$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.
Related implementations across industries and use cases
Self-hosting GPUs capped training at weekly runs. A serverless shift cut costs 3x and enabled daily iteration for 87% accuracy.
Long therapy logs caused training failures. A new pipeline handles extended context, enabling 3-7x more weekly model updates.
Complexity slowed AI adoption. Intelligent orchestration on GKE now deploys models in minutes, allowing clients to iterate 90% faster.
Long therapy logs caused training failures. A new pipeline handles extended context, enabling 3-7x more weekly model updates.
Complexity slowed AI adoption. Intelligent orchestration on GKE now deploys models in minutes, allowing clients to iterate 90% faster.
Clinicians spent evenings buried in manual notes. AI now generates charts from audio, scaling from primary care to oncology.
Doctors spent 3 hours nightly reviewing complex records. Claude now synthesizes 300-page referrals into instant patient histories.
Hundreds of pages per board book slowed director prep. Now, isolated AI securely condenses sensitive materials into actionable briefs.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.
$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.
Related implementations across industries and use cases
Self-hosting GPUs capped training at weekly runs. A serverless shift cut costs 3x and enabled daily iteration for 87% accuracy.
Long therapy logs caused training failures. A new pipeline handles extended context, enabling 3-7x more weekly model updates.
Complexity slowed AI adoption. Intelligent orchestration on GKE now deploys models in minutes, allowing clients to iterate 90% faster.
Long therapy logs caused training failures. A new pipeline handles extended context, enabling 3-7x more weekly model updates.
Complexity slowed AI adoption. Intelligent orchestration on GKE now deploys models in minutes, allowing clients to iterate 90% faster.
Clinicians spent evenings buried in manual notes. AI now generates charts from audio, scaling from primary care to oncology.
Doctors spent 3 hours nightly reviewing complex records. Claude now synthesizes 300-page referrals into instant patient histories.
Hundreds of pages per board book slowed director prep. Now, isolated AI securely condenses sensitive materials into actionable briefs.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.