Darrow vs Pattern Data: how they compare in 2026

D
Darrow profile
P
Pattern Data profile
Last verifiedSeptember 27, 2026
Verdict

Darrow and Pattern Data both sell AI to mass tort and class action practices, and are rarely weighed together because they work at opposite ends of a case. Darrow finds where litigation is forming, from regulatory filings, incident reports and market signals. Pattern Data evaluates claimants once a mass tort exists and carries them to settlement. Darrow is stronger on evidence and naming. It shows about thirty customer firms by name, including Milberg and Baron and Budd, and its terms name Anthropic and OpenAI as its AI providers. The same terms grant it a perpetual license over customer data, including to train foundation models. Pattern Data is stronger on oversight and fit: eligible claims are decided automatically, outliers go to a person, and it integrates with Litify.

Which one fits

Choose Darrow if

  • Your problem is finding the next case before others do. Darrow ingests regulatory filings, incident reports, litigation patterns and market activity, more than 5 million signals a month by its figures, and surfaces where legal exposure is forming across more than 50 categories.
  • You insure or defend against that exposure. Darrow sells separate routes to insurers pricing litigation risk and to corporate compliance teams monitoring their own external footprint, alongside plaintiff and class action firms.
  • You want to know which AI companies are involved. Darrow's terms name Anthropic and OpenAI as its AI service providers, and give an indemnity against third party claims that use of the service infringes a US patent.

Choose Pattern Data if

  • Your problem is a docket of claimants already signed. Pattern Data screens each for exposure and injury, reconciles full records to model valuation, and calculates settlement points against the agreement's criteria, recalculating when criteria change.
  • You need automated decisions with a human backstop. Pattern Data states that eligible claims are auto adjudicated and complex or outlier cases are flagged for review, and it has been court appointed to run eligibility in settlement programs.
  • You want the unit of charge before a call. Pattern Data prices transactionally by case volume and service, naming case analysis, settlement allocation and packet generation, and integrates with Litify and an open API.

At a glance

Category
DarrowPlaintiff & Claims AI
Pattern DataPlaintiff & Claims AI
Founded
DarrowNot published
Pattern DataNot published
Headquarters
DarrowNew York, New York, United States
Pattern DataCharlotte, North Carolina, United States
Last verified
DarrowSep 4, 2026
Pattern DataSep 6, 2026

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.

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

Section 8.3 states that the AI features are mandatory and integrated by default, and that a customer who does not accept the AI service providers' terms has no remedy other than to stop using the service. The published architecture is four layers of model work: ingesting raw signals at scale, interpreting them through legal context, reasoning across the result to prioritize and orchestrate action autonomously, and surfacing it to the teams responsible. Published throughput is more than 5 million signals detected monthly. Without the models there is no product.

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

The product reads records, extracts exposure, injury and treatment data, scores every claimant against litigation criteria and decides eligible claims automatically. Pattern Data has sold nothing else since its founding, and it names the models it tailors to each litigation as the product.

Citation Accuracy and Hallucination Disclosure

Whether the vendor publishes measured accuracy on citations and assertions, grounds output to primary sources, and says plainly what its system does when it does not know. Legal has a documented public record of fabricated citations reaching filed briefs, so an untested claim of accuracy is not evidence.

Darrow
CC on Citation Accuracy and Hallucination DisclosureAccuracy is asserted without measurement, or grounding is claimed while output cites sources the reader cannot open and verify.

The knowledge base is described in principle as connecting the laws that create obligations, the organizational weaknesses that emerge when they are not met, and the enforcement actions that follow. The inputs are described by category as regulatory filings, incident reports, litigation patterns and market activity. Nothing describes how an output traces back to the input that produced it: no citation, source link or retrieval method. Hallucination is addressed only as a disclaimer. Section 8.3 records that generative AI involves uncertainties as to quality and accuracy and that the company has no control over output. The trial terms disclaim liability for undetected, misdetected or mischaracterized events, signals, risks or cases. No accuracy figure or test set is published, and section 12.1 expressly disclaims any warranty of accuracy. Darrow also publishes Research and Domain Coverage pages.

