Health Care
Bring data privacy and AI efficiency together for better patient outcomes and reduced cost.
Medical records are an incredibly useful group of artifacts for AI models to operate against, and include a range of data modalities that encompass text, imaging, audio notes and others.
AI models are increasingly being used to analyze medical records for conflicting or confirming diagnoses, processing high-resolution imaging detect anomalies, predict disease progression, and assist in diagnostics, or correlating audio notes with written notes or imaging results .
Challenges
● Data Privacy & Compliance: Patient data must adhere to strict governance policies (HIPAA, GDPR) to ensure privacy and security.
● High Operating Costs: Unoptimized data modalities, and high-resolution medical images in particular consume large amounts of AI resources, making processing costly.
● Concurrency & Latency: Hospitals and research institutions often process records from multiple departments simultaneously, leading to bottlenecks and resource exhaustion in AI use.
How Constellation AI Helps
1. Enterprise Security First Architecture
Designed from the ground up by experienced Enterprise engineers based on the time-tested STRIDE security model, our platform security architecture works to keep your data and workloads safe. Our deployment model also does not require any training or inference data transit outside of your already-compliant environments.
Teams may secure data at rest and in transit with your own keys (BYOK), or optionally invoke our quantum-proof encryption service included in the platform. Each platform deployment or update also creates an automated STRIDE analysis and report of the platform configuration to further ensure a secure operating environment.
2. Automated Data Governance
We want fast, better, cheaper health care, but not at the expense of our privacy.
Our data pipeline HIPAA compliance services identify in-scope data, apply smart-contract-based tagging, and ensure protection of patient privacy as data flows through the platform. For compliance and auditing, the platform creates immutable logs of each discrete piece of data, and what happened to it during processing or transit as well as traditional strict access controls and operational logs.
3. High Performance Concurrency and Multi-Cloud Load Balancing
Time is health.
With our concurrent data ingestion, agentic routing and proprietary caching architecture, the Constellation AI platform eliminates traditional data bottlenecks while maintaining cost-effectiveness. We also make it fast and easy to set up secure, private connections between on-prem or other public cloud data centers for extensible multi-location data routing to the platform.
4. Cost Effective AI at Scale
Our unique layer-wise adaptive quantization services work across multi-modal data types, reducing the amount of data AI models need to produce accurate results by up to 40% in our testing. We also leverage hardware-aware resource orchestration and optimization balanced with data prioritization and model performance tracking.
The event-driven architecture enables rapid scale-out and scale-in activities based on data volumes and resource constraints. The platform orchestration constantly monitors and learns from the environment resources, their energy consumption and the downstream quantization impacts of data on model performance, automatically backing off or changing quantization types when model performance degrades, ensuring the optimal balance of cost and accuracy in AI model operations.
Business Impact
Hospitals and research institutions benefit from reduced data processing and storage costs, faster AI-driven diagnostics, and improved regulatory compliance, ultimately leading to better patient outcomes and operational efficiencies.