This proposal sets out to deliver a solution, EICON MULTIMODAL, that has three main objectives. Firstly, to facilitate access to multimodal clinical data in the public domain by providing a single Cloud-based multimodal search capability across a set of public domain Data Commons. Secondly, to enable healthcare and research organizations to integrate and harmonize their own clinical data into a unified Search Fabric and to adopt a Data Commons paradigm that enables their researchers to search across both public domain and in-house data in a single pass from our Cloud-based browser interface. As part of our security model, we will use the concept of a local "punchout" to keep browser-based in-house data and metadata within the user network and never send these data to the Cloud. Thirdly, to enable healthcare and hospital organizations who have aggregated their data using a Data Commons standard to participate in a marketplace for Real World Data. As part of this implementation, we will integrate EICON DEID, our clinical data de-identification solution, to address the data privacy issues inherent in sharing PHI-bearing data. For Phase I, we will develop a fully functional protptype to demonstrate a solution that meets the first two objectives. In Phase II, we will develop the prototype into a fully tested, validated, production-ready solution with full regulatory compliance, address the third objective, and deploy the solution into at least one research organization and one hospital. Our solution is targeted primarily at AI/ML development groups and will enable them to query, access and create cohorts of multimodal clinical data for use in training their models.