Pattern Data
BB on Citation Accuracy and Hallucination DisclosureGrounding is real and documented, with linked primary sources and a described retrieval method, short of published accuracy figures an outsider can test.

Retrieval augmented generation over language models underpins the platform, Pattern Data's FAQ states, with case reviewers validating the findings the AI aggregates. The platform page states clear sourcing and human validation at every step and that every result can stand up to review, audit or settlement. A third party review gives a figure of 98 percent accuracy, which is not the vendor's own. No figure, test set or evaluation from the vendor is published. The product reads records and cites no primary law.

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.

Darrow
CC on Autonomy and Oversight ModelAutonomy is claimed and oversight is asserted without a mechanism. Human in the loop appears as a phrase rather than a described control.

The published description of the agentic layer says advanced AI systems reason across the intelligence, identify emerging opportunities, prioritize signals and orchestrate action autonomously. The product is framed as an always on legal red team. The only oversight statements are contractual disclaimers. Section 8.3 makes the customer responsible for evaluating the results of its use of the AI features and says the service is not a substitute for legal advice, legal research and independent review. Nothing published separates what the system does unattended from what a person approves. No threshold is stated at which it escalates or stops, no review surface inside the portal is described, and nothing addresses what happens when a signal is wrong. Darrow also publishes platform, law firms and FAQ pages.

Pattern Data
AA on Autonomy and Oversight ModelWhat the system runs alone, what constrains it, and how a lawyer checks it are all published: modes, thresholds, review surfaces, and the route a matter takes back to human judgment. A categorical limit on a named mode or tier, stating what its output may not be used for, meets the threshold limb without a number.

Eligible claims are decided automatically by the proprietary AI while complex or outlier cases are flagged for human review, the FAQ states, and case reviewers validate the findings the AI aggregates. On its home page, Pattern Data states that every extraction, classification and score is built to support the team's review rather than bypass it. The threshold is the eligibility and allocation logic set by the settlement criteria, recalculated when criteria change. The review surface shows validated data, record status and what each case needs next, with sourcing on every result. Flagged outliers go to a person. Nothing states a confidence level below which automatic decisions are withheld, beyond the criteria themselves.

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.

Darrow
BB on Operational and Outcome EvidenceReal deployment evidence with substance, short of full attribution or measurement: a named customer without figures, or figures without the named customer.

Roughly thirty customer organizations are shown by name: Baron and Budd, Milberg, Girard Sharp, Bernstein Litowitz Berger and Grossmann, Zuckerman Spaeder, Singleton Schreiber, Kahn Swick and Foti, Lynch Carpenter, Bailey and Glasser, Nichols Kaster, Loevy and Loevy, Wolf Haldenstein, Stephan Zouras, Schneider Wallace, Freed Kanner, Kozyak Tropin and Throckmorton and Consovoy McCarthy, alongside Microsoft and Armis on the corporate side. Figures are published at corporate level: more than 22 billion dollars in legal exposure surfaced, over 80 organizations, more than 5 million signals detected monthly, over 22,000 legal professionals and more than 10,000 active matters. No figure is attached to any named firm, no case study is published, nothing is dated, and no testimonial from a named individual appears on the home or segment pages.

Pattern Data
CC on Operational and Outcome EvidenceCustomer logos and unattributed testimonials stand in for evidence, or results are quoted with no basis stated.

More than thirty litigations and 1.4 million cases sit on the platform, Pattern Data's FAQ states, alongside roles appointed by courts in major settlement programs, settlement submissions in one day rather than fifteen and review costs cut by up to five times. None is attributed to a named firm or program, and the testimonials on the home page are unnamed. The chief executive's conference biography names the 3M Combat Arms Earplug and Philips CPAP litigations as deployments, without figures.

