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Trellis

Machine learning makes the underlying records usable, on a platform whose base offering is search over public court data. The vendor describes Trellis AI as combining its data with advanced language models to produce case assessments that review facts, claims and defenses and suggest likely outcomes, next steps and risks, along with argument drafting. Underneath is a docket search engine over more than 3,000 courts, close to what the company sold at founding, when it indexed California Superior Court records. Remove the models and a searchable trial court database remains.

Precision is asserted in marketing and disclaimed in the agreement. The vendor describes Trellis AI as leveraging advanced language models to deliver precise insights that enhance decision-making and case preparation, and positions the platform on unmatched coverage. The terms of service then disclaim liability for the omission or inaccuracy of any court-provided data and for any content, errors in or omissions from the online services.

No accuracy figure, error rate, benchmark, test set or published evaluation is published on any surface read. That gap matters more here than on a drafting tool, because the product's output is factual assertions about how named judges have ruled, and a wrong one is not detectable by a reader.

Autonomy is claimed, and no oversight is published. Trellis AI is described as reviewing case facts, claims and defenses to give insight into likely outcomes, recommended actions and risks. Each assessment is said to offer next steps for case management, settlement strategy and trial preparation, and the product also drafts arguments. Nothing says what the system produces unattended, where a lawyer must review before relying on an assessment, or what happens when an output is wrong.

A vendor job listing describes contract attorneys labeling verdict types and monetary awards to ensure data accuracy, which suggests human review in the data pipeline, but a job advert is not product material.

Named users at named institutions, with scale figures that carry no customer. Attributed quotes come from Brian Cassidy, Student Services Librarian at Cleveland State University Law Library, on strategic trial court comparison analytics; Dean Walters, Assistant Director for Content at Harvard Law School, on the platform giving empirical sourcing to what was once anecdote; and Miguel Aristizabal, Partner at Clayton Trial Lawyers.

All three are qualitative. The vendor separately states it serves tens of thousands of law firms and litigators daily across 3,000-plus courts in over 2,500 counties spanning 45 states. No figure for what changed at any named customer is published, and no case study with a stated method was found on the surfaces read.

The vendor makes an explicit confidentiality claim, and the rest of its material cuts against it. Its blog says data confidentiality is a top priority, that the platform relies only on public filings so users need not enter sensitive client or internal data, and that Trellis handles no personal information or confidential case details. On the other side, the privacy policy describes collecting personal information. It limits disclosure of usage data to third parties except to service the account, enforce the terms, meet obligations to content and technology providers, or as law requires, which is a general assurance rather than a commitment about what the product holds.

The knowledge base says judge pages show career history and political affiliation, so the platform does handle identifying information about named public officials. Trellis Envelopes, an in app messaging service for sharing rulings, dockets and documents between users, is a channel for the internal material the blog says users never need to enter. Nothing addresses training on queries or shared material, retention, segregation or access, or privilege and work product, on a product where a litigator's searches reveal strategy.

Nothing is published on the advice line. There is no statement that Trellis output is not legal advice, no professional responsibility or ethics page, and no bar or ethics guidance named, including ABA Formal Opinion 512. Nothing addresses a lawyer's competence or supervision duties when relying on an assessment that recommends actions and settlement steps. The terms carry one significant use restriction, but it is regulatory rather than professional: no user may use the data to decide a consumer's eligibility for credit, insurance or a government license or benefit, with consumer defined by the Fair Credit Reporting Act at 15 USC 1681. That addresses the vendor's exposure as a data provider, not the lawyer's duties.

No governance position on model behavior is published. Nothing names an accountable owner, describes testing before release, publishes a responsible AI framework or discloses anything about uneven output. The absence is notable on this product. The platform builds analytical profiles of named judges, and the knowledge base says judge pages show career history and political affiliation alongside ruling tendencies. A product that scores identifiable public officials and shows their political affiliation calls for published bias testing, and none exists.

A general privacy policy covers the website and account relationship, not what a user does inside the product. The policy says Trellis does not sell customer or user data and limits disclosure of usage data to unaffiliated third parties, and that a user may cancel registration at any time in settings. No security page is published: no encryption standard, access control model, retention period, named subprocessor, breach notification practice or deletion commitment beyond account cancellation.

