EvenUp vs Filevine: how they compare in 2026

The models are the entire product, and the company was built around a proprietary dataset to feed them. Piai is named as EvenUp's own AI engine, and the vendor's central technical claim is that it is trained on a large dataset specific to personal injury rather than adapted from a general model. Every deliverable is model output. Medical chronologies are generated from raw records with treatment timelines and ICD extraction, demand letters are generated end to end, case valuations come from a settlement repository, and analytics sit on top of the extracted data. Remove the models and nothing remains but a document store the firm already had. Independent review material reaches the same conclusion, describing it as a vertical drafting engine trained on injury cases rather than a general legal assistant.

Filevine names more than a dozen AI products and sells them on top of a complete practice management system. They include MedChron for medical chronologies, DemandsAI for demand letters, Depo CoPilot, Depo Summaries, AIFields, AI Doc Review, AI Data Mapping, ValidationAI, ImmigrationAI, Leads AI, Ask LOIS, LOIS for Word and the LOIS Console. The medical chronology and the demand letter are core work in a personal injury practice, and the AI drives both. Underneath sits the platform Filevine sold before the AI: matters, documents, intake, billing, electronic signature, analytics and deadlines. Without the models, a firm keeps running on that platform. The AI is sold as packages and extensions on top of it, with its own free tier.

Grounding is built into the deliverable, and the vendor publishes no measured figure. Medical chronologies carry citations back to source documents, so a reviewer can check any entry against the underlying record, which suits output that is a factual account of someone's treatment. Demand packages cite comparable verdicts from the settlement repository, so the valuation argument traces to named prior outcomes, and a Thomson Reuters and Westlaw integration supports legal citation. There are two gaps. Two accuracy figures circulate in third party material and neither is published in vendor material with a method attached: that chronologies capture over 90 percent of relevant medical information on first pass, and that demands are 69 percent more likely to reach policy limits. Neither comes with a sample, baseline or definition. And nothing says what the system does when a record is illegible, contradictory or missing, which in medical record work is the common case.

Grounding is claimed across products and accuracy is not measured. Ask LOIS returns grounded, traceable answers, LOIS for Word gives source linked recommendations, Depo Summaries carry page and line references, and the free LOIS Explore tier cites every result to source. A legal research opinion reader lets a user open the authority. The agreement names the failure modes: output may be incomplete, contain factual or legal errors, reflect bias, or differ for similar inputs. What is missing is any number. No accuracy figure, test set, evaluation or error rate is published, though AIFields marketing invites buyers to stop struggling with hallucinations. MedChron's output points to sources only when applicable.

Oversight is sold as a product tier, which makes it visible rather than aspirational. Demands are offered in tiers from instant AI generation through Express Demands to an expert reviewed tier, where an in house team checks the document before delivery. Independent material notes that the human quality step adds turnaround time, a trade off made visible in the pricing structure. Output is consistently positioned as a draft that requires attorney review. The mechanics are not published: nothing says what the in house reviewers check or against what standard, or what distinguishes the tiers beyond speed. No confidence indication is given on generated content, and nothing describes the instant tier, where no human sits between generation and the attorney's inbox.

The review duty is in the contract, and it names the act required. Section 3.2 of the subscription agreement makes the customer responsible for reviewing and verifying output, and for confirming citations and legal conclusions before relying on it or sharing it with a client or a court. An AI Acceptable Use Policy is part of the agreement, AI drafting is described as human verified, and outputs link back to the underlying material. The agreement also warns that similar inputs may produce different output. What is missing: no abstention behavior, no confidence indicator, no threshold at which a feature declines, and no route to report a wrong output.

Outcome claims are specific and named firms appear, but the best available source flags the whole class as vendor supplied. Lundy Law is reported to have increased output from about 30 to about 110 demand packages a month after adopting AI tooling without adding staff, and J. Chrisp Law to have reclaimed 80 hours of paralegal time per case. Those are named firms with quantified operational change. The vendor claim that demands are 69 percent more likely to reach policy limits is the most consequential figure, because it speaks to case outcome rather than throughput, and it carries no method, comparison group or sample. The independent guide reporting these figures says most such benchmarks come from vendor marketing and that results depend on case complexity and record volume. The adoption story is credible and consistently reported, but none of it is published as a vendor case study with a method.

