EvenUp cuts document drafting from 15 hours to 15 minutes with Claude
EvenUp, a legal technology platform for personal injury firms that has resolved more than 200,000 cases and secured more than $10 billion in damages for injury victims, built its AI Drafts product on Claude, with Opus 4.8 handling deep reasoning and consistency-checking, and Sonnet or Haiku handling everyday extraction from case records that can run 1,000-plus pages. Document drafting that previously took 8 to 15 hours of skilled paralegal work now returns as finished drafts in about 30 minutes, a roughly 99% time reduction, while settlement offers across EvenUp's customer firms rose 300% and one firm cleared a 45-day demand-writing backlog after drafting time fell from about a month to roughly ten minutes per case.
Overview
EvenUp, a legal technology platform for personal injury firms that has resolved more than 200,000 cases and secured more than $10 billion in damages for injury victims, built its AI Drafts product on Claude, with Opus 4.8 handling deep reasoning and consistency-checking, and Sonnet or Haiku handling everyday extraction from case records that can run 1,000-plus pages. Document drafting that previously took 8 to 15 hours of skilled paralegal work now returns as finished drafts in about 30 minutes, a roughly 99% time reduction, while settlement offers across EvenUp's customer firms rose 300% and one firm cleared a 45-day demand-writing backlog after drafting time fell from about a month to roughly ten minutes per case.
This entry has 14 published fields tied to exact passages in an immutable source capture.
Inspect the highlighted sourceThe challenge
A personal injury case runs on documents - demands, negotiation sheets, discovery responses, medical summaries - each of which has to be formatted correctly, factually airtight, and toned to match the firm. Before EvenUp, that was entirely manual: a paralegal worked through stacks of records that were weeks late and out of order, with the same visit sometimes documented three different ways by three different providers. One California firm ran its entire demand-writing function through a single person and carried a 45-day backlog; paralegals at an Ohio firm built medical chronologies and totaled bills by hand, taking 8 to 15 hours per case, forcing firms to choose between eating the hours or referring the case out.
The solution
EvenUp's AI Drafts reads each page of a case (often 1,000+ pages from a dozen providers) the most affordable way it can - real text, then standard OCR, then Claude's vision for scanned bills and checkbox forms - and sorts documents by type so the system only asks each page what it can answer. Every fact keeps a citation to its source page, duplicates are merged, and the record is settled once before drafting starts. Opus 4.8 sets the drafting blueprint (applicable legal rules, likely opposing arguments, the case's throughline) and checks it for consistency once; Sonnet then writes each section from that blueprint following state-by-state rules written in plain English. Everyday extraction runs on Sonnet or Haiku, reserving Opus for tasks where a subtly wrong argument could hide inside polished text. Every draft still ends with an attorney reading, checking, and signing it.
Reported business value
Drafting that once took 8 to 15 hours of skilled work now returns as finished drafts in about 30 minutes, a 99% decrease. Settlement offers across EvenUp's customer firms are up 300%. The California firm that ran all its demand writing through one person cleared its 45-day backlog, with demands that took a month now taking about ten minutes and attorney review moving 75% faster. An Oregon firm's drafting turnaround fell from months to days and its team reported 400% revenue growth in one year. Inside EvenUp itself, 200+ employees use Claude Enterprise and Claude Code is spreading through engineering.
Sources
Open any source and check the claim yourself — that is the point of the register.
This record was researched and written with AI assistance, and its claims were checked against the sources above. (EU AI Act art. 50 transparency notice.)
Other legal entries in the register.
Darrow raises $35M for an AI that parses public documents for class action lawsuit potential
Darrow, a legal tech startup founded in 2020, built an AI-based data engine that crawls thousands of sources of publicly available information (newsfeeds, social media, consumer complaints, regulatory filings, SEC filings, environmental reports, court dockets) to identify class-action litigation potential in areas such as data privacy violations, environmental contamination, and discrimination, and to predict likely legal outcomes and case value. A team of legal data specialists, including former lawyers, reviews the AI-surfaced insights before lawyers use the platform for case review and discovery. Around 50 law firms, covering hundreds of lawyers, were using the product, and active cases stemming from Darrow's data insights totaled around $10 billion in claims at the time of the funding round.
Delivering agentic AI to law firms globally using AWS with stp.one
stp.one, a Karlsruhe, Germany-based legal tech provider founded in 1993, built Legal Twin, an AI-driven platform integrated with its document management system STP Documents, using Amazon Bedrock (including Anthropic's Claude and the Titan embedding model) and Amazon Aurora PostgreSQL. Legal Twin offers six AI-powered capabilities including intelligent contract risk analysis and automated receivables processing, with responses grounded in case documents and court decisions and citations shown so lawyers can verify sources. It supports Model Context Protocol integration and lets clients with data sovereignty requirements store and process data locally, connecting on-premises storage with cloud-based processing. Certain claims that traditionally took 6-10 minutes to file can now be processed in under 30 seconds using Legal Twin, and productivity gains for users reach up to 3x at the upper end. The platform must comply with GDPR and Germany's federal code for lawyers.
IDEXX Laboratories cuts contract sanctions review from weeks to 20 minutes with Luminance AI
IDEXX Laboratories used the AI-powered contract automation platform Luminance to review its entire contract database for connections to sanctioned countries and entities following Russia's invasion of Ukraine, completing in 20 minutes a review that would typically have taken weeks manually. Separately, Koch Industries' in-house legal team uses Luminance Corporate to automate generation of NDAs, master service agreements and IT-related contracts, including self-service contract generation for non-legal business units, and Deloitte used Luminance on a project standardizing 4,500 contracts across 14 European entities for client BT in two weeks, estimating a 50% time savings versus manual review.
Spellbook runs 530,000 contract reviews a month with Claude
Spellbook, a contract drafting and review platform serving 5,000 customers across 80 countries including in-house legal teams at companies like LG, Dropbox and eBay, built Claude-powered agents that review and redline contracts inside Microsoft Word, apply each legal team's own review standards automatically, and orchestrate about 15 different Claude agent configurations matched to task complexity. Spellbook's agents now run about 530,000 contract reviews a month and field more than 700,000 lawyer chat messages a month, cutting the time to complete an agreement roughly 10x, from about 10 hours of lawyer work to about one hour.
Was this helpful?
Your feedback helps us improve our use case database

