Accolade creates seamless healthcare experiences with a RAG solution on Databricks
AccoladeDatabricks Data + AI Platform · Unity Catalog · Agent Bricks +3
Healthcare technology company Accolade consolidated fragmented data from AWS Redshift and Snowflake into a Databricks lakehouse with Unity Catalog and built a RAG solution using the open-source DBRX model via Agent Bricks Custom Agents to help internal teams quickly and accurately answer complex member inquiries.
Overview
Healthcare technology company Accolade consolidated fragmented data from AWS Redshift and Snowflake into a Databricks lakehouse with Unity Catalog and built a RAG solution using the open-source DBRX model via Agent Bricks Custom Agents to help internal teams quickly and accurately answer complex member inquiries.
This entry has 11 published fields tied to exact passages in an immutable source capture.
Inspect the highlighted sourceThe challenge
Accolade's member data was fragmented across multiple platforms including AWS Redshift and Snowflake, hindering accurate member stratification, slowing internal teams' access to information and increasing operational costs.
The solution
Accolade consolidated data into a Databricks lakehouse architecture governed by Unity Catalog (supporting HIPAA compliance), then built a retrieval augmented generation (RAG) solution using Agent Bricks Custom Agents on the open-source DBRX model, deploying it via Databricks Model Serving as a RESTful API for real-time predictions.
Reported business value
The RAG solution let internal teams quickly and confidently answer complex member inquiries across diverse data sources such as PDFs, protocols and customer information, driving major productivity gains and giving teams greater transparency and control over ML costs and resources.
Sources
Open any source and check the claim yourself — that is the point of the register.
This record was researched and written with AI assistance, and its claims were checked against the sources above. (EU AI Act art. 50 transparency notice.)
Other healthcare entries in the register.
Less paperwork, more time for people: Azure OpenAI at Landsberg Hospital
Klinikum Landsberg am Lech, a German acute-care hospital, deployed an AI language solution built on Azure OpenAI with partner Pexon Consulting that transcribes doctor-patient consultations in real time via tablet, recognizes medical terms, structures the content, and transfers it directly into the hospital information system.
Novo Nordisk builds AI drug discovery platform on Azure with Microsoft Research
Novo Nordisk partnered with Microsoft Research to build an AI platform on Azure AI and data stacks spanning regulatory affairs, early research, drug discovery and trial design, using Azure OpenAI Service, Azure Cosmos DB and Azure Kubernetes Service, with Power BI and Power Apps for collaboration. The platform includes a copilot for researchers, shared reasoning-chain templates, and governance/auditing of how data and models are used. The teams published early results on predictive AI models for cardiovascular disease risk detection, including an algorithm that Novo Nordisk says predicts patients' cardiovascular risk better than the best clinical standards, drawing on more than 100 years of insulin research data.
Novo Nordisk· DenmarkAzure OpenAI Service · Azure Cosmos DB · Azure Kubernetes Service +2BAYADA Builds a Unified, AI-Ready Platform for Compassionate Care
BAYADA Home Health Care is consolidating three separate legacy data platforms (multiple practice management systems, an on-prem ODS, and Snowflake) and 65+ enterprise data sources into a single Databricks Lakehouse under its Data Modernization program, using medallion tiers, Lakeflow Jobs, Asset Bundles, and Unity Catalog governance. As part of the migration, BAYADA uses an LLM-powered code converter and Databricks Assistant to automate SQL and stored-procedure translation, and applies a machine learning-based data mastering accelerator to create golden Client, Payor, Candidate, and Referrer records. BAYADA reports roughly 30% better workload performance and cost efficiency versus its prior Snowflake environment, and is laying a governed foundation for AI agents supporting payroll validation, compliance monitoring, and operational insights, separately from its roadmap for AI-assisted chart review and risk prediction.
BAYADA Home Health CareDatabricks SQL · Lakeflow Jobs · Unity Catalog +1Heidi Health fine-tunes NVIDIA Parakeet/Nemotron ASR, cutting clinical transcription latency 75% and costs 64%
Heidi Health, which processes 2.4 million clinical consultations weekly across 110 languages, fine-tuned the open NVIDIA Parakeet V2 speech recognition model on 1,500 hours of curated clinical audio using the NVIDIA NeMo framework and 8x H100 GPUs, replacing its closed-source vendor ASR. The in-house Nemotron-based ASR stack cut end-to-end transcription latency from about 3.0 seconds to 0.7 seconds (75%+ improvement), reduced word error rate from 13% to 9.4%, and cut operating costs by 64% by eliminating per-minute API pricing, while giving Heidi full ownership of model weights for data sovereignty.
Was this helpful?
Your feedback helps us improve our use case database