Our unique technology - a result of over 15 years of industry-leading innovation - cleanses, aggregates and harmonises real-world clinical data using open standards, fit-for-purpose AI technologies, data warehousing and analytics; streamlining the process of turning healthcare data into actionable evidence


Leaders in digital healthcare

We are built by experts in digital health, and know how to cut through the complexity to support your innovations today, and in the future.

Our Team


Our proprietary algorithms include machine learning and natural language processing to transform data from any format or source into OMOP with over 99% reliability.


Our data warehousing is purpose built for healthcare interoperability. Transformed data is organised, de-identified, and appropriately governed and secured to run applications, at scale.


Designed for use by clinicians and researchers, our low-code, self-serve analytics toolbox enables insights and evidence to be extracted from the data with ease.A RESTful API provides flexibility by allowing any third party tool to be integrated.


Medical research and innovation require collaboration to ensure the reliability of clinical evidence. EvidenceHub is our global research collaboration and translation platform enabling real time replication without sharing data.


We exist to provide healthier data for you to make better informed decisions. And because healthcare is complex, our solutions are designed to adapt and scale accordingly.

Quality and Safety

An essential part of improving the safety and quality of care is analysing clinical performance across the organisation. By consolidating data on operational performance, clinical outcomes and patient experience, our technology equips healthcare organisations with the insights to:

  • Monitor compliance
  • Automate clinical audits
  • Reduce waste
  • Measure adherence to guidelines and standards of care
  • Compare efficacy and risk of various clinical care pathways
Case Study

Population Health

Healthcare data is often fragmented and is a barrier to developing evidence based policy. Our technology unlocks your longitudinal health data and incorporates patient generated data to: 

  • Design more effective healthcare delivery services
  • Identify gaps in care
  • Reduce chronic disease burden
  • Reduce costs by using evidence based incentives

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Research & Innovation

Some of the most time-consuming and difficult tasks in developing a new intervention or policy center on data. AI can help solve many problems in healthcare, but it first needs to be trained to high-quality data. Our technology rapidly cleanses and standardises data:

  • Reducing the time and cost to train and prove healthcare AI
  • Enabling study replication 
  • Facilitating collaboration without sharing data
  • Reducing translational medicine timeframes from years to months

Case Study

Learning Health Systems

A learning health system (LHS), a cornerstone of digital healthcare, continuously measures, analyzes and rapidly implements processes that produce better health outcomes, at reduced costs and with fewer risks to patient safety. Our technology supports the implementation of a LHS by delivering the required evidence, to the right people, at the right time.

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