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Current company Indoqubix Cloudtech
IT Services and IT Consulting · 17 employees · Founded 2011 · Noida, Uttar Pradesh, India
Indoqubix Cloudtech Pvt Ltd accelerates business innovation through AI-powered healthcare technology, intelligent cloud services, and comprehensive digital transformation solutions. With 50+ years of collective experience and 100+ successful projects across healthcare, automotive, manufacturing, and energy sectors, we transform industries through future-ready platforms. AI-Powered Healthcare Solutions (QubixCare) Our flagship healthcare platform delivers measurable outcomes: 65% reduction in patient wait times through real-time FHIR/HL7 interoperability, explainable AI, and production-grade MLOps. HIPAA/HITRUST-ready with federated privacy-preserving learning, unified patient temporal graphs, and pluggable risk engines that support diverse clinical models. Our platform features adaptive scheduling with closed-loop outcomes, generative AI safety guardrails, and real-time device/IoT integration. Smart Energy Management (QubixLink) Multi-vendor integration platform connecting smart prepaid electricity meters, existing energy management systems, and IoT devices for intelligent energy optimization and automation. Data Analytics Platform (Formlytic) AI-powered assessments delivering enhanced analytics and actionable reporting for data-driven decision making across industries. 24x7 Cloud DevOps & Managed Services Cloud-agnostic GitOps pipelines across AWS, Azure, and GCP with DevSecOps automation, unified observability, self-healing infrastructure, and sub-5-minute incident detection. ISO 27001 and ISO 27701 certified for enterprise compliance and data security. Our Differentiators: 91%+ client retention rate with multi-year renewals across 4 geographies and 5+ industries 50+ engineers and technical specialists at our Noida development center Proven expertise: Healthcare (75%), Automotive (15%), Energy (5%), Education. Standardized DMLIF framework for zero-loss data migration and legacy integration Hybrid pricing model balancing flexibility with predictability