The vendor argues the exposure is low, saying on its blog that the platform relies only on public filings and does not handle personal information or confidential case details. That is a real mitigating point, but it sits uneasily with a privacy policy that describes collecting personal information and with an in app feature for sharing documents between users.

Liability is addressed only through a limitation clause, and that clause disclaims precisely the exposure the product creates. The terms of service state that Trellis shall not be liable for any loss, injury, claim, liability or damage of any kind resulting in any way from any content, errors in or omissions from the online services, the unavailability or interruption of the services, the customer's use of them, the loss or corruption of any data, or the omission or inaccuracy of any court-provided data, all to the fullest extent permissible by applicable law.

The services may also be enhanced, added to, withdrawn or otherwise changed without notice. No indemnity running to the customer, no warranty on output and no insurance position is published, and the cap was not among the text retrievable. A separate subscription agreement is referenced by the terms and is not published, so the full allocation may sit there.

One real integration route, documented at a high level, and nothing else. Trellis publishes an API with its own support documentation, described as providing access to state and federal court data that was previously siloed and fragmented and as available for integrating Trellis directly into a customer's workflow. That is a genuine route for a firm building its own tooling. What is not published is integration into the systems litigation work otherwise lives in: no document management, no matter management, no practice management, no filing system and no named third-party connector of any kind.

Nor was implementer-level documentation reached, since only the API overview was retrievable and it describes availability rather than what the endpoints return or how authentication and rate limits work.

Nothing published on where the software runs or where customer data sits. No hosting provider is named, no tenancy model is stated, no region or residency option is offered, and nothing distinguishes processing from storage. The single geographic statement located runs the other way and is a restriction rather than an option: the terms of service state that, to comply with local privacy, data protection and other laws, the customer may not access Trellis outside the United States. That tells a buyer where they may use the product, not where their data lives.

No independent security attestation is published in vendor material. No certification, auditor, scope, coverage period or penetration test is named, and there is no trust center or portal. A third party blog says the company follows SOC 2 security standards, but nothing from the vendor confirms it. A different, unrelated company also trading as Trellis, at trelliscare.app, publishes a detailed healthcare security page covering HIPAA, business associate agreements and zero data retention; it is not this vendor.

Nothing published about the model supply chain a customer inherits. The vendor's own product announcement states that Trellis AI leverages its data foundation along with advanced language models, which acknowledges that language models are involved and identifies none of them. Searched the home page, that announcement, the API documentation, the knowledge base index, the terms of service and the privacy policy: no provider is named, no model or version is identified, no architecture is described, no processing location is given, no subprocessor list exists, and nothing commits the vendor to notifying customers when any of it changes.

The privacy policy's reference to obligations to content and technology providers acknowledges third parties in the chain without naming one.

Pricing is published for part of the range, and the firm tier is withheld. The vendor's knowledge base page on subscription tiers, read, sets out four plans. Three have monthly and annual rates: Personal at $69.95 a month or $649.95 a year, Research at $129.95 a month or $1,099.95 a year, and Research and Judge Analytics at $199.95 a month or $1,999.95 a year. Each comes with an annual allowance of content views, 240 on Personal and 900 on the two Research tiers.

All three cover a single state, and Judge Analytics separates the top published tier. The fourth plan, Law Firm and Academia, has no price and leads to a sales form. Documents are charged separately: some are included, some can be requested free within a monthly limit in Los Angeles and Cook counties, and others are bought, with a deferred billing add-on for enterprise document purchases. The tier a serious firm would buy is the one without a number, and nothing says what implementation or onboarding adds.

Coverage is quantified precisely and the audience is segmented in detail, with the boundaries stated only in part. The vendor publishes coverage as more than 3,000 courts across over 2,500 counties spanning 45 states, and the API documentation and plans navigation add federal circuits, bankruptcy courts and the Supreme Court. Audience segmentation runs to role rather than just firm type, with published pages for associates, partners, knowledge management and marketing or business development inside law firms, plus in-house legal, and the customer evidence adds academic law libraries.

Practice coverage is expressed concretely through motion type and legal issue pages and through published treatises and primers on how common motions are handled at trial court level. Two limits are stated: access is restricted to the United States by the terms of service, and the data may not be used for Fair Credit Reporting Act eligibility determinations. What is not stated is which of the 45 states are covered to what depth, and the state-only positioning used in much of the marketing sits awkwardly beside the federal coverage the API page claims.