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Enlight Exchange

Enlight Exchange provides a secure platform for researchers to access anonymized mental health data, facilitating data discovery and collaboration among global data providers. This exchange addresses the lack of comprehensive and accessible mental health datasets, enabling more effective research and innovation in mental healthcare.

Santa Monica, United StatesFounded 20228100+ followers
Updated 4 months ago

Funding

Funding not disclosed

Funding rounds are not available yet.

Founders

Product

Problem

Mental health research is often hindered by a lack of comprehensive and accessible datasets. Researchers face challenges in discovering and accessing anonymized mental health data from diverse sources, limiting collaboration and slowing innovation in mental healthcare.

Solution

Enlight Exchange is a platform designed to facilitate the secure exchange of anonymized mental health data between researchers and data providers. The exchange enables researchers to easily discover and request specific datasets, while allowing data providers to securely list their data offerings. By connecting these two groups, Enlight Exchange aims to overcome the limitations of data scarcity and fragmentation, fostering collaboration and accelerating advancements in mental health research. The platform simplifies data discovery and promotes the use of diverse datasets in mental health studies.

Target Audience

The primary users are mental health researchers seeking diverse datasets and data providers looking to share their anonymized data with the research community.

Features

  • Secure platform for listing and requesting anonymized mental health data.
  • Search functionality enabling researchers to find specific datasets based on various criteria.
  • Streamlined process for data providers to securely share their data offerings with researchers.
  • Facilitates collaboration between global data providers and researchers.
  • Closed Beta program for qualified data providers and researchers.
This profile is AI-generated and may contain inaccuracies.