Best AI for OCT: 10 Essential Features Your Platform Must Have 

So you’ve decided to trial AI for OCT analysis and wondering how to choose among all the available platforms. To save you some time, we’ve collected 10 most essential criteria according to which you can assess all existing AI platforms. Using this criteria you will be able to make an informed and rational choice.

As an ophthalmologist, I am interested in finding innovative and modern approaches that could help me to enhance the workflow and improve patient outcome as a result.Analyzing various platforms, I realized that these 10 criteria are crucial for the right choice.

1. Regulatory Compliance and Clinical Validation

In healthcare, safety is always first. Regulatory approval and clinical validation are essential for AI-powered platforms for OCT scan analysis.

The best AI OCT platforms should meet regulatory standards set by authorities such as the FDA, HIPAA, CE, and ISO. 

Adhering to regulatory guidelines enhances credibility and fosters trust among healthcare professionals. Check if the AI for OCT analysis tool has all these certificates in place and if they are valid.

 

2.Wide range of biomarkers and pathologies detected

Some AI for OCT platforms concentrate on certain pathologies, like  Age-Related Macular Degeneration (AMD) or Diabetic Retinopathy, because of the prevalence of these conditions among the population. It mostly means that eye care specialists must know in advance that they are dealing with the AMD patient to find the proof of AMD on the OCT.

The best AI for OCT tools should have a wide variety of biomarkers and pathologies, including rare ones that cannot be seen daily in clinical practice, such as central retinal vein and artery occlusions, vitelliform dystrophy, macular telangiectasia and others. Altris AI, the leader of OCT for AI analysis, detects 74 biomarkers and pathologies as of today. 

3.Cloud-Based Data Management and Accessibility

To ensure seamless integration into clinical workflows, the AI OCT platform should offer cloud-based data management and accessibility. Cloud storage allows for easy retrieval of patient records, remote consultations, and multi-location access. Secure cloud computing also enhances collaboration between ophthalmologists, optometrists, and researchers by enabling data sharing while maintaining compliance with data privacy regulations such as HIPAA and GDPR. 

Many clinics have strict policies regarding patient data storage as well: it is crucial that the data is stored on the servers in the region of operation. If the clinic is in EU, the data should be stored in the EU.

4.Real-world usage by eye care specialists

When choosing the best AI for OCT analysis, real-world usage by eye care specialists is the most critical factor. Advanced algorithms and high accuracy metrics mean little if the AI is not seamlessly integrated into clinical workflows and actively used by optometrists and ophthalmologists. There are thousands of research models available, but when it comes to the implementation, most of them are not available to ECPs.

Eye care professionals are not IT specialists. They require AI that is intuitive, fast, and reliable. If a system disrupts their workflow, generates excessive false alerts, or lacks clear explanations for its findings, adoption rates will be low—even if the technology itself is powerful. The best AI solutions are those that specialists trust and rely on daily to enhance diagnostic accuracy, streamline patient management, and support decision-making.

Moreover, real usage generates valuable feedback that continuously improves the AI. Systems actively used in clinical settings undergo rapid validation, refinement, and adaptation to diverse patient populations. This real-world data is far more meaningful than isolated test results in controlled environments.

5. Customizable Reporting and Visualization Tools

Reports are the result of the whole AI for OCT scan analysis that is why customizable and comprehensive reports are a must.

A high-quality AI OCT platform must offer customizable reporting and visualization tools. Clinicians should be able to adjust parameters, select specific data points, and generate detailed reports tailored to individual patient needs.

Heatmaps, 3D reconstructions, and trend analysis graphs should be available to help visualize disease progression. These tools improve the interpretability of AI-generated insights and facilitate patient education.

 

6.AI for Early Glaucoma Detection

Glaucoma is a leading cause of irreversible blindness, and since OCT is widely used to assess the retinal nerve fiber layer (RNFL), Ganglion Cell Complex ( GCC), optic nerve head (ONH), AI can significantly enhance early detection and risk assessment.

Therefore, the best AI for OCT analysis tools have an AI for early glaucoma detection module available to assess the risk of glaucoma especially at the early stage. Moreover, tracking the progression of glaucoma with the help of AI should also be available for eye care specialists.  

Clear and bright notifications about glaucoma risk are also vital for making AI glaucoma modules easy to use.  AI can provide proactive insights that enable early intervention and personalized treatment plans

7.User – Friendly Interface and Intuitive Workflow Integration

A well-designed AI OCT platform should feature a user-friendly interface that integrates seamlessly into existing clinical workflows. 

It means that even non-tech-savvy eye care specialists should be able to navigate it effortlessly. 

The interface should be intuitive, reducing the learning curve for healthcare providers. Features such as automated scan interpretation, voice command functionality, and guided step-by-step analysis can enhance usability and efficiency.

8.Integration with Electronic Health Records (EHRs)

For a seamless clinical experience, the AI OCT platform should integrate with existing electronic health record (EHR) systems. Automated data synchronization between AI analysis and patient records enhances workflow efficiency and reduces administrative burden. This feature enables real-time updates, streamlined documentation, and easy access to past diagnostic reports.

9. Universal AI solutions compatible with all OCT devices

Uf you want to use AI to analyze OCT, this AI should be trained on data received from various OCT devices and therefore should be applicable with various OCT devices. A vendor-neutral AI tool for OCT analysis provides unmatched advantages over proprietary solutions tied to specific hardware. By working seamlessly with multiple OCT devices, it eliminates the need for costly equipment upgrades and ensures broader accessibility across clinics and hospitals.

This approach also fosters greater innovation, allowing AI models to continuously improve based on diverse datasets rather than being limited to a single manufacturer’s ecosystem. Vendor-neutral solutions integrate effortlessly into existing workflows, reducing training time and boosting efficiency. Clinicians benefit from unbiased, adaptable technology that prioritizes patient outcomes rather than locking users into restrictive ecosystems.

10. Cost-Effectiveness and Accessibility

To maximize its impact, an AI-powered OCT platform should be cost-effective and accessible to a wide range of healthcare providers. Affordable pricing models, including subscription-based or pay-per-use plans, can make AI technology available to smaller clinics and developing regions. Accessibility ensures that AI-driven OCT analysis benefits as many patients as possible, improving global eye health outcomes.

Conclusion

What is the best  AI for OCT scan analysis? The best AI for OCT must be a comprehensive, intelligent, and adaptable platform that enhances diagnostic accuracy, streamlines clinical workflows, and supports proactive eye care. Key features such as high-accuracy automated analysis, multi-modal imaging integration, real-time decision support, cloud-based data management, interoperability, and explainable AI decision-making are crucial for an effective OCT AI system. By incorporating these attributes, AI-driven OCT platforms can revolutionize ophthalmology, enabling early disease detection, personalized treatment planning, and improved patient outcomes. As AI technology continues to advance, its integration with OCT will play an increasingly vital role in shaping the future of eye care.