Library/olawForked

harvard-lil/olaw

olaw

AI + Legal APIs: A Tool-Based Retrieval Augmented Generation Workbench for Legal AI UX Research.

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Builder

harvard-lil

harvard-lil • individual

Stars

136

Using upstream star count

Forks

Using upstream fork count

Open Issues

Activity Score

0/100

0 commits in 30d

Created

Jan 22, 2024

Project creation date

README Summary

OLAW is a Tool-Based Retrieval Augmented Generation (RAG) workbench designed for legal AI user experience research. It combines AI capabilities with legal APIs to provide a comprehensive platform for exploring and testing legal AI applications. The tool serves as a research environment for studying how AI can be integrated into legal workflows and user interfaces.

AI Dev Skills

Unmapped

Retrieval-Augmented GenerationTool-based AI SystemsLegal Document ProcessingAPI DevelopmentUser Experience Research

Taxonomy

AI Trends

Tool-based AI Retrieval-Augmented Generation Domain-specific AI Applications

Deployment Context

Self-hosted Cloud API

Industries

Legal Tech

Modalities

Text

Skill Areas

Retrieval-Augmented Generation Tool-based AI Systems Legal Document Processing API Development User Experience Research

Use Cases

Legal Document Question Answering AI Legal Research Experimentation Legal AI UX Testing

Recent Activity

Updated 1 years ago

7 Days

30 Days

90 Days

Quality

research

Quality: medium
Maturity: research

PM Skills

Developer Platform

Languages

JavaScript100.0%

Timeline

Project created: Jan 22, 2024
Forked: Mar 23, 2026
Your last push: 1 years ago
Upstream last push: 1 years ago
Tracked since: Oct 29, 2024

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