Why Harvey is multi-model by design
Harvey harnesses multiple frontier models to maximize performance, ensure continuity, and put control in customers’ hands.
Last year, Harvey went multi-model, expanding its platform to incorporate leading foundation models from Anthropic, Google DeepMind, and OpenAI. That decision was a deliberate architectural commitment — one that has only become more consequential as the AI landscape has evolved.
Being multi-model creates both opportunity and resilience. The opportunity is straightforward: Different models have different strengths and weaknesses, and a platform that harnesses all of them delivers better outcomes than one constrained to a single provider. Resilience has become equally important. Enterprise AI adoption introduces a category of risk that most organizations are only beginning to reckon with — model provider risk. When a provider experiences a disruption, whether operational, regulatory, or geopolitical, organizations that depend exclusively on that provider face an immediate question: What now?
Harvey’s customers never have to ask that question. We built a multi-model platform because doing so is the only responsible way to serve organizations whose work demands the best available intelligence, uninterrupted continuity, and full control over their technology stack. That commitment rests on three pillars: quality, reliability, and choice.
To read the article in full, click here.