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.

Darrow
DD on Privilege and Confidentiality PostureNothing published on how client confidences are handled by a product built to ingest them.

The confidentiality regime at section 11 defines Confidential Information as business, product, technology and marketing information that is not public, and does not bring Customer Data within that definition, so the mutual confidentiality obligations do not by their terms reach what a customer puts into the service. Section 5.1 grants the company and its subprocessors an irrevocable, perpetual, sublicensable license over Customer Data that expressly extends to training foundation models. Section 11.3 reserves a broad right to access, read, preserve and disclose any information obtained in connection with the service. Nothing addresses privilege or work product, nothing addresses segregation between customers or matters, and no retention period exists. Section 7.3 commits to reasonable industry standard technical and organizational security measures to protect Customer Data, which is a security promise rather than a confidentiality one. Section 5.2 separately prohibits the customer from submitting protected health information.

Pattern Data
CC on Privilege and Confidentiality PostureConfidentiality is asserted in general terms, or the commitment lives only in a sales conversation and cannot be read in advance.

Confidentiality measures in Pattern Data's FAQ are TLS encryption, environments that comply with HIPAA for protected health data, multifactor authentication, stringent access controls and staff training. No customer agreement is published, so nothing binds a training position. No statement is published on training use, retention, deletion, segregation by matter or docket, third party model providers, or privilege and work product.

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.

Darrow
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.

Section 8.3 states that the customer acknowledges the service is not a substitute for legal advice, legal research and independent review, and the trial terms go further, adding that it is not a substitute for audit, assessment or any medical, legal or regulatory conclusion and that the customer is solely responsible for obtaining necessary legal, medical, scientific or regulatory advice and for its own due diligence. Both sit inside the AI features and warranty clauses rather than in a dedicated position. Nothing on the home page or the segment pages addresses the question at all. No competence or supervision language appears, no rule of professional conduct is named, and jurisdiction is handled by disclaimer rather than by limit, with section 12.1 disclaiming any guarantee that output is suitable for the customer's jurisdiction. The product recommends which matters a firm should pursue.

Pattern Data
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.

No advice line or supervision statement is published. The product is sold to law firms and to administrators appointed by courts. Pattern Data's home page states the AI amplifies rather than replaces human judgment. No page states that outputs are not legal advice or how the product supports a supervising lawyer's duties, and no customer agreement is published to carry such a statement.

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.

Darrow
DD on AI Governance and Bias DisclosureNo governance position published for a system whose output affects legal outcomes.

The system decides which potential claims a firm sees. There is no responsible AI statement, governance framework, named owner accountable for model behavior, description of evaluation before release, or published testing result. Nothing addresses bias, though the system prioritizes signals and so determines which exposures surface and which do not. The company describes itself as an AI lab and publishes a Research page. The agreement records at section 8.3 that the company has no control over the output of the AI features.

Pattern Data
CC on AI Governance and Bias DisclosureResponsible AI principles are published without a mechanism, a testing regime, or anything a buyer could audit.

The AI does not replace human judgment and every output supports review, Pattern Data's home page states, and the FAQ describes validation by people in the loop. No responsible AI framework, ISO 42001 or equivalent, accountable owner, results of testing before release, or statement about uneven output across litigations or record types is published.

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.

Darrow
CC on AI Safety and Data StewardshipA generic privacy policy covers the product without addressing what happens to documents and prompts after processing.

Section 7.3 commits to reasonable, industry standard technical and organizational security measures during the subscription term, with no control named: no encryption standard, access model, logging or testing cadence. There is no security page anywhere in the site navigation or footer. Retention is not addressed. Section 10.4 says only that after termination the company may delete Customer Data, which is permissive and sits against the perpetual license granted at section 5.1. Section 8.1 acknowledges that subprocessors exist and names none. No incident or breach notification practice is published. The privacy policy is incorporated by reference at section 7.1. Section 7.1 is headed Privacy Policy and DPA, but no data processing agreement is linked or published.

