Our company had early access to this product and I was impressed by it. Our company had built our own FHIR datastore and I can attest to the fact that it's a mo

Our company had early access to this product and I was impressed by it. Our company had built our own FHIR datastore and I can attest to the fact that it's a more complex endeavor than it seems externally. The killer feature of the product is its simple connectivity to other Google Cloud products for ML/Analytics purposes. Being able to receive a large quantity of radiology images (DICOM) or clinical data (using tools like Epic Kit/Caboodle) and immediately _do something with it_ is pretty impressive and hopefully lowers the burden for innovators in the space. Of course, there are other options if you are looking for them, namely: 1) Azure API for FHIR: https://azure.microsoft.com/en-us/services/azure-api-for-fhir/ https://azure.microsoft.com/en-us/services/azure-api-for-fhi... -> Focused a bit more on application-workflows currently than ML/Analytics. Also has an open-source version: https://github.com/Microsoft/fhir-server https://github.com/Microsoft/fhir-server 2) HAPI FHIR: http://hapifhir.io/doc_intro.html http://hapifhir.io/doc_intro.html Open-source library from the makers of the most popular HL7v2 parser library. We run a bit of this today and it works smoothly. There's unofficial commercial support (same creators, different effort) from https://smilecdr.com/ https://smilecdr.com/. 3) Vonk: Made by a company that has focused alot on FHIR based tooling. https://fire.ly/vonk/ https://fire.ly/vonk/