
Intelligent Data Platform

Key features for Intelligent Data Platform

Integration Engine
Built to support Interoperability, IDP can consume a diverse set of Healthcare data (including HL7, FHIR) to create customized outcome-based workflows.

Unified Data Layer
Combination of EMR/HMIS or clinical system data presented as a single source of prepared, cleansed, and structured unified data for improved efficiency and faster insights.

AI-as-a-Service
Allows providers to experiment with AI to detect and diagnose preventable harms without large initial investment and with low risk.

MLOps
A platform for collaboration and communication between data scientists and operations professionals to help manage production ML.
Transform Your Data Pipeline with our Intelligent Data Platform
Healthcare Integration Engine
- HL7 interface development for inbound/outbound messages in an EMR
- Development of interfaces empowering customer EHRs to communicate with external systems (clinical, financial and pharmacy)
- Enable data to be routed to many sources with help of HealthCare Event builder leveraging all open source components (RedHat – Intelligent Data Platform)


Unified Data Layer
- Access complete patient records and improve clinical decision-making.
- Provide personalized access to the unified patient record at the point of care for both physicians and patients.
- Provide Standardize data models like UDMH and custom build to align with business needs.
- Generate insights as per business needs, with a self-service data catalog with enriched data set.
- Provide the right data, at the right time, in the right modality with a unified data layer.
AI-As A Service
- Assist data-scientists to build better machine learning models faster and take them from prototype to enterprise-scale deployment in a few clicks.
- Accelerate Data scientists to start with already built-in data models providing a self-service experience.
- Build advanced AI/ML pipelines and bring the power of DevOps with built-in MLOps workflows.
- Develop specialized and bespoke analytics use cases for different stakeholders .i.e. CXOs, research teams, data scientists, analysts, clinicians, etc.

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Success Stories
Technology Stack