Pattern Data
CC on AI Safety and Data StewardshipA generic privacy policy covers the product without addressing what happens to documents and prompts after processing.

TLS in transit, storage that complies with HIPAA for protected health data, multifactor authentication, stringent access controls and continuous staff training make up the safeguards in Pattern Data's FAQ, with adherence to SOC 2 and regular audits. No retention period, deletion commitment, subprocessor list or practice for notifying incidents is published. No customer agreement is published.

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.

Darrow
BB on AI Liability and RecourseA real published position on liability, short of the full picture: commonly a stated indemnity without scope or caps.

Section 14.1 gives a narrow company indemnity covering third party claims that the right to use the service infringes a valid United States patent, with five named exclusions and remedies at section 6.4. The agreement states that these are the sole and exclusive remedy for intellectual property infringement. Section 13 caps aggregate liability at fees paid in the preceding twelve months, dropping to 50 US dollars for trial and prerelease services under section 2.3 and for the drug and device intelligence trial. No warranty is given. Section 12.1 disclaims accuracy, completeness, availability and security outright. Section 8.3 states the company is not liable for the performance of the AI features and does not guarantee the accuracy or reliability of any output. The trial terms disclaim liability for undetected or mischaracterized signals, risks or cases. No insurance position is published.

Pattern Data
DD on AI Liability and RecourseNothing published on who bears the loss when the system is wrong.

No liability position is published. The site's navigation and footer carry Privacy, Security, Careers and an AI search page, and no terms of service or customer agreement. The FAQ describes pricing as tailored per firm, so the agreement is a negotiated document that is not published.

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.

Darrow
DD on Practice Systems Integration DepthNo integration into practice systems located, or the product stands alone and requires work to move to it.

Section 8.4 of the agreement refers to integration with certain third party applications set out in the company's documentation or within the service, then disclaims responsibility for them without naming any. No case management system, document management system, intake platform or CRM appears on the home page, the terms or the navigation, and there is no integrations page or developer documentation in the navigation or footer. Plaintiff firms, the segment named first on the site, get case signals with no stated route into an intake or matter system. Darrow also publishes Platform and Law Firms pages.

Pattern Data
BB on Practice Systems Integration DepthReal integrations exist and are documented, short of depth: named connections without a description of what they actually move.

The navigation carries an Integrations page and a dedicated Litify page. Pattern Data's FAQ states an open API with customizable scripts for automated actions, bulk imports from cloud storage systems and drag and drop upload, and describes integration with existing case management systems. The platform page states that settlement packets are generated in the formats claims administrators require. What syncs with Litify, and in which direction, is not described in the FAQ or on the platform page.

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.

Darrow
DD on Deployment Model and Data ResidencyNothing published on where the software runs or where client data sits.

No region, country, hosting provider or data center is named on any surface, and no tenancy model is described: nothing states whether the platform is single or multi tenant or how one customer's data is separated from another's. The agreement says only, at section 8.1, that the service is hosted and made available by certain subprocessors, none of them named. No deployment option, private tier or residency commitment of any kind is offered. The one geographic signal is indirect, in the export control clause at section 15.1 referring to Israeli, United States or foreign export controls.

Pattern Data
CC on Deployment Model and Data ResidencyCloud delivery is implied and neither the tenancy model nor the region is stated.

The platform is delivered as a cloud service. Pattern Data's FAQ states that protected health data is stored in secure environments that comply with HIPAA and that bulk import from cloud storage is supported. No hosting provider, region, residency option or tenancy model is named.

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.

Darrow
DD on Security Certifications and Trust CenterNo independent security attestation located.

