CAMBRIDGE, MA – Jul 15, 2026 – Most medical chronology software requires a sales cycle and a demo call before an attorney ever sees output quality. newcase.ai is taking the opposite approach: litigation teams can test their own medical records firsthand, today. Show, don’t tell. The platform already processes more than 1 million pages of case material monthly. Its accuracy has been benchmarked against senior legal reviewers across 100,000+ pages of depositions and medical records, producing page cited chronologies attorneys can verify fact by fact, an approach aimed at ending the “productivity trap” of AI chronologies that save time on the first pass, then cost more in verification than they saved.
That trap is now familiar to anyone running AI tools on real litigation files. AI-generated medical chronologies are flooding into litigation workflows. They are structured. They look complete. Then law firms, insurance litigation teams, and in-house counsel hit the same wall: hallucinated diagnoses and medications that are not in the record, events attached to the wrong encounter, treatment dates that silently drift during processing, and chronologies that omit the “negative space” that wins cases: gaps in care, missed appointments, contrary diagnoses, medication discontinuations. No careful attorney can sign it, produce it, or take it into a deposition without rebuilding the source verification by hand.
Why Most AI Medical Chronologies Fail Attorney Review
The core problem is a mismatch between summarization logic and litigation logic. Generic medical record summarization tools are built to produce a coherent narrative. A litigator has to prove, page by page, what happened, when it happened, who recorded it, and whether the summary fairly reflects the underlying record. Courts do not ask whether a chronology is structured or plausible. They ask whether every material assertion can be tied to a source, and whether opposing counsel can test that assertion.
Most AI tools in the legal market were never designed for that standard. They were built for general document processing or they simply wrap a generic AI model in litigation branding. Applied to medical records review for attorneys, they produce unsupported inferences, merged events, silent date normalization errors, and chronologies with no provenance trail. Peer-reviewed medical-AI research confirms the pattern: general-purpose systems hallucinate, omit clinically important facts, and mishandle extraction unless tightly grounded in source documents. Those are tolerable defects in a brainstorming draft. They are fatal in a deposition binder, a summary-judgment record, or a trial exhibit.
The result is what legal teams describe as a productivity trap: the AI draft is not wrong enough to discard, but it is uncertain enough that verifying it takes longer than manual medical record review would have.
Benchmarked Across 100,000+ Pages of Medical Records and Depositions
In a benchmark spanning more than 100,000 pages of depositions and medical records, reviewers using newcase.ai were measured against senior legal professionals conducting manual review and against teams using competing AI medical chronology tools. Reviewers with newcase.ai extracted 100% of critical facts with exact citations and completed the work 15 times faster than manual review.
A second benchmark tested three heavily documented medical cases totaling more than 120,000 pages. newcase.ai averaged a completed medical chronology in under 10 minutes per case, extracting 100% of events with correct, source-cited dates, providers, and descriptions. Reviewers again finished 15 times faster than manual review, matching the first benchmark.
The architecture is the difference. newcase.ai reads every page, surfaces every clinical finding with a precise source citation, and maps treatment timelines from complex medical documentation. Every event in a newcase.ai medical chronology links directly to its source document, so counsel can walk any entry back to the underlying record in seconds. Competing medical chronology services and software produced chronologies with unverifiable entries, misattributed events, and missed treatment gaps that no attorney could rely on in a high-stakes proceeding.
The Verification Gap in Legal AI
“There is a recurring theme across the litigation teams we’ve spoken to. They ran an AI chronology on a real file, and it looked polished until they started checking it against the record. Then they spent more hours verifying, adding events, correcting dates, and rebuilding citations than the tool ever saved them. Bar guidance is explicit that lawyers remain fully responsible for AI output, so an uncited chronology transforms from a time-saver to a liability. That’s why we’re letting attorneys test newcase.ai on their own.” — Mustafa Awad, COO and Co-Founder of newcase.ai
Security, Privacy, and Compliance
Medical records are among the most sensitive materials in any legal practice, and privacy law reinforces the same requirements courts do: integrity, access controls, and auditability. newcase.ai runs on a security-first architecture with strict tenant isolation across environments and regular third-party penetration testing. The platform is SOC 2 Type II compliant, with zero data retention across all AI processing workflows. Client data is never shared, sold, or used for model training. All AI processing runs through vendors operating under a Business Associate Agreement (BAA), so workflows involving protected health information remain HIPAA-compliant.
