Intelpixel provides a cloud‑based platform that aggregates and indexes over 9 million anonymized medical imaging studies from more than 500 healthcare sites across the US, MENA, and Asia. Researchers and AI developers can instantly search, access, and download diverse, compliant datasets for model training, device development, and clinical trials, while providers can monetize their de‑identified scans through a secure contribution portal.
Funding
Funding not disclosed
Founders
Product
Problem
Healthcare providers often have large volumes of medical imaging data that remain unused due to privacy concerns and complex licensing processes, while AI researchers face lengthy negotiations and limited access to diverse, high‑quality datasets needed for model development and validation.
Solution
Intelpixel offers a platform that aggregates anonymized, indexed medical imaging studies from over 500 healthcare sites across the US, MENA, and Asia. Providers can upload de‑identified scans and receive compensation, contributing to research without exposing patient identities. Researchers gain instant, cloud‑based access to searchable datasets, including free sample images, and receive notifications when new studies become available. The service streamlines data licensing, eliminating weeks‑long negotiations, and supports rapid iteration of AI models for diagnostics, device development, and clinical trials.
Target Audience
Primary customers are medical imaging AI developers, device manufacturers, and clinical research organizations that require large, diverse, and compliant imaging datasets, as well as healthcare providers seeking to monetize their de‑identified scan archives.
Features
- Index of more than 9 million de‑identified imaging studies searchable by modality, anatomy, and metadata
- Cloud‑native data delivery that provides immediate, secure access without local storage or transfer delays
- Provider portal for automated de‑identification, dataset contribution, and revenue tracking
- Real‑time update feed and alert system for newly added studies and dataset expansions
- Free sample library enabling quick evaluation of data relevance before full acquisition
- Multi‑regional coverage (US, MENA, Asia) ensuring demographic and equipment diversity for robust model training