No SOC 2, ISO 27001, HIPAA or any other framework is claimed anywhere, no auditor or certifying body is named, no report is offered at any access tier, and no penetration testing is mentioned. There is no security page and no trust center: the site navigation carries Law Firms, Insurance, Compliance, Research and a Company menu, and the footer carries only a cookie policy, a privacy policy and the terms of use. The agreement offers section 7.3 alone, promising reasonable industry standard measures without naming a standard. No unsupported badges are displayed.

Pattern Data
CC on Security Certifications and Trust CenterBadges appear on the site with no scope, no date, and no report available.

Pattern Data's FAQ states adherence to SOC 2 compliance, regular comprehensive security audits and full HIPAA compliance. It does not state that a SOC 2 report has been issued. No report type, auditor, coverage period or route to a report is stated. The footer links a Security page.

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.

Darrow
BB on Model Supply Chain DisclosureThe supply chain is partly disclosed: providers named without change notification, or architecture described without the providers.

Section 8.3 identifies the AI service providers as third parties including Anthropic Claude and OpenAI, both misspelled in the published text, and makes clear that the AI features are mandatory and integrated by default. The disclosure sits in the agreement rather than in marketing. The same clause reserves the right to use different AI service providers at any time without prior notice, and a customer who objects to a current or future provider has no remedy but to stop using the service. The word including leaves the list open. No specific model or version is named, no location is given for inference, and no subprocessor list is published; section 8.1 acknowledges subprocessors without identifying any.

Pattern Data
CC on Model Supply Chain DisclosureThe vendor refers to advanced or proprietary models without identifying what sits underneath.

Pattern Data's FAQ states a retrieval augmented generation approach and large language models, and the litigation pages describe models tailored to specific litigations. No provider, model, inference location or commitment to notify customers of changes 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.

Darrow
DD on Commercial TransparencyNo pricing information published at any level, including the unit of charge.

There is no pricing page, no tier names, no feature split, no indication of whether charging is per user, matter, signal or case, and no free trial or self-serve route. Every call to action leads to a demo request or a booking with the team. The agreement shows the shape of the arrangement rather than its price. Fees are set in an Order Form in US dollars and paid annually in advance. They cannot be canceled or refunded, renew automatically unless canceled 30 days before expiry, and carry overage fees for excessive use. A banner states that 78 percent of production is already reserved.

Pattern Data
BB on Commercial TransparencyReal pricing is published for part of the range, with enterprise tiers withheld, or the unit and structure are stated without the figure.

Pattern Data's FAQ describes a transactional pricing model, with fees based on case volume and the specific services used. It names case analysis, settlement award allocation and settlement packet generation as priced services, tailored per firm to caseload and budget, and claims review fees cut by up to five times against manual review. No figure, rate card or pricing page is published.

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.

Darrow
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.

Each segment has its own page and stated job: law firms identifying emerging litigation earlier and building case portfolios, insurers detecting exposure and pricing risk, and corporate compliance teams surfacing exposure across their external digital footprint. Practice breadth is put at more than 50 legal exposure categories, and the footer links a Domain Coverage page. The named customers, overwhelmingly plaintiff and class action firms, corroborate the primary segment. No individual practice area is named on the home or segment pages, firm size is not addressed, no jurisdiction of coverage is stated, and nothing says which exposure types or industries fall outside the system.

Pattern Data
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.

Buyers are plaintiff firms, defense firms, settlement administrators and special masters. The litigation pages name Roundup, AFFF and PFAS, Camp Lejeune, Depo-Provera, hair relaxer, GLP-1, Paraquat, social media, talc and Zantac, with more than thirty litigations supported. Pattern Data states the platform is built for mass tort and multidistrict litigation. No jurisdiction outside the United States is addressed.

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?

Darrow
Permitted, in the contract

Section 5.1 has the customer grant the company and its subprocessors an irrevocable, perpetual, nonexclusive, worldwide, royalty free, fully paid and sublicensable license over Customer Data. It covers accessing, using, processing, copying, downloading, storing, distributing, creating derivative works from and displaying that data to maintain and develop the service, with training foundation models named inside that purpose.

