100% synthetic. By construction.
Eve-Genesis (Law Edition) is the proprietary synthetic reasoning corpus that fine-tunes the Phi-4-derived legal reasoner inside Eve-Legal F5/reasoner. Every example, every reasoning trace, every fact pattern was constructed for training — not extracted from a customer matter, not scraped from a court record. Your firm’s data is never used to train any model. Foundation or fine-tuned. Ours or anyone else’s.
The case for synthetic data in legal reasoning.
Privilege survives. A model fine-tuned on synthetic legal reasoning never sees a real client’s confidential matter, never memorises a real attorney’s work product, never risks reproducing a real privileged exchange. The attorney-client relationship is intact at the training layer, not just at the inference layer.
Quality is engineered, not scraped. Eve-Genesis examples are designed for the specific reasoning patterns the production pipeline runs — four-pass demand-letter construction, multi-provider medical chronology, jurisdiction-aware damages modeling. Coverage is engineered, not accidental.
Bias is auditable. When the corpus is constructed, the demographics, jurisdictions, injury types, and case shapes that compose it are documented. We know what the reasoner has been shown. We know what it has not been shown.
Coverage scales with the editions. Eve-Genesis is a family of editions — Law, Education, Clinical, Theology — each calibrated for the workload of its product. The Law Edition itself extends as new editions ship: WC, MM, MT, IB, EL each contribute their own reasoning patterns back into the corpus.
Synthetic doesn’t mean fictional.
Eve-Genesis is not a stack of made-up cases. The reasoning patterns are real — they are the patterns senior litigators apply when they read a record, decide a demand, or prepare an expert. What is constructed is the example: the fact pattern, the matter shape, the procedural posture.
Legal authorities — the actual case law cited in production demand letters — are not in Eve-Genesis. They are resolved at inference time against CourtListener, the public legal-research corpus, by the four-pass pipeline’s citation verifier.
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