When minutes matter,
data can't wait.

Healthcare organizations are moving to Databricks to deploy AI-powered clinical insights, meet regulatory requirements, and improve patient outcomes in real-time. SunnyData accelerates this transformation.

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Trusted by Leading Organizations

THE REAL CHALLENGE

AI needs to show results now. Not potential.

Healthcare and Life Sciences organizations spent years exploring AI. Now their leadership is asking a harder question: where are the actual outcomes?

Healthcare and life sciences AI stuck in pilots — SunnyData builds the reliable Databricks infrastructure to move clinical AI from demo to real production
Siloed clinical, operational, and financial data unified on Databricks — eliminating inconsistent answers across healthcare and life sciences teams
Healthcare and life sciences governance built into Databricks — replacing compliance bottlenecks with a framework that shapes and accelerates AI adoption
Real healthcare interoperability on Databricks — connecting EHR, claims, lab platforms, and device data into a unified, reliable view for life sciences organizations

BUILT FOR HEALTHCARE

The speed and security Healthcare demands.

Healthcare organizations need partners who understand both the technology and the industry. We transfer the knowledge to run what we build.

Healthcare-specific expertise

CLINICAL

Move from batch reports reviewed hours after the fact to insights delivered at the point of decision when care teams can still act on them.

HIPAA-compliant by design

COMPLIANCE

Regulatory requirements built into the architecture from day one. Governance that accelerates AI adoption instead of standing in its way.

Unified patient and operational data

PLATFORM

Clinical records, claims, labs, imaging, genomics, and device data on one governed platform. No silos, fragmented views or competing versions of the truth.

Cost predictability at scale

COMMERCIAL

Compute-based pricing with no per-seat licensing. Costs that scale with actual usage, not vendor tier structures.

WHO WE WORK WITH

Four segments. One consistent standard.

Each part of the HLS industry faces distinct pressures. We understand the specifics of each and build accordingly.

BioPharma
From molecule to market, with data you can act on.
Pharma companies face simultaneous pressure on every front: patents cliff, pipeline pressure, and growing scrutiny on what they bring to market. The key is turning their data into a strategic asset across the entire value chain: from early research through commercial launch.
💊
AI-assisted drug discovery acceleration through target identification and biomedical research assistants.
🔬
Clinical trial optimization through protocol design, site selection, adverse event detection.
📋
Regulatory document generation and submission workflow automation.
📄
FAIR data platform implementation for cross-functional research data access.
📦
Supply chain visibility and demand forecasting for new product launches.
💼
Sales rep and medical affairs next-best-action for provider engagement
BioPharma outcome and foundation
The Outcome
A pharmaceutical organization that:
  • Identifies promising compounds faster
  • Runs more efficiently staffed clinical trials
  • Generates regulatory submissions with less manual effort
  • Brings drugs to market with a fully operational commercial data layer
The Foundation we build
  • FAIR data platforms that make research data findable and reusable across teams
  • Governed AI pipelines that meet regulatory requirements
  • Clinical data repositories connecting trial data, real-world evidence, and post-market surveillance in a single architecture.
MedTech
The devices are digital. The data infrastructure often isn't.
Many organizations are managing all of this while integrating the data complexity of recent acquisitions. The gap between the ambition of connected, intelligent devices and what the underlying data infrastructure can actually support is where most opportunities are lost.
🩻
AI-powered image analytics and surgical workflow optimization.
🚨
Postmarket safety surveillance, automated signal detection from device data streams.
🌍
End-to-end dual supply chain visibility across geographies and acquisitions.
✅
Verification and validation automation for AI-enabled device submissions.
⌚
Connected device pipelines, continuous glucose monitoring, remote diagnostics.
MedTech outcome and foundation
The Outcome
A MedTech organization where:
  • Device data flows cleanly into clinical evidence
  • Safety signals are detected before they become regulatory events
  • The supply chain is visible end to end
The Foundation we build
  • Streaming architectures for real-time device telemetry
  • Compliant AI pipelines built to survive regulatory scrutiny
  • Integrated data environments that bridge legacy systems from M&A activity with modern Databricks infrastructure
Health Plans
From processing claims to preventing them.
Health insurance organizations operate under relentless pressure. So how can they use data to move from reactive to proactive? By identifying risk early, closing care gaps, and personalizing how they engage with members.
💰
Revenue cycle integrity: claim denial analytics, fraud, waste, and abuse detection
🚨
Medical coding automation and risk adjustment accuracy
📈
Member risk stratification and retention prediction
🔁
Interoperability infrastructure aligned with current CMS data sharing requirements
🤲
Care management programs and personalized member engagement at scale
Health Plans outcome and foundation
The Outcome
A health plan that:
  • Detects a fraudulent claim pattern before it matures
  • Identifies a high-risk member before an expensive admission
  • Meets current interoperability requirements without a two-year integration project
The Foundation we build
  • Unified platforms consolidating claims, clinical, and member data
  • HIPAA-compliant AI pipelines with governance built in
  • Interoperability architectures that position health plans ahead of regulatory requirements
Providers
Clinical data that reaches the people who need it.
Hospitals and health systems are under structural pressure. The data exists. The gap is in making that data available, trustworthy, and actionable at the point of decision for the clinician at the bedside and the executive in the boardroom.
📄
Clinical documentation and coding automation, reducing administrative burden on clinical staff
😷
Patient risk stratification and population health analytics
🤲
Care gap identification and value-based care program performance tracking
📋
Revenue cycle analytics, from denial root cause to net revenue yield
🔄
Interoperability infrastructure for care transitions and network referral optimization
Providers outcome and foundation
The Outcome
A health system where:
  • Clinicians spend less time on documentation
  • High-risk patients are identified before a preventable admission
  • The financial performance of every care program is visible in real time
The Foundation we build
  • Unified clinical and operational data platforms
  • HL7 and FHIR-compliant pipelines
  • AI infrastructure designed to meet the security and access requirements of enterprise health systems
  • Integration with Epic, Cerner, and other EHR environments.