The license is irrevocable and perpetual on its own words, so it does not end when the subscription does. Section 6.1 vests in the company any improvements and developments created by processing Customer Data. No way to opt out, no requirement to remove identifying details and no exception for sensitive matters appears anywhere. The identical clause appears in all three agreements published on the terms page.

Pattern Data
No agreement published

No customer agreement is published, and no training statement is published. The site's navigation and footer carry Privacy, Security, Careers and an AI search page and no terms of service. The FAQ addresses encryption, HIPAA environments, access control and audits without stating whether customer records train any model. The litigation pages describe models tailored to each litigation without saying what they are trained on.

Prompt and Output Retention

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

Darrow
Disclosed without a period

Section 10.4 places the export obligation on the customer before termination and then provides that following termination the company may delete Customer Data without retaining any copy, which is permissive rather than a commitment and gives no window. No retention period applies during the subscription term, no deletion request route is described, and no certification of deletion is offered in the home page, the terms of use or the footer.

The position sits against section 5.1, which grants an irrevocable and perpetual license over the same Customer Data, so a deletion that is optional after termination coexists with a license that by its terms does not expire. Darrow also publishes a privacy policy.

Pattern Data
Not addressed

Nothing published addresses how long records, extractions or settlement data are kept. The FAQ addresses storage security without a period, and no customer agreement is published.

Ethical Walls and Matter Segregation

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

Darrow
Not addressed

Nothing on the home page, the terms of use, the site navigation or the footer states whether the platform is single or multi tenant, how one customer's data is separated from another's, or how access is controlled within a customer account, and no role or permission model is described. The agreement's only adjacent provisions are account security obligations placed on the customer at section 03 and a general security promise at section 7.3.

The named customers are plaintiff and class action firms that compete for the same matters, and the product allocates case signals among them.

Pattern Data
Claimed, not documented

Pattern Data's FAQ states multifactor authentication and stringent access controls, and the platform holds each firm's docket as one live inventory. Nothing describes how one firm's docket is walled off from another's, how an administrator's view is separated from the firms whose claimants it adjudicates, or how the models respect those boundaries.

Third Party Request and Subpoena Notice

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

Darrow
Disclosure addressed, notice absent

Section 11.3 lets the company access, read, preserve and disclose any information it obtains through the service as it reasonably believes necessary to satisfy any law, regulation, legal process, subpoena or governmental request. No notice obligation is attached. Section 11.2(iv) does commit to best efforts to give prompt notice of compelled disclosure, but only for Confidential Information. Section 11.1 defines that as business, product, technology and marketing information that is not public, and by its terms it does not include Customer Data. The clause that reaches what a customer puts into the service carries no notice. No transparency report is published.

Pattern Data
Not addressed

Nothing published addresses whether the customer is told when a third party demands its data. No customer agreement is published.

Primary Law Corpus Provenance

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

Darrow
Not addressed

The published material says signals are ingested from regulatory filings, incident reports, litigation patterns and market activity. It says a structured knowledge base connects the laws creating obligations, the organizational weaknesses that emerge, and the enforcement actions that follow. No database, publisher, register or docket source is named, no jurisdiction of coverage is stated, and the rights basis on which any of it is held is not addressed.

Section 8.3 refers to reliance on various third party data sources without identifying them. Darrow also publishes a Research page and a Domain Coverage page.

Pattern Data
Not addressed

The product is not built on a body of legal content, and none is identified behind its output. It extracts facts from the records of the customer's claimants and scores them against litigation and settlement criteria the firm or administrator supplies, citing no law.

Good Law Verification

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

Darrow
Not addressed

The product does not retrieve or present primary law as its output: it surfaces signals of emerging legal exposure drawn from filings, incident data and litigation patterns. Nothing on the home page, the terms of use or the site navigation addresses whether authority is checked for subsequent history.

