Entelai is a health technology company that uses artificial intelligence to automate and enhance the interpretation of medical images. Based in Latin America, Entelai specializes in AI solutions that assist radiologists and clinicians in achieving faster, more accurate diagnoses across multiple medical domains.
At the core of Entelai’s offering is its flagship platform, Entelai Pic, which combines advanced machine learning algorithms with medical imaging workflows. The system is designed to integrate seamlessly with radiology departments, providing decision support that improves efficiency and consistency in clinical interpretation.
Entelai aims to address the growing demand for diagnostic imaging services by offering scalable AI tools that reduce reporting time, support early disease detection, and improve patient outcomes. The platform has already demonstrated real-world success in radiology, neurology, and ophthalmology.
Features
Entelai Pic: This is the company’s main AI-powered platform that analyzes medical images, extracts clinical information, and provides structured reports. It supports various imaging modalities including MRI, CT, and fundus photography.
Brain MRI Analysis: Entelai provides automated segmentation of brain structures and detects abnormalities such as white matter lesions and brain volume changes, supporting early diagnosis of neurodegenerative diseases like multiple sclerosis.
Chest X-Ray Analysis: The platform identifies common thoracic conditions including pulmonary opacities, cardiomegaly, and pneumothorax. This supports triage and decision-making in emergency care settings.
Ophthalmology Support: Entelai includes AI tools for detecting diabetic retinopathy and other eye diseases from retinal images, making it suitable for primary care screening programs.
DICOM Compatibility: Entelai supports DICOM image formats and integrates easily with hospital PACS systems, ensuring smooth adoption without major infrastructure changes.
Cloud-Based Deployment: The system is accessible through a secure cloud environment, allowing hospitals, clinics, and remote practices to access the platform from anywhere.
Automated Reports: After analyzing the image, Entelai generates structured diagnostic reports that include visual overlays and quantifiable results, reducing the time spent on manual measurements and reporting.
Multilingual Interface: Designed for international scalability, Entelai supports multiple languages, making it suitable for global deployments and diverse healthcare settings.
How It Works
Entelai Pic functions by receiving medical images directly from imaging devices or radiology archives through DICOM-compatible connections. Once images are uploaded to the system, Entelai’s AI algorithms begin automatic analysis, identifying key clinical findings relevant to the scan type.
In brain MRI analysis, the software segments brain regions, quantifies volumes, and identifies lesions or other abnormalities that could indicate diseases like multiple sclerosis or Alzheimer’s. For chest X-rays, the system flags urgent findings such as fluid accumulation or abnormal lung opacity.
In ophthalmology, retinal images are analyzed for signs of diabetic retinopathy using deep learning models trained on large, annotated datasets. If pathology is detected, the system generates an alert and supports referral to specialist care.
Each analysis ends with a structured report that includes both visual results and numerical measurements. The reports can be reviewed by radiologists or general clinicians, enabling faster decision-making and reducing diagnostic backlogs.
Because the platform operates in the cloud, results can be accessed from any authorized location, enabling teleradiology and remote diagnostics.
Use Cases
Entelai is used in a wide variety of healthcare environments where rapid, reliable diagnostic imaging support is essential.
In neurology clinics, Entelai supports the early detection and tracking of neurological conditions by providing quantifiable brain measurements and lesion detection, helping in disease monitoring over time.
Radiology departments use Entelai to prioritize urgent cases, especially in chest X-ray triage where findings like pneumothorax or cardiomegaly require immediate attention.
In public health and primary care, the platform supports large-scale diabetic retinopathy screening programs by enabling general practitioners and nurses to screen patients without waiting for specialist input.
Teleradiology providers benefit from Entelai’s automated reporting tools, which help deliver consistent results faster, even in high-volume environments.
The platform is also used in clinical research and trials that require standardized imaging analysis across multiple sites.
Pricing
Entelai does not publish its pricing on its website. Pricing typically depends on the scale of deployment, number of imaging modalities used, and total scan volumes processed monthly.
Hospitals, clinics, and research institutions interested in implementing Entelai can request a customized quote by contacting the company directly. Entelai may offer tiered plans based on usage, cloud storage needs, and required features.
Pilot programs or scaled trials may also be available for new users or public health institutions seeking to assess the platform’s effectiveness before full deployment.
Strengths
Entelai’s greatest strength is its multi-specialty AI capability, covering radiology, neurology, and ophthalmology within a single platform. This makes it a flexible solution for institutions that handle diverse imaging workflows.
Its automated, structured reporting saves time and supports consistency in diagnostics, reducing human error and subjectivity in image interpretation.
The platform’s cloud-based deployment ensures accessibility, scalability, and minimal IT overhead, which is especially valuable in resource-constrained settings.
Another advantage is the platform’s usability in both urban and rural healthcare environments, including support for telehealth and remote screening programs.
Its multilingual design also makes Entelai viable for international use, supporting expansion into new markets.
Drawbacks
One limitation of Entelai is that, while it offers support across several specialties, its depth in each area may not match that of niche-specific AI tools. For example, platforms focused exclusively on cardiology or lung imaging may provide more advanced features for those specialties.
Performance is also dependent on image quality. Poor acquisition standards may reduce the accuracy of AI results, particularly in chest X-rays and retinal imaging.
Another drawback is the lack of transparent pricing on the website, which may make it harder for small clinics or public health organizations to plan adoption without direct consultation.
Some advanced clinical applications may also require radiologists to verify or cross-check the AI output, especially in jurisdictions where regulatory approval for full automation has not yet been granted.
Comparison with Other Tools
Compared to other AI imaging platforms like Aidoc, Zebra Medical Vision, or Arterys, Entelai differentiates itself with its focus on Latin American markets and support for multiple imaging types within one platform.
Aidoc specializes in emergency radiology and provides real-time alerts for conditions like intracranial hemorrhage or pulmonary embolism, whereas Entelai offers broader modality support with emphasis on brain, chest, and eye imaging.
Zebra Medical Vision provides population-level analytics and detection algorithms for a wider range of chronic diseases, including cardiovascular and metabolic conditions. Entelai, in contrast, focuses more on clinical workflow tools and automated reporting.
Arterys offers cloud-native AI with advanced collaboration tools and organ-specific models. Entelai may offer more streamlined integration for resource-limited environments and public healthcare systems, especially in emerging markets.
For healthcare providers needing multilingual, versatile AI tools with scalable deployment, Entelai provides a cost-effective and clinically validated option.
Customer Reviews and Testimonials
While Entelai’s website does not display traditional customer review sections, the company highlights successful collaborations with hospitals, universities, and public health organizations throughout Latin America.
The platform has been implemented in screening programs for diabetic retinopathy and has been used in multiple research studies involving brain imaging and chest radiology.
Testimonials from clinical partners emphasize improved workflow efficiency, faster reporting times, and successful scaling of AI-supported diagnostics in both urban hospitals and rural clinics.
Prospective users are encouraged to contact Entelai directly for references, case studies, or demo access to evaluate the system’s performance in real-world settings.
Conclusion
Entelai is an innovative AI medical imaging platform that supports faster, more consistent diagnosis across neurology, radiology, and ophthalmology. With its robust image analysis capabilities, structured reporting, and cloud-based architecture, it empowers healthcare providers to streamline workflows, reduce diagnostic errors, and improve patient care.
Its strengths lie in versatility, ease of integration, and multilingual support, making it ideal for emerging markets and institutions needing scalable, reliable diagnostic AI tools. While not as specialized in individual domains as some competitors, its broad functionality and proven success in public health applications position Entelai as a leading solution in medical imaging automation.