OUR APPROACH

Enablers in Healthcare transformation.

Healthcare organizations need a partner who understands both the technology and the industry. We transfer the knowledge to run what we build.

Healthcare-specific expertise

Our HLS practice understands compliance requirements, clinical workflows, and operational pressures unique to the industry, not just the technology layer on top of them.

Build alongside your team

Your data engineers and IT staff participate throughout every engagement. They learn patterns they can apply to future challenges independently.

Knowledge transfer from day one

Every implementation includes documentation, training, and hands-on collaboration. Our success metric goes beyond project completion; it's your team's self-sufficiency.

No proprietary black boxes

Everything we build uses Databricks-native capabilities and open standards. You own the IP, understand how it works, and can maintain it without ongoing dependency on us.

Kai Thapa, CEO and Healthcare & Life Sciences SME at SunnyData — deep expertise across payer, provider, and research data environments on Databricks
Kai Thapa, CEO and Healthcare & Life Sciences SME at SunnyData

With deep experience across payer, provider, and research data environments, Kai brings firsthand knowledge of the compliance requirements, clinical workflows, and operational pressures that define the industry, and what it takes to modernize without disrupting patient care.

Kai Thapa

CEO • Healthcare & Life Sciences SME

HEALTHCARE STANDARDS EXPERTISE

We speak the language of your data

Healthcare data is unlike any other. Our practice is built on deep proficiency in the standards, terminologies, and workflows that make Healthcare systems work.

Built on the standards
your systems already use

We're proficient in HL7, FHIR, and OMOP terminologies. We understand the nuances of payer, provider, and research data, and ensure precise handling across all healthcare workflows.

This isn't surface-level familiarity. It's the deep technical proficiency that separates an implementation that works in a lab from one that runs in a live clinical environment.

Healthcare data solutions built on HL7, FHIR, and OMOP standards — SunnyData ensures precise handling across payer, provider, and research workflows on Databricks
Healthcare data solutions built on HL7, FHIR, and OMOP standards — SunnyData ensures precise handling across payer, provider, and research workflows on Databricks

Built on the standards
your systems already use

We're proficient in HL7, FHIR, and OMOP terminologies. We understand the nuances of payer, provider, and research data, and ensure precise handling across all healthcare workflows.

This isn't surface-level familiarity. It's the deep technical proficiency that separates an implementation that works in a lab from one that runs in a live clinical environment.

HL7 v2 and v3 message processing on Databricks — converting complex healthcare messages into standardized, queryable formats
HL7 v2 and v3 message processing on Databricks — converting complex healthcare messages into standardized, queryable formats

HL7 Message Processing

Complex HL7 v2 and v3 messages converted into standardized, queryable formats. Freeing data trapped in messaging infrastructure.

HL7 Message Processing

Complex HL7 v2 and v3 messages converted into standardized, queryable formats. Freeing data trapped in messaging infrastructure.

FHIR-Native Architecture

Data architectures aligned with FHIR R4 standards, enabling interoperability and simplifying regulatory compliance.

FHIR-Native Architecture

Data architectures aligned with FHIR R4 standards, enabling interoperability and simplifying regulatory compliance.

FHIR R4-native data architecture on Databricks — enabling healthcare interoperability and simplifying regulatory compliance for life sciences organizations

OMOP CDM Implementation

Disparate clinical data gets standardized into the OMOP Common Data Model, enabling cross-institutional research at speed.

EHR System
Integration

Epic, Cerner, and other EHR systems connected to Databricks without disrupting clinical workflows.

OMOP CDM Implementation

Disparate clinical data gets standardized into the OMOP Common Data Model, enabling cross-institutional research at speed.

OMOP Common Data Model implementation on Databricks — standardizing disparate clinical data for cross-institutional research at speed
Epic, Cerner, and EHR system integration with Databricks — connecting clinical workflows without disruption for healthcare and life sciences organizations

EHR System
Integration

Epic, Cerner, and other EHR systems connected to Databricks without disrupting clinical workflows.

Transform Healthcare delivery through data.

Your clinical teams have the expertise. Databricks provides the platform. SunnyData accelerates the transformation.

Talk to our team →