Xtasis offers a cloud‑native AI platform that automates the entire medical imaging workflow, from HIPAA‑compliant de‑identification and collaborative annotation to real‑time diagnostic inference and surgical scheduling. The system integrates with existing PACS, runs sub‑second pipelines at petabyte scale on AWS, Azure, and GCP, and provides customizable dashboards for cardiovascular analysis and resource optimization. It is designed for hospitals, health systems, and research institutions seeking secure, scalable AI tools to accelerate diagnostics and operational efficiency.
Funding
Funding not disclosed
Founders
Product
Problem
Healthcare and research organizations must manage massive volumes of medical imaging and clinical data while ensuring privacy, regulatory compliance, and efficient analysis. Traditional workflows are fragmented, slow, and often require manual annotation and scheduling, limiting the speed of diagnosis and research insights.
Solution
Xtasis provides a cloud‑native, end‑to‑end AI platform that automates the full data journey from ingestion to actionable output. The system first de‑identifies images and text to meet HIPAA and GDPR standards, then offers customizable annotation tools for building high‑quality training sets. Integrated AI models deliver real‑time cardiovascular diagnostics, including 3D vessel reconstruction and lesion detection, with seamless PACS integration. An AI‑driven scheduling engine optimizes operating‑room resources based on diagnostic findings, patient acuity, and surgeon availability. All components run on sub‑second pipelines across AWS, Azure, and GCP, handling petabyte‑scale workloads with support from NVIDIA, AWS, and Microsoft partners.
Target Audience
Primary customers are hospitals, health systems, and academic research groups that need secure, scalable AI tools for imaging diagnostics, workflow automation, and surgical scheduling.
Features
- Automated PHI removal from medical images and clinical notes with configurable retention policies
- Customizable labeling schemas and collaborative review workflows for building training corpora
- AI‑powered diagnostic dashboards offering 3D vessel reconstruction, measurements, and lesion detection overlays
- Seamless integration with existing PACS systems for direct image access
- Real‑time and asynchronous AI pipelines delivering sub‑second inference at petabyte scale
- Cloud‑native deployment on AWS, Azure, and GCP with built‑in compliance and security controls
- Intelligent OR scheduling algorithm that balances resource availability, surgeon expertise, and patient priority
- Export of annotated data and analysis results in JSON/CSV formats for downstream research use