Filevine publishes volume claims rather than customer outcomes. It says customers draft about 100,000 demand letters a month, and claims the largest and most accurate personal injury case management data repository in the world. One case study headline names a shareholder who brought 125 active cases under control, without naming the firm. The agreement lets Filevine use a customer's name and logo, with a right to withdraw. No measured outcome for a named organization is published. Filevine has a customers and case studies library.

Confidentiality evidence here rests on a health specific credential. The product takes in complete medical records, billing statements and treatment histories for injured claimants, so the confidential material is not only the client's legal matter but a third party's protected health information. Against that sit an independently assessed HIPAA attestation validating safeguards for PHI and a SOC 2 Type 2 examination whose scope includes confidentiality and privacy as well as security and availability. The vendor also says it supports customers handling sensitive information through contractual, technical, organizational and compliance measures, which acknowledges the business associate relationship a plaintiff firm needs. Nothing addresses legal professional privilege or attorney work product. A demand package is work product and the case strategy in a valuation is privileged, but the published posture covers health data protection and general security without reaching the legal side at all.

Filevine's agreement makes substantive commitments on confidentiality and training. Third party AI providers are barred in writing from training on customer data and from keeping it beyond the request, except briefly for abuse monitoring. The customer owns its data, including output, and customer data is confidential information for seven years, with trade secrets protected indefinitely. Filevine cannot reduce its confidentiality or security commitments mid term without consent. Another customer's queries and output are not the customer's data, which separates tenants. What is missing is separation inside a firm: nothing describes a wall between two matters, which is live for a plaintiff firm with adverse cases.

Not located in vendor material. The product generates the demand letter a firm sends to an insurer, which is an advocacy document making legal and valuation arguments on a client's behalf, and it generates the case valuation that shapes settlement advice. Independent material states consistently that output is a draft requiring attorney review, and that framing is not published as a vendor published position. Nothing addresses the supervising attorney's duty over machine drafted advocacy, the professional responsibility of relying on a machine generated valuation when advising a client whether to settle, or any bar guidance. The gap matters more here than on a research tool because the output goes out under the firm's name to an adverse party.

Filevine's agreement draws the advice line clearly. Filevine is not a law firm and does not give legal advice, and using output creates no attorney client relationship. The customer must confirm citations and legal conclusions before relying on output or sharing it with a client or a court, which names the duty and the audience. An AI Acceptable Use Policy governs permitted uses. What is missing: no bar or ethics authority is named, including ABA Formal Opinion 512, and no jurisdiction limit is stated for a platform used in immigration, criminal defense and prosecution work across every state.

Nothing published about how the models are governed or evaluated. No AI policy, no model card, no bias or fairness testing, no evaluation methodology or result, no accuracy monitoring, no drift statement, no named governance body and no ISO 42001. The untested risk on this product is specific and serious: case valuation is generated from a settlement repository of past outcomes, and historical personal injury settlements carry the demographic and geographic patterns of who was compensated well and who was not. A valuation engine trained on that history can reproduce those patterns for a new claimant while presenting the result as a data backed figure, and nothing published indicates whether that has ever been examined.

Filevine publishes six AI principles: fairness, reliability and safety, privacy and security, inclusiveness, transparency and accountability. The fairness principle commits to fighting bias in its legal AI tools. The agreement repeats the point where it binds, stating that output may reflect biases in training data. Governance has some structure: an AI Acceptable Use Policy is part of the agreement, Filevine keeps a list of permitted models, and it cannot reduce its confidentiality or security commitments mid term without consent. A Head Legal Futurist and a Legal Futurist are named roles. What is missing is testing: no evaluation before release, no published result, and no bias audit or fairness measure.

Data handling is credentialed and the training question is unanswered. The HIPAA attestation and the SOC 2 Type 2 privacy and confidentiality scope show that safeguards over protected health information have been independently assessed, which is real stewardship evidence. No statement is published on whether medical records, demand drafts, case files or settlement outcomes submitted by firms are used to train or improve Piai, how long client content is kept, or whether a firm can require deletion. The question is central for this vendor: its main technical claim is a proprietary model trained on a large personal injury dataset, and nothing published says where that dataset came from or whether customer matters continue to feed it. A credential covering how data is protected is not a statement about what it is used for.

