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Pre/Dicta

The model is the product. A user enters a case number and receives a forecast; there is no repository, workflow, drafting tool or document store underneath that would work without the model. Only the training data would remain. The vendor says it is neither a self serve analytics tool nor a case law research vendor, and the interface is built around the prediction rather than search. This is a platform that exists to deliver model output.

Pre/Dicta publishes a measured accuracy figure rather than only asserting accuracy. The claim is 85 percent on motions to dismiss, with the test set described as more than 50,000 motions to dismiss across all 94 US federal district courts, drawn from about two decades of federal data. Its limits are stated against the vendor's commercial interest. The 85 percent covers motions to dismiss only, and for the other nine motion types the vendor says it models outcomes rather than predicting them, a distinction shown on the home page.

An interview transcript on Pre/Dicta's own site gives 87 percent, against 85 everywhere else, and nothing reconciles the two. The product forecasts outcomes rather than making cited legal assertions, so grounding to primary authority and citator checks do not apply. The vendor discloses instead that forecasts are produced independently of case facts and precedent. The method behind the figure is not described, so whether it came from a holdout backtest, live tracking or in sample validation is unknown, and no outside validation is published.

A real review surface is published and the rest of the control structure is not. The vendor commits that every output is inspectable down to the underlying docket, that every underlying comparable case is visible, inspectable and linked, and that outcomes are verifiable, which gives a lawyer a genuine route from a forecast back to the matters that produced it. The platform also allows a user to re-weight or change the factors behind a prediction, which is a form of human control over model output rather than passive consumption.

What is absent, checked 31 Aug 2026: nothing states that a lawyer must review before relying, no threshold or confidence gate is described, and nothing addresses what happens when a forecast proves wrong. On a product whose output feeds settlement valuation and venue strategy, the absence of any published statement about the weight a forecast should carry is the gap.

One named customer of real weight, with no figures. John B. Quinn, Executive Chairman and Founding Partner of Quinn Emanuel, is quoted saying all attorneys at the firm now have access to the platform. That is a named firm wide deployment at a major litigation firm, not a logo or anonymous quote. The vendor also won ALM Legal Week's Innovator of the Year award. No figure shows what changed at Quinn Emanuel or anywhere else, and there is no case study with a stated method and no customer count.

No other named customer is published on the pages read. The 85 percent accuracy figure measures the product, not its deployment.

The privacy policy carries a dedicated section on case reports that addresses the actual exposure this product creates. It recognizes that case numbers and reports may be sensitive, and commits that Pre/Dicta does not share, sell or disclose case numbers, case report contents or access history to third parties, that encryption and strict access controls prevent unauthorized viewing, and that case access logs are used only for security monitoring and troubleshooting rather than marketing or profiling.

It also states that case numbers are not stored against a personal profile unless the user creates an account. That is a considered answer to the real risk here, which is that the matters a litigator looks up reveal the firm's docket and strategy. Three gaps: no statement on whether anything a user enters trains any model, no retention period, and privilege and work product are not addressed. Note the underlying exposure is lower than for a document platform, since the input is a case number rather than client files.

Nothing is published on the advice line, and there is nowhere it could sit. There is no disclaimer, ethics or professional responsibility page, no bar or ethics guidance named, including ABA Formal Opinion 512, and no statement that a forecast is not legal advice or no substitute for professional judgment. There are no terms of service either: the footer link labeled Terms of Conditions leads back to the home page, and no terms are published anywhere.

The exposure is high because the published use cases are settlement valuation, venue selection, whether to move to dismiss and whether to challenge an expert, all decisions a client relies on counsel to make.

No governance position is published for a model whose central design choice raises exactly these questions. Pre/Dicta's forecasts rest on judicial biography, and the vendor names the variables: education, appointment history, political affiliation, net worth and location, with judges compared against cohorts of similar background. Its marketing has promoted dismissal rates for Republican appointees, and a biographical intelligence feature lets users isolate a judge's political affiliation to see how it bears on outcomes in similar cases.

No responsible AI statement, accountable owner, testing regime before release or fairness evaluation is published. Nothing discusses what it means to model identifiable federal judges by politics and personal wealth. The vendor may have defensible answers, but none is published, and on this product the question is central.