Pattern Data
Not addressed

Nothing published addresses whether authority is checked for subsequent history. The product does not retrieve or cite primary law. Its output is case scores, valuations and settlement packets, and it has no citator function.

Refusal and Uncertainty Behavior

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

Darrow
Not addressed

The agreement acknowledges uncertainty extensively but only as allocation of risk: section 8.3 records that generative AI involves uncertainties as to content quality and accuracy and that the company has no control over the output, and the trial terms disclaim liability for undetected, misdetected or mischaracterized events, signals, risks or cases. The home page and the terms describe no abstention path, no way of returning no answer, and no confidence or grounding score surfaced to the user, on a product whose stated function is prioritizing signals.

Pattern Data
Documented

Pattern Data's FAQ states that eligible claims are decided automatically while complex or outlier cases are flagged for human review, and that the platform flags missing documentation rather than filling gaps. The criteria that make a case an outlier are not stated.

Fabricated Citation Record

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

Darrow
None located

The AI Hallucination Cases database kept by Damien Charlotin holds no entry naming Darrow or Darrow AI.

Pattern Data
None located

The AI Hallucination Cases database maintained by Damien Charlotin records no case naming Pattern Data, and no court finding on mass tort settlement administration names it. No court order, opinion or disciplinary record naming Pattern Data is on the public record. The product's outputs feed settlement adjudication supervised by courts, and they are facts drawn from records rather than citations.

Bar Guidance Alignment

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

Darrow
Not addressed

No bar association, regulator, rule of professional conduct or ethics opinion is named anywhere in the terms of use, on the home page or in the segment pages. The nearest provisions are the disclaimers at section 8.3 and in the trial warranty clause stating the service is not a substitute for legal advice, legal research and independent review, which disclaim a role rather than engage published guidance. Nothing addresses solicitation and referral rules, which govern case identification and client development more closely than any other area of practice.

Pattern Data
Not addressed

No published material names an ethics opinion, bar rule or professional responsibility framework. Pattern Data's material addresses adjudication appointed by courts and settlement compliance. No guidance from any bar or regulator on lawyers' use of AI is named.

Billing and Fee Posture

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

Darrow
Outside the fee relationship

The published figures describe exposure surfaced and signals detected rather than time or cost saved, so no savings claim is made. Nothing on the home page, the terms of use or the site navigation addresses how work originated through the platform should be billed or disclosed to a client, and nothing describes a per matter record of work done with AI. The product supplies case opportunities to contingency fee firms rather than compressing billable work.

Pattern Data
Savings claims only

Law firms are the primary buyer. Pattern Data claims case review fees cut by up to five times, and settlement submissions in one day rather than fifteen. Nothing addresses how review assisted by AI is recorded or disclosed on a client's bill or in a contingency settlement. Nothing addresses how the cost of AI adjudication by an administrator appointed by a court is allocated.

Outside Counsel Guideline Readiness

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

Darrow
Subprocessors listed

Section 8.3 of the terms of use identifies the AI service providers as third parties including Anthropic Claude and OpenAI, so a firm can name who is behind the AI without asking. The word including leaves the list open, the same clause reserves the right to change providers at any time without prior notice, and section 8.1 acknowledges subprocessors generally without naming any. Nothing addresses a client's consent or notification requirement, and no forwardable pack for clients is offered.

Section 7.1 is headed Privacy Policy and DPA, but no data processing agreement is linked or published anywhere on the site.

Pattern Data
Not addressed

No subprocessor list, model provider list or forwardable disclosure material is published. The FAQ describes retrieval augmented generation over language models without naming a provider, and no customer agreement or DPA is published.

Court Disclosure Support

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

Darrow
Not addressed

Nothing on the home page, the terms of use or the site navigation describes an export, an audit trail, a log of which signals or reasoning produced a given output, or any item by item record a firm could put in front of a court or a regulator. No model is recorded against an output, no human verification step is documented, and no disclosure guidance or template is published. The product's output is intelligence a firm acts on rather than a document it files, though a firm relying on surfaced exposure may still need to account for how a matter was identified.

