Why Harvey is Multi-Model by Design

This post details the architectural commitment to a multi-model AI platform, emphasizing the strategic decision to integrate multiple frontier models from different providers (Anthropic, Google DeepMind, OpenAI). It explains the rationale behind this choice, focusing on three pillars: quality (matching models to specific tasks based on their strengths), reliability (ensuring service continuity by routing work to alternative models during provider disruptions or outages), and choice (allowing customers to control which models are available and to select preferred models). The post also touches on operational aspects like regional availability, data sovereignty, and enforcing security/compliance standards across providers. It mentions continuous evaluation through BigLaw Bench and expert preference testing as methods for model selection.