A general privacy policy covers the ground in principle without specifics. It cites industry standard technical and organizational measures, including encryption, secure servers and limited employee access. It says case report access logs are purged automatically after a limited retention period unless the law requires longer, and handles transfers abroad through Standard Contractual Clauses. No security page is published: no encryption standard, access control model, named subprocessor, breach notification practice or stated retention period.

The policy was also published with unreplaced template placeholders where the company name and privacy contact address should be.

Nothing is published, because there is no agreement to publish it in. The footer of every page carries a link labeled Terms of Conditions, and it resolves to the home page rather than to any document. Searched for terms of service, terms and conditions and any subscription agreement across the site and the wider web and located none. The consequence is total: no indemnity, no liability cap, no warranty or disclaimer of warranty on output, no insurance position, no allocation of risk of any kind between vendor and customer.

This is a product that forecasts whether a motion will be granted and is marketed for settlement valuation and reserve-setting by insurers, sold without published terms addressing what happens when a forecast is wrong. Recorded as a vendor-side absence rather than a retrieval failure: the link exists and points to the wrong place.

No integration into any practice system is published. No API is offered or referenced, no document or matter management system is named, no billing or filing system connection appears, and there is no integrations page. What the vendor publishes in this area are workflow conveniences rather than integrations: the platform is cloud-based and reachable from any location, reports can be shared under the firm's own letterhead, matter numbers can be assigned to reports for cost tracking, and no technical training is required to implement. Useful to a buyer, but none of it moves data between Pre/Dicta and the systems a litigation team already runs.

Cloud delivery is implied and neither the tenancy model nor the region is stated. The only infrastructure statements located are that the platform is cloud-based and accessible from any location, and that data may be transferred to and processed in other countries where the vendor's servers or partners operate, with Standard Contractual Clauses and other lawful safeguards applied to those transfers. That acknowledges cross-border processing while naming no country, no region, no hosting provider and no customer-selectable option.

Nothing describes single or multi-tenancy, and nothing distinguishes where data is stored from where it is processed. No residency commitment of any kind is offered.

A badge with nothing behind it. The footer of every page carries an AICPA SOC for Service Organizations mark, in the non-CPA form licensed to service organizations, which asserts a SOC examination without stating which one. No accompanying text names SOC 1 or SOC 2, no Type I or Type II is specified, no auditor is identified, no coverage period or report date is given, no scope is described, and no route to request a report exists.

There is no trust center or security page anywhere on the property. A mark of this kind is meaningful only alongside the report it refers to, and the report is neither published nor offered.

The vendor describes its own model in detail and says nothing about anything it may depend on. It describes machine learning models trained on about two decades of federal litigation data, around 15 to 20 million cases, with 50 to 100 data points per case, dozens of variables for parties and firms, and biographical profiles of hundreds of federal judges. No third party model provider is identified. The architecture as described looks like proprietary machine learning rather than a licensed foundation model, though nothing confirms that either way.

No model version or release identifier is given, so a buyer cannot tell which model produced a forecast or when it changed. There is no commitment to notify customers of changes to the model or its training data, and no subprocessor or infrastructure provider is named.

No pricing information is published at any level, including the unit of charge. Searched the home page, platform page, privacy policy, the full primary navigation covering platform, about, research center, news, support and contact, and the footer. There is no pricing page, no tier structure, no per-seat, per-case or per-report unit, no volume banding and no statement of what implementation adds. Every call to action is a demo booking or a case consultation request.

The one adjacent statement is that the platform requires no technical training to implement, which speaks to effort rather than cost. Nothing published would let a buyer form any view of price before entering a sales process.

The buyer segments are carefully reasoned, and coverage is only half described. Four buyers are named with the question each brings: litigators setting strategy and timing motions, general counsel choosing outside counsel, private equity valuing law firm acquisitions on portfolio performance, and insurers setting reserves against how similar matters resolve. Each has its own page. Federal coverage is concrete: all 94 district courts, the appellate level, and ten named motion types from motions to dismiss through Daubert challenges, temporary restraining orders and motions to remand.

State coverage is described only as select state courts, with no list, no court detail and no depth statement. The January 2023 acquisition of Gavelytics brought state trial court assets, and their current coverage is not published.