Key Capabilities of the newcase.ai Platform
AI Medical Record Review: Extracts clinical findings, identifies pre-existing conditions, hand-written notes and generates detailed medical chronologies with case-specific analysis. Whether the record set spans 200 pages or 100,000, Every event carries full source verification.
Zero Hallucination Standard: Every extracted fact links directly to its source document with exact page and line citations. The platform never generates information that does not exist in uploaded case materials. newcase.ai surfaces the facts; the attorney determines the strategy.
Cross-Case Deep Insights: Cross-references all evidence across medical records, depositions, and unstructured documents. Surfaces contradictions between testimony and the medical record, identifies inconsistencies across providers, and flags the treatment gaps and record amendments that manual review misses.
AI Deposition Analysis: Generates page-line-cited deposition summaries, cross-references testimony against the medical chronology, and identifies contradictions and key admissions in under 30 seconds per transcript.
Additional Advanced Features: Expert Witness Investigation analyzes an opposing medical expert’s prior depositions, publications, and litigation history to surface inconsistencies and build cross-examination strategy. Deposition Prep maps attorney questioning patterns and tactical approaches across cases, so litigation teams are prepared before they walk into the room.
Self-Serve Access: Test It on Your Own
newcase.ai’s free self-serve trial is available now at newcase.ai. Litigation teams across the United States can sign up securely, upload medical records and case files, and generate fully cited medical chronologies, deposition summaries, and cross-case insights immediately.
Frequently Asked Questions
Q: Does newcase.ai take my case’s specific claims into account when building a medical chronology?
A: Yes. newcase.ai is context-aware, so every chronology is tailored to the claims, issues, and theory of your case. The same medical records produce different chronologies depending on the matter: a delayed sepsis diagnosis case surfaces vital signs, lab values, and nursing notes on the deterioration timeline, while an orthopedic injury case organizes the record around treatment progression, functional limitations, and pre-existing conditions.
Q: Does newcase.ai capture gaps in treatment and contradictions in the medical record?
A: Yes. The legally material facts are often what did not happen. newcase.ai surfaces gaps in care, missed appointments, medication discontinuations, contrary diagnoses, and inconsistencies between providers. It also cross-references the medical record against deposition testimony to flag where witness accounts contradict the documentary evidence, helping teams build causation arguments and anticipate opposing counsel’s treatment-gap arguments.
Q: How does newcase.ai compare to other AI medical chronology tools and medical chronology services?
A: Verifiability. Most chronology software produces fluent summaries without source-level citations, and outsourced services add days of turnaround and per-page costs. newcase.ai delivers chronologies in minutes, with every event cited and linked to its source document, benchmarked at 100% critical fact extraction across 100,000+ pages. Attorneys stay in control: the platform surfaces source-verified facts, and the attorney decides what matters strategically.
Q: Is newcase.ai secure and HIPAA-compliant for medical records?
A: Yes. newcase.ai is SOC 2 Type II compliant, with strict tenant isolation, encryption in transit and at rest, and regular third-party penetration testing. All AI processing runs under a Business Associate Agreement for HIPAA-compliant workflows, with zero data retention across AI pipelines. Uploaded materials are never shared, sold, or used for model training.
Q: Who is newcase.ai designed for?
A: newcase.ai serves law firms, insurance litigation teams, in-house legal departments, and claims professionals handling complex liability cases across the United States. It is built for practice areas where medical records drive case value, including medical malpractice, workers’ compensation, product liability, transportation litigation, premises liability, personal injury, and pharmaceutical and medical device cases.
About newcase.ai
newcase.ai is the AI litigation intelligence platform that connects facts and insights from depositions, medical records, expert testimony, attorney strategy, and case materials into a single searchable intelligence layer. Built for insurance litigation and complex cases, the platform processes more than 1 million pages of case material monthly and has summarized over 40,000 depositions. newcase.ai helps legal teams produce court-ready medical chronologies, uncover contradictions, cross-reference testimony, and develop strategy faster than manual review, with 100% critical fact accuracy and zero hallucinations. Every insight is source-verified with page-line citations, all AI processing runs with zero data retention, and no customer data is ever used for model training. Founded in 2024 and headquartered in Cambridge, MA, newcase.ai is backed by Social Leverage, The LegalTech Fund, and Plug and Play.
Learn more at newcase.ai.
Media ContactCompany Name: newcase.aiContact Person: Mustafa AwadEmail: Send EmailCountry: United StatesWebsite: newcase.ai
