Enigma Health inks partnerships to boost healthcare efficiency with AI.
Enigma Health — a spinoff from the SingHealth Duke-NUS Academic Medical Centre — has signed two Memoranda of Understanding (MOUs) to expand its flagship product's reach and capabilities.
Developed by a team of clinicians and AI scientists, Enigma is a healthcare agentic artificial intelligence (AI) platform designed for healthcare. It focuses on workflow optimisation by streamlining data-intensive and time-consuming processes while maintaining strong data security and regulatory compliance.
The first MOU, signed with Roche, outlines a joint effort to explore advanced AI and digital technologies aimed at accelerating clinical trial recruitment, improving market access, and strengthening business intelligence.
As part of the partnership, Enigma Health’s sovereign AI workflow platform will be integrated into Roche’s business processes, supporting its commitment to driving innovation and improving patient outcomes.
Under the second MOU, Enigma Health’s proprietary small language model will be integrated into ST Engineering’s AGIL Genie Studio platform, enabling non-technical users to more easily develop AI-powered healthcare applications.
This collaboration combines SingHealth’s clinical expertise with ST Engineering’s strengths in hospital command centre data management, creating a strong synergy to improve healthcare operations, decision-making, and AI-driven clinical trials.
Looking ahead, Enigma Health will partner with Synapxe to scale the deployment of its flagship platform across the SingHealth network.
The company also plans to deepen its technical capabilities to optimise clinical workflows, financial operations, research trials, and broader administrative and business intelligence functions.
In parallel, Enigma Health is expanding its regional footprint through partnerships with pharmaceutical firms and both public and private healthcare providers across Southeast Asia.
Pilot trials of Enigma Enigma has already been piloted across SingHealth institutions. At the Singapore National Eye Centre (SNEC), the platform analysed data points from more than 7,000 cataract surgeries and 1.2 million data points between January and June 2024.
As a result, audit time plunged by 90%, from 528 hours to just seven. Clinical audits (which are mandatory for every surgery to ensure patient safety and compliance) were completed faster and with reduced risk of human error. By automating these processes, Enigma freed up clinicians to focus more on patient care rather than paperwork.
At KK Women’s and Children’s Hospital (KKH) and the SingHealth Duke-NUS Institute of Precision Medicine (PRISM), Enigma was used to pilot an automated system for extracting lab data from PDF reports.
The tool automates the retrieval, extraction, and conversion of unstructured data from PDFs into structured tabular formats, using ambient search and full-report extraction. The automation was tailored to user preference to ensure precise data capture that is optimised for integration with electronic health records and downstream analytics.
Consequently, the processing time per report dropped from 30 minutes to mere seconds, a 400-fold improvement. Over 1,400 reports could be processed and organised in about an hour, a task that would have previously taken weeks.
The automation freed genetic counsellors and analysts from labour-intensive manual tasks, enabling them to focus on direct patient care and deeper data analysis.
Clinical workflows and improved data availability also saw enhanced efficiency for research and precision medicine initiatives.