Legal AI for litigation, answered.

Case-level research returns a case. Proposition-level legal research returns the rule that does the legal work: from the court that established it, still good law, with the correct stance toward your party, at the correct procedural stage, and citable in your forum. Deep Research is proposition-level legal AI built on Solon.

Substance verification is confirming that a legal proposition holds, whom it favors, and whether it survived, not merely that the citation exists. Form verification checks that a case is real and the quote matches. Legal substance verification checks citation-to-proposition support: that the proposition is the holding rather than dicta, favors your party, governs in your forum at your posture, and is still good law at the line you cited. See substance verification.

Most AI citation verification stops at case law verification: the citation resolves to a real opinion. That is the commodity floor. Proposition-level citation verification goes further and checks citation support, meaning the case actually stands for the proposition you cited it for. Real cases cited for the wrong proposition are the failure that ordinary citation checks miss.

Yes. Good law verification runs case by case against subsequent history: reversed, modified, vacated, review granted, abrogated by statute. A status problem flips the authority to red before it can reach a draft. Holding verification and treatment classification track how later courts treated the specific proposition, not only the case as a whole.

Yes. Controlling authority research is built in: Deep Research models the forum hierarchy, so binding versus persuasive authority is resolved for the court you are in front of. It is also stage-aware legal research, filtering by procedural posture, and party-favorability legal research, filtering by which side a holding favors.

On purpose. Counter-authority legal research retrieves the adverse cases with their distinguishing patterns, so the adverse authority arrives from Legawrite.AI and not from opposing counsel.

A citation enters a memo only from the verified record, with its source attached, and cannot be rewritten by a model afterward. The citation is never generated. It is retrieved, verified, and locked. That is what makes legal research with verified citations possible by construction.

Every proposition in Solon is verified against the exact source lines it came from, with a documented extraction error rate of 0.003%. On the adversarial ADR-Hard benchmark, Legawrite.AI reaches 88% Dispositive Recall at filing; the strongest alternatives on the same test land between 9% and 24%.

Legawrite.AI runs AI motion drafting as background workflows on one fact and claim foundation. Four are live today: Demand Letter, Complaint Drafter, Demurrer and Complaint Checker. Each pauses for attorney review at the stages that matter and exports to Word on your firm’s own template. See drafting workflows.

Yes, and it is live. Upload the complaint you were served. The demurrer workflow identifies which causes of action are vulnerable, maps the argument structure for each, and drafts the demurrer with grounds tied to each claim. Local Rules apply the court’s deadlines and formatting. It is demurrer drafting software grounded in demurrer legal research on verified propositions.

Yes. Deep Research is live in New York, California and Missouri, so motion to dismiss legal research, including New York CPLR 3211 practice, runs on verified, stage-aware propositions. MotionLogic confirms the motion is the right procedural move before you draft it.

Yes, in two stages, both in Early access with a first group of firms and not generally available. The MSJ Qualifier decides whether a dispositive pathway exists and whether the record is ready to use it. The MSJ Engine then builds the motion structure before prose: every fact mapped to the element it supports, evidence screened for admissibility, and the burden framework applied for the jurisdiction. Summary judgment legal research, including California summary adjudication and separate statement practice and New York CPLR 3212, is available today through Deep Research.

No. The MSJ Qualifier never produces a win probability or a case-strength score. It breaks each claim into elements, burdens, evidence and candidate paths to judgment, answers dozens of narrow questions against Solon and the record, and applies explicit decision rules to mark each pathway QUALIFIED, BLOCKED or UNRESOLVED, with the reason and the strongest opposing argument. Merits and procedural readiness are reported separately. Counsel still decides whether to file.

A single model answer blends legal interpretation, evidence, burden, discovery posture and uncertainty into one fluent narrative, so when it is wrong nobody can say where. The MSJ Qualifier separates those tasks into narrow determinations, grounds each one, keeps UNKNOWN visible instead of turning it into NO, and leaves a decision record showing exactly why a pathway survives or fails.

Opposition drafting is in Early access, built first for oppositions to a demurrer, a motion to dismiss and a motion for summary judgment. Answer to Complaint, the responsive pleading, and Cross-Complaint are also in Early access.

Because a dispositive motion is where being wrong ends a case. Verified legal research for dispositive motions means the right proposition, the right stance, the right stage, good law and currently citable, all at once. That is the test our benchmark measures.

Every law firm AI policy and outside counsel AI policy converges on one question: can you show how this document was made? Look for no model in the citation path, attorney review before filing, per-firm data isolation, no training on client matters, and a legal AI audit trail. Our AI-use disclosure is written to be checked against exactly those policies.

A growing number of judges and courts issue AI standing orders and local rules on AI disclosure in court filings, some requiring a certification about how generative AI was used and that citations were verified. The requirements vary court by court, so check the orders for your judge. Legawrite.AI is built so that whatever you are asked to certify, you can show it on the record.

Legal AI provenance is a record of what was done, in what order, and why. Show Your Work freezes the full derivation record when a document is marked filed: issue framing, research, authorities scored, citations accepted and rejected, validation passes, attorney edits and final text. The record is sealed in immutable storage and its fingerprint is anchored to the Solana blockchain. The contents stay privileged.

Malpractice insurer AI diligence, carrier AI guidelines for panel counsel and client AI use policies all ask for the same evidence: which tool, what checks, who reviewed. For insurance defense firms, a sealed provenance record answers the carrier audit without reconstructing the work after the fact.

Recent decisions do not hold that using AI destroys privilege. Courts have drawn a line between a client using a consumer chatbot under terms that permit disclosure, and attorney-directed use of an enterprise or on-premises tool with contractual confidentiality. The risk is careless disclosure and weak vendor terms.

Yes. Insurance defense legal AI is the first focus: panel counsel partners, staff counsel, and the carriers, risk pools and corporate legal departments that audit the file. It fits practices under billing guidelines, capped rates, pre-approved budgets and flat fees, where efficiency is already forced and the margin stays with the firm.

Panel counsel AI compliance comes down to showing your work. Every filed document carries a sealed derivation record, citations come only from a verified record, and the attorney is the decision-maker of record. That is the evidence a carrier or client AI use policy asks for.

Yes. Public entity litigators are named in our positioning alongside defense boutiques and panel counsel, and the air-gapped deployment serves agencies that cannot send files to the cloud.

LitigationOS is live in New York, California and Missouri. Illinois, Texas and Massachusetts are next, followed by the remaining states. Court local rules coverage is built from more than a thousand local rule documents across California, Nevada and New York. See Local Rules.