Filevine's Data Protection Agreement (updated 14 Jan 2026) covers all five elements. Personal information is kept for the life of the service, then destroyed or returned on the customer's written direction. If law forces Filevine to keep something, it must tell the customer what, why and when it will be destroyed, and certify destruction within thirty days. Access is limited to staff who need it, with training and background checks where lawful. Subprocessors sign terms at least as protective, the list sits in Annex C, customers can subscribe to change notices and object within ten business days, and Filevine is liable for its subprocessors. Breaches are notified promptly, with the data affected, the number of people, the steps taken and a named contact, and Filevine bears reasonable costs. What is missing is a fixed notice deadline in hours.

No published position is published on liability for AI output, warranty, service levels or remedy. The exposure is concrete here. A missed injury, a misread treatment date or an omitted provider in a generated chronology flows straight into a demand letter and can understate a claim, and an understated demand that settles is a loss the claimant never learns about. A generated valuation that anchors a firm low has the same effect. No published vendor position addresses any of it, so the risk sits with the firm and ultimately the injured claimant. Enterprise agreements govern this and are not public.

Filevine publishes a full liability position on four fronts. It defends and indemnifies against third party claims that the service infringes a US patent or copyright or misappropriates a trade secret, with remedies of a license, a fix, or termination and refund. Total liability is capped at the greater of twelve months of fees or two hundred thousand dollars, so smaller customers get a floor. The cap reaches claims from a security breach of customer data, gross negligence and intentional misconduct sit outside it where law requires, and the infringement indemnity is uncapped. Filevine commits to insurance from carriers rated A minus, VI or better by A.M. Best. It also warrants that the service conforms to its documentation and complies with law, with 99.0 percent uptime and service credits. What is not covered: output carries no warranty and is excluded from the indemnity.

One substantive integration is named, and the connections this buyer needs most are not. A Thomson Reuters and Westlaw integration supports legal citation inside generated demand packages, a real integration for a plaintiff drafting tool that gives the citation layer an established source. No case management system integration is published, and for a personal injury firm that is the connection that matters, since the practice runs on a case management platform holding intake, treatment tracking and deadlines. No API or export documentation is published either, and nothing describes how records get in or how a finished demand returns to the matter file. Independent comparisons in this market treat case management integration as a primary criterion, which makes its absence notable.

Filevine names real integrations. LOIS for Word puts drafting and redlining inside Microsoft Word with source linked recommendations. Microsoft 365 integration is reported, DataBridge gives real time access to Filevine data, Vinesign has a public API, and native and partner integrations are sold as an extension. The agreement grants API access. Deposition scheduling books court reporters and creates Zoom links. What is missing is depth: nothing says what moves, in which direction or with what setup, and nothing is published for iManage, NetDocuments or ebilling. Filevine has an integrations and API page.

Nothing is published. No hosting provider is named, no region or data residency commitment is published, and no single tenant or dedicated instance option is described. For a platform holding protected health information for injured claimants, where that data sits and how it is separated is a question a firm's compliance review would ask directly. The HIPAA attestation shows that safeguards were assessed without saying where the data sits. The Trust Center's request access route was not used and may hold residency detail.

Filevine runs in the cloud on Amazon Web Services, named on its case management page and pricing FAQ, with separate US and Canadian login domains. The Data Protection Agreement names Filevine, Inc. in Salt Lake City, Utah as the data importer and names a Data Protection Officer. Transfers from Europe, the UK and Switzerland run on Standard Contractual Clauses and the UK addendum, with supervisory authorities listed. Government access requests are notified to the customer only. What is missing is a residency choice: no region list, no selectable location, no tenancy model, and no statement of where AI inference runs, which matters because third party AI providers process customer data.

Scope, currency and a self serve route are all published. A Trust Center at trust.evenuplaw.com describes security, privacy and compliance practices and offers a request access route to documentation rather than a sales gate. The attestation is named with its scope: a SOC 2 Type 2 examination covering security, availability, confidentiality and privacy, four of the five Trust Services Criteria. Currency is dated, with recertification announced in April 2026. Alongside it sits an independently conducted HIPAA compliance assessment and attestation, the credential this product needs given that it processes protected health information. The vendor correctly explains that HIPAA has no formal certification and that what exists is a third party attestation. The auditing firm is not named for either the SOC 2 or the HIPAA assessment.

