MD.ai

What MD.ai does

MD.ai is a New York-based medical AI software company operating two core products: MD.ai Annotator, a DICOM-native cloud platform for creating large, high-quality labeled medical imaging datasets and deploying/validating AI models, and MD.ai Reporting, an AI-enabled clinical reporting platform that uses HIPAA-compliant large language models and speech-to-text to automate template selection, impression generation, proofreading, and billing code generation for radiologists. The platform supports collaborative annotation, AI-assisted labeling, PHI detection and de-identification, developer APIs (REST, Python client library, CLI), and integrates natively with Google Cloud Healthcare API, Amazon S3, Azure Blob Storage, NVIDIA Clara, Google Vertex AI, and HL7/DICOM-based EHR/RIS systems. The company holds FDA 510(k) clearance for its medical imaging viewer and operates in HIPAA-, ISO 27001-, and GDPR-compliant environments.

MD.ai serves two primary customer segments: top US academic medical institutions (Mayo Clinic, Stanford, NIH, Cleveland Clinic, UCSF, Northwestern, Emory) using the platform for radiology AI research and benchmark dataset creation, and large pharmaceutical and medical technology companies (Philips, Johnson & Johnson, Bayer) using it for algorithm validation and clinical workflow development. Its go-to-market combines a free, self-serve public annotation tier (public.md.ai) that funnels researchers and smaller institutions into the ecosystem, with a quote-based enterprise sales motion ("Get a Demo" / "Contact us") for HIPAA-compliant deployments. Distribution is reinforced through a flagship multi-year partnership with the Radiological Society of North America (RSNA) hosting annual Kaggle AI challenges, additional collaborations with SIIM and ASNR, and joint white papers with NVIDIA and Google Cloud.

The company is privately held, was founded in 2016 by Harvard/Duke/Columbia-trained physicians, and is structured as MD.ai, Inc. (Delaware/New York). It is US remote-first with a headquarters in New York City, runs a SaaS subscription revenue model, and has disclosed one funding round led by Vye Ventures in April 2022. Headcount is reported in the 1-10 range, and the company currently lists no open positions on its careers page, signaling a small but operationally lean team relative to the breadth of its platform capabilities and partner ecosystem.

Name

MD.ai

Legal name

MD.ai, Inc.

Website

https://md.ai

Company type

Private

Founded year

2016

Operating status

Operating

Headcount range

1–10 employees

Short description

MD.ai operates a DICOM-native cloud platform for medical imaging AI: MD.ai Annotator for collaborative dataset creation and AI model validation, and MD.ai Reporting for AI-powered clinical reporting for radiologists. It serves US academic medical centers, pharmaceutical companies, and medical technology firms, distributing via RSNA-hosted Kaggle challenges and HIPAA-compliant enterprise deployments.

Ownership category

akta.pro rank

Product category

Medical Imaging AI Software

NAICS

Software Publishers (5132), Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services (518210), Navigational, Measuring, Electromedical, and Control Instruments Manufacturing (33451)

SIC

Services-Prepackaged Software (7372), Surgical & Medical Instruments & Apparatus (3841)

akta.pro primary industry

AI Orchestration & Imaging Analytics Platforms (Model Management/Triage) (HLACALAG)

akta.pro secondary industries

Medical Imaging AI (HDAAAEAH), Annotation Tooling & Workflow Management (HDAAALAC), Data Labeling & Annotation Services (HDAAALAB), Domain-Specific Training Data Solutions (e.g., medical, AV, geospatial) (HDAAALAL), SaMD – Imaging & Signal Analysis (AI/ML) (HLACANAG), End-to-End Enterprise AI Platforms (MLOps & Model Lifecycle Management) (HDAEANAA)

Keywords

• Medical imaging AI
• Radiology reporting software
• DICOM annotation platform
• Clinical AI workflows
• Medical data annotation

Headquarters

HQ city

New York

HQ country

United States

HQ region

North America

Offices1 record

Markets served

GTM type

B2B

Offering type

Software

Cost components

Personnel, Technology or R&D, Infrastructure, Marketing or Sales, Operations

Revenue model

1. SaaS Platform Subscription: Cloud-based SaaS platform providing annotation tools and AI reporting capabilities on a subscription basis. Supports enterprise deployments with HIPAA compliance and Business Associate Agreements for healthcare organizations.

Go-to-market motion1 record

Distribution channels4 records

Marketing channels6 records

Core offering

MD.ai operates a DICOM-native cloud platform offering two core products: MD.ai Annotator for medical imaging data annotation, dataset creation, and AI model training/validation, and MD.ai Reporting for AI-powered clinical reporting workflows for radiologists using HIPAA-compliant LLMs and speech-to-text. The platform enables healthcare organizations to build high-quality labeled medical imaging datasets, deploy and validate AI models, and automate radiology report generation.

Product overview

MD.ai offers two core products: MD.ai Annotator and MD.ai Reporting. MD.ai Annotator is a DICOM-native annotation platform that enables doctors, scientists, and engineers to create large high-quality labeled datasets, deploy and validate AI models, and build AI-driven clinical workflows. MD.ai Reporting is a cloud-based AI-enabled platform that supercharges clinical reporting workflows for radiologists using LLMs and speech-to-text technology. The two products work together: Annotator handles dataset creation and model development while Reporting enables AI-powered clinical deployment. Both products share HIPAA compliance, cloud infrastructure, and developer APIs.

