01  /  EXECUTIVE SUMMARY: Proprietary AI in BigLaw is a hybrid model, not a from-scratch build

 “Proprietary AI” at large law firms usually does not describe a foundation model trained from scratch. The dominant architecture across the market is hybrid, combining four elements: licensed foundation-model capability from providers such as OpenAI, Anthropic or Microsoft; specialist legal applications such as Harvey, Legora, Spellbook or DeepJudge; a firm-built layer covering document retrieval, permissions, prompts, workflows and evaluations; and lawyers who own validation, risk and workflow design.

This hybrid approach is also the most defensible one for a firm operating at Kirkland's scale. Training a fully proprietary model is expensive, difficult to keep current against fast-moving foundation-model providers, and unlikely to outperform specialist vendors across every practice-area workflow. The advantage a large firm can sustain over time is its private precedent base, its workflow design, its security controls and its adoption data, not the underlying language model.