Objective Performance Scores
GenieAI performs regular internal testing aimed at learning what drives great output quality, pushing the boundaries of legal accuracy and benchmarking the platform's capabilities against other AI providers.
Below is the latest test data, obtained through fair and objective testing involving an analysis of 65 simulated documents across a broad variety of document types.
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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.
- Board authorized 3 strategic partnerships for European expansion
- NexGen: solid-state battery supply, EUR 2.5B+ annual commitment by 2028
- AutonomX: autonomous driving for EU market, EUR 250M+ total investment
- NordischEM: contract manufacturing, 100,000+ vehicles/year capacity
- Key risks: single-source dependency, quality issues, regulatory compliance
- Board considering QuantumFlux acquisition to reduce NexGen dependency
- Type Approval issues could impact EUR 189M–567M in revenue
- Strategic objective: 20M vehicles annually by 2030 (Master Plan Part 3)
Overall Scores
15 legal quality metrics, each scored 1–10, max 150
ChatGPT — Critical Gaps
The six largest scoring deficits vs GenieAI reveal fundamental coverage failures
Where GenieAI Leads over CoWork
Advantages driven by RAG-based deep document mining
Where CoWork Leads over GenieAI
Structural and clause-level depth advantages
What ChatGPT Does Differently
Financial modeling extrapolations — consulting-style what-if scenarios, not legal analysis
System Profiles
GenieAI
A step-change in legal AI. Covers all 8 key points, 5 partnerships (incl. Panasonic historical), both regulatory workstreams, all 4 board meetings. 10-point cross-cutting risk analysis identifies systemic patterns — 12× concentration escalation, board authorization deviations, Tesla's knowledge gap — that no other system surfaced. Seven perfect 10/10 scores.
A+ · Litigation-grade + Board-readyCoWork
Competent legal risk assessment with the broadest clause-level analysis across all 4 contracts (MSA, JDA, MLA, NDA, QSM, EU Reg). Three-tier action plan with named suppliers, acquisition strategies, and dual-signature protocol. Honest about Tesla's own procedural failings. Gap: document mining depth — whistleblower evidence, insolvency trajectory, cascading chains.
B+ · Action-oriented + StructuredChatGPT
Operates as financial consulting, not legal analysis. Introduces novel what-if scenarios (lithium corridor, FSD monetization) but on incorrect base figures (EUR 45K ASP vs actual EUR 28.5K–39.5K). Misses QuantumFlux entirely, has zero regulatory coverage, covers only 2/8 key points, and presents binary dispute framing with no probability assessment.
F · Financial modeling onlyBottom Line
The three-way comparison reveals a clear tier structure. GenieAI (A+, 90%) leads in 11 of 15 metrics through RAG-powered document access delivering both breadth and depth. CoWork (B+, 79.3%) produces a competent legal risk assessment with the strongest clause-level analysis and most structured recommendations.
ChatGPT (F, 37.3%) fails the benchmark fundamentally — missing QuantumFlux entirely, zero regulatory compliance coverage, only 2 of 8 expected key points, and speculative extrapolations built on incorrect base figures presented as quasi-authoritative projections. Its strength — financial what-if modeling — is a different discipline than what the question asked for.
The 79-point gap between GenieAI and ChatGPT, and the 63-point gap between CoWork and ChatGPT, demonstrate that access to source documents is not merely helpful but dispositive for legal quality work product.
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