Top SitesEve Legal | Legal AI for plaintiff law firms

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robots.txt

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llms.txt

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# Eve

> Eve is an AI-powered legal assistant built exclusively for plaintiff law firms. It covers the full case lifecycle — from intake and evaluation through pre-litigation and litigation — automating document-heavy work so attorneys can focus on strategy and client relationships.

Eve is developed by Butler Labs, Inc. (San Francisco, CA), founded by Jay Madheswaran (CEO, 15+ years in AI/ML, formerly Lightspeed Venture Partners and Facebook), Matt Noe (CPO, founding engineer at Rubrik), and David Zeng (Head of Engineering). The company has raised a Series B round with backing from Lightspeed Venture Partners.

Eve serves plaintiff firms in two primary practice areas: **Personal Injury** and **Labor & Employment**. It is trusted by 1,000+ plaintiff lawyers and has delivered reported outcomes including 250% year-over-year revenue growth, 2.5x increases in case capacity, and 90% faster demand letter generation for client firms.

## Core Product: Eve 2.0

Eve 2.0 is described as a "proactive AI workforce for plaintiff firms." It learns a firm's writing style and preferences during the implementation phase, producing documents that sound like the team wrote them. The platform is positioned not as a generic AI tool but as a specialist partner that trains and grows with each practice.

## Key Use Cases

- **Case Intake and Evaluation**: Assesses case value and key facts; creates comprehensive case files including timelines, claims, witnesses, and evidence to help firms prioritize high-potential cases.
- **Medical Overviews**: Generates complete medical chronologies and damage assessments in minutes; supports unlimited updates as cases evolve.
- **Demand Letters**: Drafts strategic, comprehensive demand letters in the firm's tone and style, with unlimited iterations.
- **Drafting**: Produces complaints, good faith letters, EEOC charges, and other legal documents quickly from case facts.
- **Propounding Discovery**: Generates relevant discovery requests (interrogatories, requests for production, requests for admission) tailored to case facts.
- **Responding to Discovery**: Drafts responses to opposing discovery requests and raises appropriate objections in a fraction of the usual time.

## Security & Compliance

- SOC II Type II certified
- HIPAA compliant
- AES-256 encryption
- Enterprise-grade data protection

## Pricing

Eve uses a custom, sales-gated pricing model. There are no publicly listed tiers or per-seat prices. Prospective customers must book a demo to receive a quote tailored to their firm's size and needs.

## Target Customers

Plaintiff-side law firms — primarily personal injury and labor & employment practices — ranging from solo practitioners to large multi-attorney firms. Not designed for defense-side, transactional, or general business use.

## Resources

- Homepage: https://www.eve.legal
- Book a Demo: https://www.eve.legal/demo
- About / Company: https://www.eve.legal/company
- Working with Eve: https://www.eve.legal/working-with-eve
- AI-Native Law Firms: https://www.eve.legal/ai-native-law-firms
- Blog: https://www.eve.legal/blog
- Webinars: https://www.eve.legal/webinar
- Customer Stories: https://www.eve.legal/customer-stories-old
- Privacy Policy: https://www.eve.legal/privacy-policy
- Master Service Agreement: https://www.eve.legal/eve-enterprise-terms
- Service Level Agreement: https://www.eve.legal/sla

## Practice Area Pages

- Labor and Employment: https://www.eve.legal/practice-area/labor-and-employment
- Personal Injury: https://www.eve.legal/practice-area/personal-injury

## Use Case Pages

- Case Intake and Evaluation: https://www.eve.legal/use-cases/case-intake-and-evaluation
- Medical Overview: https://www.eve.legal/use-cases/medical-overview
- Drafting: https://www.eve.legal/use-cases/drafting
- Demand Letters: https://www.eve.legal/use-cases/demand-letters
- Propounding Discovery: https://www.eve.legal/use-cases/propounding-discovery
- Responding to Discovery: https://www.eve.legal/use-cases/responding-to-discovery

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