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Swast‑AI is a dedicated division of Swastome focused on creating AI‑driven analytical pipelines, advanced neural networks, and next‑generation diagnostic tools. Its work spans medical image analysis, temporal patient data interpretation, healthcare support system management, and large‑scale omics data integration. By building fast, robust, and high‑throughput analysis pipelines, Swast‑AI assists hospitals, clinicians, and healthcare professionals to make quicker, more accurate decisions and improve patient outcomes.
How Swast‑AI is Turning Clinical Data into AI-Powered Clinical Decision Support System?
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Algorithms & Neural Networks for Diagnosis: AI models tuned to interpret medical imaging (X‑rays, CT, MRI), EHR, omics, and real‑time IoMT data.
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High‑throughput Data‑analysis Pipelines: Optimized to process large datasets like medical images, metadata, genomic/omics data in real time with speed and accuracy.
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Custom Software & Databases: Integrated tools to unify heterogeneous datasets (imaging, EHR, multi‑omics) into actionable clinical decision support.
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Real‑Time Analytics Support Systems: For immediate feed‑in and outputs in clinical workflows: automated triage, prediction, cohort mining.
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Tools for Developing Countries: Lightweight, locally deployable, with modular infrastructure support—ideal where cloud or compute resources are limited.
Ongoing Projects
Building Healthcare Management Solutions for Healthcare
(2024 - Present)
AI‑Driven Health Monitoring from Smart Wearables (2024 - Presnet)
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Why Swast‑AI Matters?
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Harnessing India’s Data Volume: India generates staggering amounts of healthcare data every day (imaging, EHR, mobile health, genomics), yet lacks the scalable AI systems to unlock insights. Swasth‑AI transforms raw data into actionable diagnostics, predictive signals, and analytics dashboards.
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Building Local Expertise & Resilience: Rather than depending on foreign platforms, Swasth‑AI enables in‑country algorithm development, capacity building, and domain‑specific tuning to strengthening local healthcare ecosystems.
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End‑to‑End Real‑Time Capability: From high‑throughput pipeline architecture to AI inference supporting clinical decisions in near real time.
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Interoperability & Federated Insights: Designed to work with national initiatives (e.g. Ayushman Bharat Digital Mission), interoperability protocols, and federated learning; enabling data sharing and learning across institutions securely.
