$98/hr training costs blocked custom AI. Moving to bare-metal GPUs cut costs 7x, enabling models that slashed chart review times by 80%.
A healthcare technology company automates critical workflows for 25 major health systems, including UCSF and Yale, helping pharmacists review patient charts for medication approvals.
Training high-accuracy clinical models on AWS H100 instances cost an unsustainable $98 per hour. Additionally, traditional cloud services introduced...
“Together Instant Clusters enabled us to build the intelligence backbone that's core to our business. Our partners will accept nothing less than state of the art so it is critical that we distill clinical nuance and the latest compendia into our models. Together AI's infrastructure gives us both the performance and experimentation freedom to make that happen.”
AI platform for medication access and prior authorization in health systems.
AI-native cloud platform for training, fine-tuning, and deploying open-source models.
Latent Health's Clinical chart review is part of this use case:
Related implementations across industries and use cases
Long therapy logs caused training failures. A new pipeline handles extended context, enabling 3-7x more weekly model updates.
Abstractors spent 6 hours hunting details per complex case. Now, they validate AI findings in 90 mins, saving 6,000 annual labor hours.
31 providers spent weekends dictating charts for 100k annual visits. Now, AI drafts notes during exams, ending after-hours paperwork.
Long therapy logs caused training failures. A new pipeline handles extended context, enabling 3-7x more weekly model updates.
Debugging acute-care AI bottlenecked a small engineering team. Now, internal AI agents autonomously query logs to investigate bugs.
Typing notes broke eye contact and caused late nights. Now, AI drafts records from spoken exam findings so vets stay present.
Manual scheduling took 3 days, slowing hiring. An AI agent now screens and books interviews in 29 minutes, doubling scheduled volume.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.
$98/hr training costs blocked custom AI. Moving to bare-metal GPUs cut costs 7x, enabling models that slashed chart review times by 80%.
A healthcare technology company automates critical workflows for 25 major health systems, including UCSF and Yale, helping pharmacists review patient charts for medication approvals.
Training high-accuracy clinical models on AWS H100 instances cost an unsustainable $98 per hour. Additionally, traditional cloud services introduced...
“Together Instant Clusters enabled us to build the intelligence backbone that's core to our business. Our partners will accept nothing less than state of the art so it is critical that we distill clinical nuance and the latest compendia into our models. Together AI's infrastructure gives us both the performance and experimentation freedom to make that happen.”
AI platform for medication access and prior authorization in health systems.
AI-native cloud platform for training, fine-tuning, and deploying open-source models.
Latent Health's Clinical chart review is part of this use case:
Related implementations across industries and use cases
Long therapy logs caused training failures. A new pipeline handles extended context, enabling 3-7x more weekly model updates.
Abstractors spent 6 hours hunting details per complex case. Now, they validate AI findings in 90 mins, saving 6,000 annual labor hours.
31 providers spent weekends dictating charts for 100k annual visits. Now, AI drafts notes during exams, ending after-hours paperwork.
Long therapy logs caused training failures. A new pipeline handles extended context, enabling 3-7x more weekly model updates.
Debugging acute-care AI bottlenecked a small engineering team. Now, internal AI agents autonomously query logs to investigate bugs.
Typing notes broke eye contact and caused late nights. Now, AI drafts records from spoken exam findings so vets stay present.
Manual scheduling took 3 days, slowing hiring. An AI agent now screens and books interviews in 29 minutes, doubling scheduled volume.
A 200% yearly data expansion bottlenecked global operations. Now, AI accelerates coding, drafts recipe cards, and resolves inquiries.
Moderation couldn't keep pace with 600M users. AI agents now filter toxicity while models recognize 2.5B objects to refine search.