AI Legal Index
Vendors · Plaintiff & Claims AI

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Pattern Data

Pattern Data is an AI case evaluation platform built for mass tort litigation, sold to plaintiff law firms, defense firms, settlement administrators and special masters. It takes a firm's whole docket, from hundreds to millions of pages of medical and administrative records, and evaluates every claimant against the same criteria for the litigation. Screen confirms product use or exposure and qualifying injury and flags missing documentation.

Develop reconciles full records against expanded criteria such as treatments and risk factors to model valuation. Settle calculates settlement points under the agreement's criteria and generates submission packets in the formats claims administrators require. The engine uses retrieval augmented generation over language models, with models tailored to litigations including Roundup, AFFF, Camp Lejeune, Depo-Provera, hair relaxer, GLP-1, Paraquat, talc and Zantac.

Case reviewers validate findings, eligible claims can be decided automatically, and complex or outlier cases are flagged for human review. The company states more than thirty litigations and 1.4 million cases on the platform, and integrates with Litify. Pattern Data is based in Charlotte, North Carolina, and prices by case volume and service.

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Pattern Data, 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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Alternatives

Alternatives to Pattern Data

Vendors in the same categories as Pattern Data whose graded profiles look most alike, with a line on what each product does.

Similar is not the same, so check that each one does the job you need. No vendor pays for placement.

Ordered by how closely the graded profiles match across the 15 capability axes, inside the same categories. See how each axis is graded in the methodology.

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 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.

Source: Vendor Published
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.

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.

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.

Source: Vendor Published
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.

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.

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.

Source: Vendor Published
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.

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.

Source: Vendor Published
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.

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 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.

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.

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.

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.

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.

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

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.

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.

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 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.

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

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.

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.

Source: Vendor Published
CC on Deployment Model and Data ResidencyCloud delivery is implied and neither the tenancy model nor the region is stated.

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 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.

Source: Vendor Published
CC on Security Certifications and Trust CenterBadges appear on the site with no scope, no date, and no report available.

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.

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.

Source: Vendor Published
CC on Model Supply Chain DisclosureThe vendor refers to advanced or proprietary models without identifying what sits underneath.

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.

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.

Source: Vendor Published
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.

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.

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.

Source: Vendor Published
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.

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.

Source: Vendor Published
Sources on file

3 public documents

The public pages on file for Pattern Data, 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.

Pricing

No published figure

  • You pay per case, and per service you use: analyzing cases, working out settlement shares, and building settlement packets.
  • The company sets a tailored deal with each firm based on how many cases it has.
  • It says review fees end up about a fifth of what manual review costs.
  • No actual rates are published.
Source: Vendor PublishedWhich legal AI vendors publish their pricing →

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

What changed

Tracked changes at Pattern Data

Oct 12, 2026Product / capabilityVerified

The new version of Pattern Data's mass tort platform is live in select litigations. Every case now opens with each litigation criterion showing what the record establishes, what is missing and the step that closes the gap, with gaps graded critical, major or minor. A review panel lets the reviewer accept, reject or adjust each suggested value with its reasoning and source document, and a change history shows whether each value came from Pattern or the firm, and who changed it when.

Bears on: Autonomy and Oversight ModelSource
Every tracked change for Pattern Data →

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?

No agreement published

No customer agreement, terms of service or equivalent contract is published on any surface located, and no policy page states a position on training. Nothing is granted and nothing is withheld, so a client has no term to hold the firm to. Where a policy page does state a position, the row takes the matching policy value instead and the summary records that no agreement exists.

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.

Source: Operator VerifiedAs of Sep 6, 2026

Prompt and Output Retention

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

Not addressed

No located public material states how long prompts and outputs are retained.

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.

Source: Operator VerifiedAs of Sep 6, 2026

Ethical Walls and Matter Segregation

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

Claimed, not documented

Segregation is asserted in public materials with no published detail on how it is enforced.

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.

Source: Vendor PublishedRobust multi-factor authentication and stringent access controlsAs of Sep 6, 2026Evidence

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.

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

Source: Operator VerifiedAs of Sep 6, 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?

Not addressed

No located public material identifies the corpus behind the product’s answers.

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.

Source: Operator VerifiedAs of Sep 6, 2026

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.

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.

Source: Operator VerifiedAs of Sep 6, 2026

Refusal and Uncertainty Behavior

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

Documented

The vendor describes refusal or abstention behavior in public materials.

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.

Source: Vendor PublishedFlagging complex or outlier cases for human reviewAs of Sep 6, 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.

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.

Source: Operator VerifiedAs of Sep 6, 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.

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.

Source: Operator VerifiedAs of Sep 6, 2026

Billing and Fee Posture

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

Savings claims only

Public materials claim time savings without addressing billing or disclosure, and the product sits inside a fee relationship between a lawyer and a client where those savings would change the bill.

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.

Source: Vendor Publishedtypically reducing case review fees by up to 5x compared to traditional review methodsAs of Sep 6, 2026Evidence

Outside Counsel Guideline Readiness

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

Not addressed

No located public material supports a client side disclosure obligation.

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.

Source: Operator VerifiedAs of Sep 6, 2026

Court Disclosure Support

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

Partial record

Some elements of the record are available, short of a document level export.

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.

Source: Vendor PublishedEvery result can stand up to review, audit, or settlementAs of Sep 6, 2026Evidence
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 462 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 19, 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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