal defense, from individual defense lawyers and firms to public defender offices, with government agencies also named as users. Matey's site shows an affinity partnership with the National Association of Criminal Defense Lawyers, and the True North program offers pro bono access to innocence organizations, advocacy teams and capital defenders. Posts from April and May 2026 market the platform to civil litigators for deposition preparation, motion drafting and mediation. The FAQ widens it to civil litigation, corporate law and forensic investigations, and the about page adds corporate legal departments and litigation funders, without saying how the product differs for them. No limits on case size, evidence type or jurisdiction are stated.
The 12 legal signals, side by side
Recorded rather than graded. These are the questions a practitioner has to answer before a tool touches a client matter, and the answers are taken from public material only.
Client Data in Training
Can material a lawyer puts into this product be used to train a model?
The published Terms of Service reserve a right to tune the vendor's own models using customer content, with no opt out located. The Machine Learning clause authorizes JusticeText to use machine learning to generate statistics, calibrate data models and improve algorithms in the course of processing uploaded content and usage data, and to test, tune, optimize, validate or otherwise enhance the models underlying the system.
The product page states that evidence is never used to train third party machine learning models; that statement is limited to third parties and does not address the vendor's own models.
Matey's blog says Matey does not train models on customer data (23 April 2026), that customer data is not used to train Matey's models (25 November 2025), and that customer files are not used to train anything, ever (11 July 2025). The agreement and privacy policy that govern the platform are not published. The website terms and website privacy policy both say the platform is covered by separate customer agreements and an End User License Agreement, and neither appears on the site, so the statement is not matched by a contractual term.
Prompt and Output Retention
How long does the product keep what a lawyer typed, and can that be set to zero?
The customer controls deletion of uploaded evidence. The product page says customers control access and deletion, and the privacy policy gives a right to deletion completed in most cases within 30 days, subject to legal retention and to deidentified usage data the vendor may keep. The terms also reserve retention and destruction under internal policies that are not published.
Matey's trust center says that on customer request, data no longer needed is removed in line with requirements agreed with the customer, and that a data retention and disposal policy governs how customer data is kept and disposed of. The policy itself and any retention period are not published, and no option for zero retention is described.
Ethical Walls and Matter Segregation
Does retrieval respect the firm’s ethical walls, or can the model read across them?
Sharing is controlled by the user, with no published detail on how separation is enforced. The privacy policy says data and work product are shared with other users only on request or according to account preferences, such as with another member of the same office. Nothing documents how cases, attorneys or codefendant matters are walled off within an office.
The security page lists role based access control that restricts sensitive data to authorized personnel, and Matey's trust center lists access controls. A post of 25 November 2025 says role based access keeps sensitive cases compartmentalized, and an April 2026 post says customers control access and sharing. Nothing published describes how access is scoped between cases, matters or teams within a customer, or how it is enforced.
Third Party Request and Subpoena Notice
If someone subpoenas the vendor for a firm’s data, does the firm hear about it first?
Disclosure under legal compulsion is limited to what the law requires, and customer notice is not addressed. The privacy policy permits disclosure for compliance with law enforcement and court orders only to the extent required, and the terms allow disclosure to law enforcement on breach. Neither commits to telling the customer before or after disclosure, which matters for a product holding defense discovery and work product.
The website privacy policy reserves sharing personal information with legal or regulatory authorities when required by law, but it expressly excludes the platform. Nothing in the website terms, the website privacy policy, the security page or the trust center addresses legal requests for case data held in the product.
Primary Law Corpus Provenance
Where does the law in this product come from, and does the vendor have the right to use it?
Licensing of legal content is a marginal question for a tool built on each customer's discovery. The AI works over the customer's own discovery rather than a legal research corpus, and no external legal source is described.
The product works on the discovery each customer uploads, and no body of primary law behind its output is identified on the home page, the product page or the FAQ.
Good Law Verification
Does the product tell you when the authority it just cited has been overruled?
Good law status has nothing to attach to here. The product does not cite legal authority, so no check of subsequent history arises and none is described.
The product analyzes case evidence rather than citing legal authority. Nothing on the home page, the product page or the FAQ addresses checking authority for subsequent history.
Refusal and Uncertainty Behavior
What does the product do when the answer is not in the corpus?
The transcript marks passages with low confidence, with no documented abstention path. The product FAQ says that for poor audio, overlapping voices and background noise the AI transcript clearly identifies areas of lower confidence so reviewers can focus there. Nothing describes what MirandaAI does when the evidence does not answer a question.
Answers link to supporting evidence, and a post of 31 October 2025 describes the system as closed loop, using only the data the customer provides. No confidence indicator, and no path in which the system declines to answer a question the evidence does not support, is described on the home page, the product page or the FAQ.
Fabricated Citation Record
Does a public court record exist addressing fabricated or hallucinated legal citations in output from this product?
The AI Hallucination Cases database kept by Damien Charlotin holds no entry naming JusticeText as the tool used. JusticeText transcribes and summarizes evidence recordings for criminal defense teams.
The AI Hallucination Cases database maintained by Damien Charlotin records no case involving Matey or CrimD. No court order, opinion or disciplinary record naming the product is on the public record.
Bar Guidance Alignment
Has the vendor engaged in public with the ethics opinions its buyers are bound by?
Lawyers using the product get no pointer to the ethics rules that govern that use. No bar ethics opinion or court rule on AI is named or engaged in connection with the product.
