What is the name of your organization?
AlemHealth
What is the name of your solution?
AlemHealth Connect
Provide a one-line summary or tagline for your solution.
The data rails that unlock global access to affordable, AI‑powered radiology diagnostics.
In what city, town, or region is your solution team headquartered?
Singapore
In what country is your solution team headquartered?
Singapore
What type of organization is your solution team?
For-profit, including B-Corp or similar models
Film your elevator pitch.
What specific problem are you solving?
Diagnostic imaging underpins 70% of clinical decisions, yet 4.7 billion people still wait days or travel hundreds of miles for a basic X‑ray or CT result. The root cause is not just too few scanners and radiologists; it is that existing devices sit idle more than 60% of the time and radiologist output is throttled by manual, paper‑based workflows.
Proven AI algorithms could read images, draft reports, and flag quality issues in seconds, but they are marooned in high‑income hospitals because clinics in low‑resource settings lack secure, low‑bandwidth “data rails” to move images to the cloud, run AI, and return structured results. Without those rails, costly machines collect dust: our field audits show CT and MRI units in sub‑Saharan Africa run barely four hours a day, while some mammography systems are used once or twice daily. Idle equipment still incurs financing, depreciation, and maintenance costs, so facilities raise fees and price out the poor; diagnostic delays meanwhile push cancers to stage III/IV and allow tuberculosis to spread unchecked.
Lowering reporting costs and raising utilisation of existing scanners is the only scalable way to bend the cost curve of diagnostics downward while improving care quality.
What is your solution?
AlemHealth turns any diagnostic imaging device into a smart, connected scanner that boosts radiologist efficiency and maximizes scanner utilisation.
Our plug and play AlemBox device connects to X-rays, CT, MRI, and ultrasound machines, securely compresses and uploads encrypted images. It then routes those images to AI tools and remote radiologists in the cloud or at other facilities. Our AI auto-selects the correct templates, drafts reports from shorthand notes or dictation, tags ICD-10 codes, and even runs quality control on the reports seamlessly, enabling radiologists to work 2× faster than before, from anywhere.
To increase scanner utilisation, we provide facilities with detailed analytics on their device usage, down to body part and protocol, so they can identify areas of improvement and benchmark against other facilities. We also help fill unused capacity by connecting centres to government and donor funded screening programs (e.g., TB, breast cancer), and a diaspora-facing portal for families abroad to book scans locally.
This combination of smarter workflows and higher throughput lowers per study costs, reduces idle time, and makes quality diagnostics accessible without new capital investments.
Who does your solution serve, and in what ways will the solution impact their lives?
Our solution directly improves diagnostic access for patients in some of the world’s most underserved regions. Our platform has supported millions of patients across Nigeria, Somalia, Ghana, the Philippines, Iraq, Yemen, Afghanistan, and other low-resource and conflict settings where access to timely imaging is limited or nonexistent. In these settings, imaging equipment may exist, but a lack of radiologists, poor connectivity, and expensive, fragmented systems mean patients often wait days or go undiagnosed entirely.
We provide facilities with AI-powered tools and remote reporting infrastructure that deliver accurate, structured radiology reports in hours, not days, at a fraction of the cost of traditional RIS/PACS systems. Our low-cost hardware and cloud platform eliminate the need for expensive IT investments, while automated workflows and AI quality control improve report accuracy, reduce errors, and standardize care.
Beyond speed and affordability, our tools shine a light on systemic quality gaps in reporting. Facilities gain visibility into turnaround times, error rates, and radiologist performance—data that was previously invisible. The result is faster, more reliable diagnoses for patients, better accountability for providers, and a scalable path to diagnostic equity across fragile health systems.
