Demos
John Snow Labs, the AI for healthcare company, today announced the release of API Endpoints for medical language models on AWS SageMaker, Databricks Marketplace, and Snowflake Marketplace. This development brings John Snow Labs’ state-of-the-art healthcare artificial intelligence (AI) models to a wider audience through a simplified, secure API integration process.
Customers can buy and deploy private API endpoints with a few clicks, making it faster and easier to get started. There is no need to manage servers, uptime, failover, scaling, or security updates, as the endpoints are fully managed. Models are available for specific healthcare language understanding tasks such as medical text de-identification, summarization, information extraction, and question answering, and are regularly updated to ensure users have continued accuracy.
In addition to delivering higher accuracy with healthcare-specific models, a key difference of this solution is privacy. Endpoints are only deployed within each customer’s infrastructure and security perimeter, meaning sensitive data is never sent to a third party—not even to John Snow Labs. These endpoints are designed from the ground up to work in high-compliance environments, in which other security and privacy controls are in place.
“The ease with which language models can now be accessed and deployed is a significant advancement in the field—especially in the healthcare industry, where easy-to-use APIs often require unacceptable compromises to privacy and security,” said David Talby, CTO, John Snow Labs. “This is just one more way John Snow Labs is making Responsible AI easily available to practitioners worldwide.”
The Private API Endpoints have already made a significant impact with enterprise customers. A recent Data + AI Summit session titled “Unlocking New AI Use Cases with Sharing,” co-presented by Databricks and John Snow Labs, showcased the practical applications and success stories of the models.
Additionally, the company will host a webinar titled, “Turnkey Deployment of Medical Language Models as Private API Endpoints,” at 2pm ET on Tuesday, August 28, diving deeper into the currently available models and how they can be easily deployed for inference on each cloud marketplace.