A Matey blog post of 3 November 2025 says the system is designed around the core ethical duties of competence, confidentiality, supervision and candor to the court, and a post of 16 October 2025 says whoever uses AI in legal work is responsible for verifying what it produces. No ethics opinion is named. The affinity partnership with the National Association of Criminal Defense Lawyers is a commercial relationship, not guidance.
Billing and Fee Posture
Does the vendor address what happens to the bill when the work takes an hour instead of six?
The product is bought mainly by public defender offices, where no client is billed for the work. Time savings are claimed as capacity for the office's own caseload. Private criminal defense firms also use it, where a fee relationship would arise, and nothing addresses billing or disclosure for that use.
The company claims 90 percent time savings on discovery review and more than $40,000 saved per case, and the home page quotes a deputy director on $30,000 of case setup labor replaced. Nothing addresses how work done with AI is billed or disclosed by the private defense firms that use it. Public defender offices bill no client.
Outside Counsel Guideline Readiness
Can a firm get this vendor through a client’s AI clause without a bespoke negotiation?
Infrastructure providers are named, and the AI providers a client would ask about are not. The privacy policy names AWS and Stripe and lists other provider categories, but no speech recognition or AI provider is named and no data processing agreement is published.
No subprocessor or model provider list is published on the home page, the security page, the FAQ or the trust center. The FAQ refers only to special agreements with Microsoft and other entities.
Court Disclosure Support
If a judge’s standing order requires an AI disclosure, can the product produce one?
Transcripts are synced in time to the original media with passages of low confidence marked, and courtroom exhibits are clipped from the original video with captions. The terms bar relying on the transcript itself as evidence. Nothing records which model produced a transcript, summary or MirandaAI answer, or who verified it.
Answers and timelines link back to the supporting evidence, and the company says the platform keeps audit trails, with structured logs, timestamps, user actions and document histories (25 November 2025). No export of a record showing the model used, the sources and the human check is described, and no disclosure guidance or template is published.
The questions both sides leave open
Derived from the records above rather than written, so it cannot favor either vendor. Take these into both conversations and ask each side the same question.
- AI Governance and Bias Disclosure
- Primary Law Corpus Provenance
- Good Law Verification
- Outside Counsel Guideline Readiness
In summary
JusticeText
JusticeText, from JusticeText Inc. of Irvine, California, is an evidence review platform built mainly for public defender offices. It transcribes body camera footage, interrogations, jail calls, dashcam and courtroom recordings into searchable transcripts synced to the media in more than 100 languages. Its assistant, MirandaAI, answers questions across a case's evidence to build timelines and spot inconsistencies. According to the AI Legal Index, JusticeText's terms bar relying on machine transcripts directly as evidence, and its transcripts flag low confidence passages for review. It names the Kentucky Department of Public Advocacy among its users. Access starts through an interest form.
Matey
Matey, from MateyAI, Inc. of Austin, Texas, sells CrimD, an AI discovery analysis platform for criminal defense. CrimD ingests scanned documents, email archives, text messages and body camera video, transcribes media and sorts documents into folders. It answers plain language questions with links back to the evidence, including timelines and motion outlines. Matey sells to public defenders, private defense firms and government agencies, and is an affinity partner of the National Association of Criminal Defense Lawyers. According to the AI Legal Index, Matey offers ISO 27001 and SOC 2 Type 2 reports on request. It is sold through a demo or sales request.
Questions buyers ask
JusticeText vs Matey: which is better for criminal defense discovery?
Both transcribe discovery media and answer questions across a case's evidence. JusticeText's terms set how transcripts may be used, and it names where data is stored and which systems it imports from. Matey holds independent security attestations and handles large mixed document sets with plain language questions. Offices whose procurement starts with security certification can start with Matey's trust center. From the AI Legal Index, based on each vendor's own published materials as of September 25, 2026. No vendor pays for placement.
Can JusticeText transcripts be used as evidence?
Not directly, under JusticeText's own terms. They state that machine generated transcripts are tools to aid review, not authoritative records, that every transcription must be checked by the user, and that users agree not to rely on them directly as evidence in court, arbitration, mediation or settlement negotiation. Transcripts are synced to the original media and flag low confidence passages, and exhibits are clipped from the original video. From the AI Legal Index, based on each vendor's own published materials as of September 25, 2026. No vendor pays for placement.
Does JusticeText train AI on defense evidence?
JusticeText's product page says evidence is never used to train third party machine learning models. Its terms separately authorize it to calibrate data models, improve algorithms and tune the models underlying its system in the course of processing customer content, so its own models may learn from uploads. From the AI Legal Index, based on each vendor's own published materials as of September 25, 2026. No vendor pays for placement.
What security certifications do JusticeText and Matey hold?
Matey's trust center, run on Secureframe, offers a 2025 ISO 27001 certificate, the initial certification audit report and a 2026 SOC 2 Type 2 audit report on request. JusticeText describes encryption, AWS hosting in the United States, multi factor authentication and single sign on. From the AI Legal Index, based on each vendor's own published materials as of September 25, 2026. No vendor pays for placement.
Neither vendor paid for inclusion, placement or a grade, and neither reviewed this page before it published. Everything on it comes from public material on the dates shown. How the index grades.
Two points to weigh. JusticeText's terms let it use customer content to calibrate and tune its own models. Its product page promise that evidence never trains third party models does not reach its own models, and that limit sits in its published terms. Matey's website terms and privacy policy say the platform is governed by customer agreements and an end user license that are not published. So the gaps on Matey's liability, training and professional responsibility positions describe what is published, not what a signed contract says. Neither vendor reviewed this page.