AI case study

Latent HealthClinical chart review

$98/hr training costs blocked custom AI. Moving to bare-metal GPUs cut costs 7x, enabling models that slashed chart review times by 80%.

Published|4 months ago

Key results

Faster Review Times
75%
Review Time Per Auth
5 mins
vs 25 minutes
Clinical QA Accuracy
97%

Result highlights

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The story

Context

A healthcare technology company automates critical workflows for 25 major health systems, including UCSF and Yale, helping pharmacists review patient charts for medication approvals.

Challenge

Training high-accuracy clinical models on AWS H100 instances cost an unsustainable $98 per hour. Additionally, traditional cloud services introduced...

Solution
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Scope & timeline

  • 2-3x faster model experimentation

Quotes

The company

Latent Health logo

Latent Health

latenthealth.com

AI platform for medication access and prior authorization in health systems.

IndustryHealthcare Providers
LocationNew York, NY, USA
Employees1-10
Founded2023

The AI provider

Together AI logo

Together AI

www.together.ai

AI-native cloud platform for training, fine-tuning, and deploying open-source models.

IndustryTechnology
LocationSan Francisco, CA, USA
Employees51-250
Founded2022

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