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Client WorkHealthTech & Data

Healthcare Data Infrastructure Platform

A healthcare-native data platform designed to help teams ingest, understand, transform and move complex healthcare information.

The platform supported technical data workflows while aiming to make them usable for both highly technical and operational users.

Client identity withheld due to confidentiality.

Context — fragmented healthcare data

  • Clinical systems
  • Insurance systems
  • Legacy databases
  • EDI files & HL7 messages
  • Nested JSON & spreadsheets
  • Custom formats
  • FHIR-based systems

The challenge — simplify complex processes

  • Data ingestion & source connection
  • File & layout understanding
  • Mapping & transformation
  • Profiling & validation
  • De-identification & deduplication
  • Pipeline execution & output
  • Project & team administration

Users

  • Data engineers
  • Healthcare data teams
  • Analysts
  • Implementation specialists
  • System administrators
  • Project managers
  • Compliance-related users

Core modules

  • Projects & connectors
  • Layouts & sublayouts
  • Mapper & profiler
  • Pipelines
  • Writer / loading
  • Dashboard
  • Team management & administration
  • Settings

Key capabilities

AI-driven auto mapping

Uses AI to help map fields across systems and reduce manual work.

Data pipeline

Supports extraction, transformation and loading workflows.

Profiler

Analyses data structure and quality.

De-identification & re-identification

Removes personal identifiers while preserving integrity, with controlled re-identification where permitted.

Deduplication & FHIR conversion

Identifies duplicate records and transforms information into healthcare interoperability formats.

Design approach

Visual workflow

Complex pipelines should be visually understandable.

Progressive technical detail

Users should see enough to decide without being overwhelmed.

Clear validation

Errors, warnings and quality issues should be visible and actionable.

Project-based organisation

Workflows organised into projects with clear ownership and status.

Complexity

  • Healthcare data standards
  • Sensitive information
  • Technical & operational users
  • Multi-step pipelines
  • Low-code workflow design
  • Multi-tenant architecture
  • Data quality & privacy requirements

What this project demonstrates

Enterprise SaaS designHealthcare data workflowsTechnical UXData-heavy productsLow-code systemsComplex information architecture

Selected project details have been anonymized due to client confidentiality. No client names, logos or private information are shown.

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