Built on Validation confirms Gravity\u2019s production use of Databricks SQL, Managed MLflow, and Delta Lake, enabling healthcare organizations to accelerate AI innovation and integrate agentic workflows into practice.<\/p>\n
Innovaccer Inc., a leading healthcare AI company, today announced it has achieved Built on Validated Partner status with\u00a0Databricks, the Data and AI Company. The validation recognizes Gravity\u2019s production use of Databricks\u2019 lakehouse architecture and machine learning (ML) capabilities across Innovaccer\u2019s Autonomous Healthcare Platform.<\/p>\n
Designed specifically for healthcare, Gravity features pre-built clinical and payer data models, industry-standard ontologies (SNOMED, ICD, LOINC, CPT, and RxNorm), proprietary predictive ML models, and clinical knowledge bases that eliminate the foundational work health systems would otherwise spend years building. Databricks powers Gravity\u2019s ML and AI infrastructure, spanning data transformation, analytics, ML lifecycle management, and model deployment, giving data science and AI teams a healthcare-native foundation where the work begins at insight and agent development, not data wrangling.<\/p>\n
\u201cBuilt on validation reflects tangible technical alignment and joint intent,\u201d said Abhinav Shashank, cofounder and CEO of Innovaccer. \u201cGravity is designed to meet healthcare organizations where they are and take them where they need to go. Databricks strengthens the AI and ML capabilities at the heart of that\u2014from pipeline development to model deployment, so our customers can focus on outcomes, not infrastructure.\u201d<\/p>\n
\u201cDatabricks built on partners deliver differentiated solutions by leveraging the Databricks platform,\u201d said Aaron Zavora, Global Healthcare GTM Leader, Databricks. \u201cWe are pleased to welcome Innovaccer as a Validated Built on Partner and support their work leveraging Databricks lakehouse architecture and ML capabilities within Gravity for enterprise healthcare workloads.\u201d<\/p>\n
As part of the partnership, Innovaccer and Databricks will collaborate to advance the following capabilities for joint customers:<\/p>\n
Support healthcare organizations building lakehouse-based data foundations using Delta Lake to enable scalable analytics and AI readiness across multi-source healthcare environments.<\/p>\n
Enable repeatable production-grade data transformation and analytics workflows with Databricks SQL and Spark Declarative Pipelines in Gravity, reducing the custom engineering burden that slows healthcare data teams.<\/p>\n
Support governed ML lifecycle management using Managed MLflow, giving healthcare organizations the ability to build, validate, and deploy models with the auditability and explainability that clinical and regulatory stakeholders require.<\/p>\n
This announcement marks the next step in Innovaccer and Databricks\u2019 partnership to advance modern data and AI capabilities for healthcare enterprises.The post Innovaccer, Databricks Partner to Operationalize Healthcare AI first appeared on AI-Tech Park.<\/p>\n","protected":false},"excerpt":{"rendered":"
Built on Validation confirms Gravity\u2019s production use of Databricks SQL, Managed MLflow, and Delta Lake, enabling healthcare organizations to accelerate AI innovation and integrate agentic workflows into practice. Innovaccer Inc., a leading healthcare AI company, today announced it has achieved Built on Validated Partner status with\u00a0Databricks, the Data and AI…<\/p>\n
The post Innovaccer, Databricks Partner to Operationalize Healthcare AI<\/a> first appeared on AI-Tech Park<\/a>.<\/p>\n<\/div>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"site-container-style":"default","site-container-layout":"default","site-sidebar-layout":"default","disable-article-header":"default","disable-site-header":"default","disable-site-footer":"default","disable-content-area-spacing":"default","footnotes":""},"categories":[4,1],"tags":[3],"class_list":["post-1877","post","type-post","status-publish","format-standard","hentry","category-ai","category-ai-and-ml","tag-ai"],"yoast_head":"\n