Pattern Data
Partial record

The platform page states clear sourcing and human validation at every step and that every result can stand up to review, audit or settlement. The product generates settlement packets in the formats administrators require from validated data, a record for each claimant of what was extracted and checked. Nothing states that a record of the model used and the reviewer's verification can be exported for a court. Adjudication under a court's program is performed by the vendor rather than certified by the firm.

What neither one publishes

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.

Signals neither addresses in public material
  • Primary Law Corpus Provenance
  • Good Law Verification
  • Bar Guidance Alignment
Change log

Product updates

The latest logged changes from each vendor, newest first, each linked to its source.

Pattern Data

  • Product / capability

    The new version of Pattern Data's mass tort platform is live in select litigations.

    Source
The Pattern Data update →

In summary

Darrow

Darrow, from Darrow AI Inc., a Delaware corporation based in New York, is a legal intelligence platform that works upstream of litigation. It turns regulatory filings, incident reports, litigation patterns and market activity into signals about where legal exposure is forming. It sells to plaintiff and class action firms, insurers and corporate compliance teams on an annual subscription. According to the AI Legal Index, Darrow shows about thirty customer firms by name, and its terms name Anthropic and OpenAI as providers.

Source: AI Legal Index, 2026

Pattern Data

Pattern Data, based in Charlotte, North Carolina, is an AI case evaluation platform for mass tort litigation, sold to plaintiff and defense firms, settlement administrators and special masters. It screens, develops and settles whole dockets against litigation and settlement criteria, with tailored models for litigations such as Roundup, Camp Lejeune and talc. It has been court appointed to run eligibility and adjudication in settlement programs. According to the AI Legal Index, Pattern Data auto adjudicates eligible claims and flags complex or outlier cases for human review. It prices transactionally by case volume and integrates with Litify. It describes retrieval augmented generation over language models.

Source: AI Legal Index, 2026

Questions buyers ask

Are Darrow and Pattern Data the same kind of product?

No. Darrow works before a case exists, surfacing signals of emerging legal exposure for plaintiff firms, insurers and compliance teams. Pattern Data works once a mass tort exists, evaluating claimants and preparing settlement submissions. Both serve mass tort practices. From the AI Legal Index, based on each vendor's own published materials as of September 27, 2026. No vendor pays for placement.

Does Darrow train on customer data?

Its terms grant Darrow and its subprocessors an irrevocable, perpetual, sublicensable license over customer data for maintaining and developing the service, expressly including training foundation models, with no opt out described. From the AI Legal Index, based on each vendor's own published materials as of September 27, 2026. No vendor pays for placement.

Which AI providers do Darrow and Pattern Data use?

Darrow's terms name Anthropic's Claude and OpenAI as its AI service providers, though the list is not exhaustive and Darrow may change providers without notice. Pattern Data describes retrieval augmented generation over language models. From the AI Legal Index, based on each vendor's own published materials as of September 27, 2026. No vendor pays for placement.

How are Darrow and Pattern Data priced?

Darrow sells an annual subscription set in an order form, payable in advance, non refundable and auto renewing, with overage fees for excessive use. Pattern Data prices transactionally by case volume and by service, tailored to each firm's caseload. From the AI Legal Index, based on each vendor's own published materials as of September 27, 2026. No vendor pays for placement.

Disclosure

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.

Three things to weigh. Darrow's terms grant it an irrevocable, perpetual license over customer data that expressly includes training foundation models. They also let it change AI providers without notice and leave customer data outside their confidentiality definition. Pattern Data publishes no customer agreement and keeps its security and privacy detail on separate pages. Neither publishes a price figure. Neither vendor reviewed this page.

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 465 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
November 10, 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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