Differentiator

Problem solved

Functional benefit

Products and services

• MD.ai Reporting Cloud-based AI-enabled platform for radiologists that streamlines clinical reporting workflows using speech-to-text and HIPAA-compliant LLMs. Features automatic template selection, key findings dictation mapping, impression generation, proofreading, automated billing code generation, multilingual support, and contextual AI chat with simple HL7/DICOM integration into EHR/HIS/RIS systems.
• MD.ai Annotator DICOM-native data annotation platform for building high-quality medical imaging datasets and deploying AI models. Includes native DICOM support, FDA 510(k)-cleared viewer, AI-assisted annotation (bounding boxes, freeform, polygons, masks, lines, locations), PHI detection and de-identification, real-time collaboration, and developer APIs with seamless scaling for collaborative annotation workflows.

Quantifiable outcome

• RSNA 2024 Lumbar Spine Degenerative Classification challenge hosted on platform with Kaggle participation
• +1 more outcomes

Named customers12 records

Segments3 records

Ideal customer profiles3 records

Technology focussed Yes

API detail

Has API

Yes

API docs

API detail

Core technology

AI maturity

App detail

Integration7 records

AI capability8 records

Feature8 records

Partnerships

Five partnerships are on record, tiered core, flagship and minor.

• NVIDIAcoreTechnology or IntegrationMD.ai collaborated with NVIDIA to validate AI models collaboratively using NVIDIA Clara Imaging platform. Published joint white paper highlighting key components of each platform and steps necessary to quickly deploy a medical imaging model built with NVIDIA Clara on MD.ai.
• Google CloudcoreTechnology or IntegrationMD.ai leverages Google Cloud Platform and Cloud Healthcare API to create annotated datasets and build algorithms for machine learning. Published case study on Google Cloud customer page showcasing infrastructure partnership.
• Radiological Society of North America (RSNA)flagshipStrategic or Co-development PartnerMulti-year strategic partnership where MD.ai platform hosts RSNA annual AI challenges including RSNA Pneumonia Detection, Intracranial Hemorrhage Detection, Cervical Spine Fracture Detection, Abdominal Trauma Detection, and Lumbar Spine Degenerative Classification. MD.ai creates datasets and platform infrastructure for competitions.
• Society for Imaging Informatics in Medicine (SIIM)coreStrategic or Co-development PartnerCollaborated with SIIM on SIIM-ACR Pneumothorax Segmentation and SIIM-FISABIO-RSNA COVID-19 Detection challenges, providing annotation platform infrastructure.
• American Society of Neuroradiology (ASNR)minorStrategic or Co-development PartnerCollaborated with ASNR on RSNA Intracranial Hemorrhage Detection challenge for dataset creation and annotation.

Scale indicators4 records

Recent moves5 records

Expansion highlights5 records

Direct peers

• CARPL.ai: Direct competitor in the medical imaging AI validation and deployment platform category. Market intelligence names CARPL.ai as the current leader among seven active vendors in this space.
• RedBrick AI: Medical imaging annotation platform offering AI-assisted labeling tools for radiology and pathology datasets. Closely comparable to MD.ai Annotator in target customer (radiologists, ML teams) and DICOM-native workflow.
• Encord: Data labeling and curation platform with dedicated medical imaging workflows and DICOM support. Competes with MD.ai Annotator for healthcare AI teams building labeled imaging datasets.
• V7 Labs: AI-assisted annotation platform supporting medical imaging use cases, including segmentation and classification. Comparable in product surface to MD.ai's annotation and AI-assisted labeling.
• SuperAnnotate: End-to-end data annotation platform with healthcare and medical imaging customers. Competes with MD.ai for ML teams building high-quality labeled medical datasets.

Emerging players

• Segmed: Medical imaging data platform providing curated de-identified datasets and annotation services for AI development. Adjacent competitor to MD.ai for dataset acquisition and annotation workflows.
• Gradient Health: Curated medical imaging dataset and annotation provider focused on accelerating AI training. Comparable to MD.ai's data and labeling services for radiology AI developers.

Broad incumbents

• Labelbox: Broad data labeling and MLOps platform serving multiple verticals including healthcare. Competes with MD.ai Annotator for enterprise ML teams needing scalable annotation pipelines.
• Scale AI: Large data labeling and AI infrastructure provider with healthcare and imaging projects. Competes with MD.ai for medical imaging annotation at scale, with substantially greater resources.
• Amazon SageMaker Ground Truth: Hyperscaler-provided managed data labeling service integrated with AWS, which MD.ai already supports as a storage integration. Represents a commoditized alternative for medical imaging labeling.

Market position

Strengths5 records

Weaknesses5 records

Competitive moat6 records

Key risks6 records

Key highlights7 records

Customer concentration

• GitHubgithub.com/mdai
• Xx.com/md_ai_

Compliance3 records

Revenue estimate

Valuation estimate

Number of profiles

Profiles1 record

Funding overview

Funding rounds1 record

Investors2 records

Funding detail is available on the Subscription and Enterprise plan.Contact sales →

M&A

Investments

M&A and investment is available on the Subscription and Enterprise plan.Contact sales →

Frequently asked questions about MD.ai