Heidi x Fireworks: Bridging the Gap in Frontier Model Performance

Heidi Health has partnered with Fireworks to enhance its ambient AI scribe technology, which transcribes clinician-patient encounters into professional clinical notes, significantly improving productivity by saving clinicians up to two hours per day. The collaboration aims to achieve superior performance compared to proprietary frontier models by transitioning from closed to open models, resulting in better control, performance, and cost savings. Fireworks' expertise in model fine-tuning and inference optimization has led to breakthroughs in supervised and reinforcement fine-tuning, allowing Heidi's model to outperform existing tiers in internal evaluations. The success of this partnership hinges on maintaining high data quality through aggressive filtering and utilizing larger batch sizes to stabilize training, facilitated by Fireworks AI's support for gradient accumulation. This approach demonstrates that open models can rival frontier models when subjected to rigorous Direct Preference Optimization (DPO), underscoring the importance of synthetic data and pre-evaluation strategies in enhancing AI model performance.

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