GenieAI Benchmarking Program
How GenieAI compares to the frontier of legal AI
Our engineering team publishes structured head-to-head benchmarks against leading LLMs and legal-AI products. Each report scores GenieAI and a comparator across legal-quality dimensions using realistic legal scenarios - full prompts, full rationale, full data.
GenieAI vs Claude CoWork - Commercial contract review
A 10-dimension head-to-head on a real commercial supply agreement: clause coverage, IP risk classification, fallback drafting, citations, and negotiation strategy.
Verdict GenieAI scores 88/100 vs Claude CoWork's 56/100 - a 32-point lead driven by IP depth, fallback drafting and citations.
- Fallback / redline language +8
- Consultant-side perspective +6
- Legal authority citations +5
- 18 Feb 2026
GenieAI vs Claude (Tesla case)
A 15-metric structured comparison on a complex multi-jurisdiction regulatory scenario: Tesla's European factory expansion across product safety, automotive type approval, GDPR, antitrust, environmental and trade dimensions.
GenieAI 82% Claude (Sonnet) 48% - 17 Feb 2026
GenieAI vs CoWork vs ChatGPT
A 15-metric evaluation of AI-generated legal risk assessments across 65 source documents in a simulated Tesla European expansion case.
Read full benchmark
Realistic legal scenarios
Each benchmark uses a representative legal task - drafting, redlining, IP review, regulatory analysis - written by the same kind of practitioner Genie is built for.
Multi-dimensional scoring
Outputs are scored across 10-15 dimensions covering substance (clause coverage, IP depth, risk classification), structure (actionability, escalation framework) and authority (legal citations, jurisdiction-specific reasoning).
Open prompts, open rationale
Where the format allows, we publish the original prompt, the expected key points, and per-metric rationale so any reader can reproduce or critique the comparison themselves.
Versioned + dated
Frontier models change weekly. Every benchmark records the exact systems and dates compared, and we re-run against meaningfully updated competitors rather than burying old results.