Medical AI company
Remidio
Bengaluru-based maker of portable retinal cameras with on-device AI (MediosHI) for diabetic retinopathy, glaucoma, AMD and ROP.
Company overview
Remidio designs portable ophthalmic imaging devices, including handheld fundus cameras and slit lamps, combined with on-the-edge AI. Its MediosHI AI software, from Medios Technologies in Singapore, screens for diabetic retinopathy, glaucoma, age-related macular degeneration and retinopathy of prematurity without depending on cloud connectivity. The company states its devices have screened more than 16 million people across 55 countries.
- Headquarters
- Bengaluru, India
- Company type
- AI Technology Developer, Medical Technology Manufacturer
- Status
- Established Company
- Deployment
- on-device
In its own words: “Our retinal imaging platforms combine advanced optics with on-the-edge AI to enable early detection and continuous monitoring of disease, delivering fast, reliable results without dependence on cloud connectivity and making them practical in real-world clinical settings” source
AI products and platforms
- MediosHI AI (DR, Glaucoma, AMD, ROP)AI-powered
On-device AI screening of retinal images for diabetic retinopathy, glaucoma, AMD and retinopathy of prematurity
Product page ↗ - Insta Neubo 130AI-powered
ROP AI-enabled ultra-widefield pediatric fundus camera
Product page ↗
Technology categories
Clinical applications
- diabetic retinopathy screening
- point-of-care eye screening
- ER triage
Markets served
- India
- United States
- Singapore
Relationships
- Partner IRIS (Intelligent Retinal Imaging Systems) source
Relationships are shown as stated on the cited page; the other party may not confirm them.
Regulatory information
- First company to receive CDSCO approval in India for adaptive ophthalmic AI, alongside CE marking under EU-MDR source
- CE-marked and FDA 510(k)-registered devices source
As stated by the company or the cited regulator page. Authorisation is specific to a product, version and market; confirm the current status with the company and the regulator. About medical device regulation
Official sources
Last verified 29 October 2026 against the sources above.
Questions about Remidio
Does Medical AI have to explain how it reaches its outputs?
Not always in a technical sense, but transparency about the product is increasingly expected. Many machine learning models cannot give a simple step-by-step reason for each output, so regulators focus on clear information for users: intended use, inputs, how the model was developed and tested, performance, and known limitations.
In the US, one of the criteria for clinical decision support to fall outside device regulation is that a healthcare professional can independently review the basis for its recommendations. FDA has also published transparency principles for machine learning devices with Health Canada and MHRA.
For buyers, a vendor's ability to document how its model works and where it fails is often more useful than heat maps or confidence scores alone.
What is AI image reconstruction and denoising?
AI image reconstruction and denoising use deep learning to produce clearer images from raw scanner data or to reduce noise and artifacts, for example in CT or MRI. Vendors often position these tools as supporting lower-dose or faster scanning protocols.
Unlike detection software, these tools change the image the clinician reads rather than adding a finding. Questions to ask include:
- Is the function built into the scanner or a separate software product?
- Which scanners, protocols and body regions is it authorized for?
- How was diagnostic image quality evaluated, and could fine detail be lost or altered?
These functions are typically regulated as part of the imaging device or as image processing software, depending on the product and market.
What is AI-powered medical image analysis?
AI-powered medical image analysis uses machine learning, often deep learning, to process images and return outputs such as detected regions, segmentations, measurements, quantitative scores or classifications.
It is used beyond radiology, including in cardiology (echocardiography), pathology (whole-slide images), dentistry (intraoral and panoramic radiographs), ophthalmology (retinal photographs and OCT) and dermatology. Outputs may be shown as overlays, structured results or notifications.
Because the software analyzes medical images, in the US it does not meet the criteria for non-device clinical decision support, and image analysis with a medical purpose is commonly regulated as a device. The Medical Imaging AI category in the Medical AI directory covers these companies.