Filevine claims SOC 2 Type II, SOC 3, HIPAA, CJIS, HITECH and GDPR on a structured security page. Its Data Protection Agreement adds the route behind the claims. An independent third party audits data processing and security controls at least once a year. Audit reports are available on the customer's written request, under confidentiality, and issues are handled through a corrective action plan. If no audit happened in the past year, or Filevine declines to share reports, the customer gets a direct audit right on 21 days' notice. Filevine also answers a security questionnaire once a year within six weeks. What is missing: no auditor, report date or coverage period is published, and the certifications carry no scope.

Nothing located. Piai is named and claimed as proprietary, trained on a personal injury specific dataset, and that is a statement about ownership rather than about supply chain. No foundation model provider is named, nothing states whether third party models sit underneath Piai or process any part of the pipeline, no subprocessor list is published, and the Thomson Reuters and Westlaw integration establishes at least one external data relationship without any accompanying disclosure of what flows to it. For a product handling protected health information, the identity of every party in the processing chain is a question a firm's HIPAA business associate review asks directly and it cannot be answered from public material.

The agreement confirms third party models are used and does not say whose. Section 3.1 says AI features use models from third party AI providers, and section 4.3 commits Filevine to keep a list of permitted models. No model, provider or version is published. The AI principles page calls Filevine's AI proprietary, and nothing reconciles that with the agreement. The providers are bound not to train on customer data or keep it beyond a request, except briefly for abuse monitoring. Material changes need thirty days' notice, though nothing is specific to models. Filevine links a Subprocessors page.

No pricing is published at any level. Independent review material describes the model as charged per case rather than per seat, so cost scales with caseload rather than headcount, and notes that the platform pays off only at sufficient injury volume. None of that comes from the vendor: there is no price, range, per case figure or tier structure, and no indication of what a demand package costs. Every route is a sales conversation and an annual contract. The absence weighs more for contingency fee firms, which carry case costs themselves, because a per case charge comes directly out of a claimant's eventual recovery.

Filevine publishes the full shape of its pricing and no figure. Filevine's pricing page lists the LOIS AI tier with seven components, four platform packages (Matters, Intake, Depositions and Signatures) with their features, and five Matters extensions. A free tier, LOIS Explore, needs no credit card and covers document questions, AI drafting, legal research and the opinion reader, but does not connect to case management. The agreement adds billing terms: interest at up to 1.5 percent a month after ten days overdue, suspension at ten days, a ten day window to dispute a charge, retroactive overage billing from usage telemetry, and no refunds outside warranty or breach. Implementation, configuration and data migration are done by separate certified partners for their own fees. What is missing is any number, at any tier. Every route to a price is a demo or a custom quote.

Depth in one practice area, stated plainly, with the boundary acknowledged. The vendor says it builds for plaintiff personal injury and nothing else, and independent review confirms it is not a general legal assistant. Within that scope coverage is deep. Inputs include police reports, medical records, billing statements, photographs and intake notes, and outputs include demand letters, chronologies, case valuations, negotiation preparation and caseload analytics, with a settlement repository supporting comparables by jurisdiction. Specializing in one practice is a design decision rather than a coverage failure. What is not described is the data behind the main differentiator. Nothing says how many verdicts or settlements the repository holds, which jurisdictions it covers, its date range, how often it updates, or whether it is deep enough in a given venue for a comparable to carry weight, which an attorney relying on that citation in negotiation needs to know.

Filevine publishes seventeen segment pages. By practice: personal injury, family law, mass torts, immigration, insurance defense, criminal defense and estate planning. By government tier: prosecutors, public defenders, states and municipalities, attorneys general and federal agencies, backed by agreement clauses on sovereign immunity and FAR and DFARS designations. By corporate use: in house counsel. By size: solo, small, mid size and big law. ImmigrationAI handles documents in 170 languages, and Timely generates court deadlines for any jurisdiction in the country. What is missing is any limit: no unsupported practice, matter type, jurisdiction or scale is named, and the deadline claim has no coverage table.