The DAIS 2026 Speaker Spotlight is a series where we hand the mic to the speakers heading to Data + AI Summit and let them answer five short questions โ in their own voice, no press-release polish.
Below, Surya Sai Turaga on how Ensemble Health Partners rebuilt their revenue cycle data foundation on Databricks Lakebase โ 800TB, 25B+ transactions, and a KLAS score of 95. Lightly edited for length โ otherwise, the words are his.
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Every enterprise is asking the same question in 2026: what's the data foundation for production agentic AI? The industry is converging on one answer โ ending the ETL tax that has blocked enterprise AI for a decade.
โ Surya Sai Turaga
The topic
What is your talk about, and who is it for?
How Ensemble Health Partners turned 800TB of fragmented revenue cycle data into an AI-ready foundation on Databricks Lakebase โ driving $30M+ per $1B health system and agentic AI at scale, built for healthcare data leaders and RCM executives.
Why this, why now
What's changed in the last 6โ12 months that makes this topic urgent right now?
Hospital operating margins turned negative in early 2026, payer AI is now denying claims in milliseconds (industry denial rates near 15%), and Databricks Lakebase hit General Availability in February โ making this the exact moment health systems must rebuild their RCM data foundation for the agentic era. Ensemble already ran 25B+ transactions across 30+ health systems on this architecture.
The personal stake
Why are you the people giving this talk?
Grant Veazey is Ensemble's CTO and former CIO โ he's lived the payer-provider data challenges from both sides and now runs the platform processing 25B+ transactions for 30+ health systems, where Ensemble has unified more than 2 petabytes of provider, payer, and clinical data on the Databricks Data Intelligence Platform and earned a KLAS score of 95 โ the highest ever in revenue cycle management. Surya Sai Turaga is the Databricks field architect who partnered with Grant's team to design and ship the 800TB Lakebase.
What you'll leave with
What will someone be able to do on Monday morning that they couldn't do before?
By Monday morning you'll have: a reference architecture diagram for the SQL Server-to-Lakebase consolidation you can sketch on your team's whiteboard, the "hydration principle" pattern for Unity Catalog-driven apps (zero code changes when schemas evolve), a workload-sequencing playbook for what to migrate first, and the math to size your own revenue leakage opportunity for your CFO (3โ5% net yield = $30M+ per $1B health system). Plus the production anti-patterns we hit so your team can skip them.
The bigger picture
How does this fit into where Databricks โ and data and AI more broadly โ is heading?
Every enterprise is asking the same question in 2026: what's the data foundation for production agentic AI? The industry โ and Databricks' bet on Lakebase โ is converging on one answer: a single governed foundation unifying transactional, analytical, and AI workloads, ending the ETL tax that has blocked enterprise AI for a decade. Ensemble is the canonical multi-tenant SaaS proof point at the scale (800TB, 25B+ transactions) and stakes (negative hospital margins).
Part of the DAIS 2026 Speaker Spotlight series โ more voices dropping in the weeks ahead. Got a DAIS speaker you'd love to hear from next? Mention them in the comments โ we're always listening.
