
Murali Makkena
I am an AI and data executive in healthcare with 20+ years of experience building and scaling compliant, production-grade platforms and AI systems in regulated environments.
Today, I work with healthcare leadership teams when AI initiatives stall, governance is unclear, or internal teams need senior ownership to move safely from experimentation to real-world impact. I help organizations take AI from prototype to compliant production, balancing speed with safety, trust, and long-term sustainability.
I believe strongly in building systems that work in the real world. Systems clinicians trust, leadership can govern, and engineering teams can operate and scale with confidence.
I founded Nuvii Partners to provide hands-on senior AI leadership without the overhead or rigidity of a large consulting firm.
Career Journey (Selected Highlights)
Nuvii Systems | Founder
- •Building a deployable healthcare AI platform for clinical documentation, coding, and revenue integrity
- •Designing and implementing LLM-based workflows with RAG, evaluation, and auditability
- •Shipping HIPAA-aligned AI systems focused on accuracy, explainability, and real-world clinical use
Why this matters: This work keeps me deeply hands-on with the realities of deploying AI safely in regulated healthcare settings.
Amwell | VP, Head of Data & Engineering
- •Built FHIR- and HL7-interoperable data platforms, unifying data from EHR, EMR, and clinical partners into a centralized, governed data store
- •Designed and delivered zero-trust, HIPAA- and FedRAMP-compliant AWS GovCloud platforms for the Defense Health Agency
- •Built conversational and interaction analytics across virtual care encounters to improve clinician workflows, patient engagement, and care delivery performance
Why this matters: This work shaped my approach to deploying AI and data platforms safely inside the most regulated healthcare environments.
GRAX | VP of Engineering
- •Built a B2B data value platform enabling enterprises to operationalize Salesforce data in their own cloud environments
- •Scaled teams and platforms to support enterprise customers including Dell, Novartis, and Pepsi
- •Balanced startup velocity with enterprise reliability, security, and governance
Why this matters: I learned how to ship quickly without sacrificing trust or operational rigor.
Oracle | Architect to Director of Engineering
- •Owned multiple enterprise SaaS products used by thousands of enterprise customers
- •Led global teams modernizing legacy CRM into Oracle Sales Cloud and CX Cloud
- •Built and commercialized Sales Predictor, an ML-driven product for lead scoring and whitespace analysis (patented)
Why this matters: This experience grounded my ability to take ML from prototype to enterprise-grade production at scale.
Areas of Expertise
Fractional Chief AI Officer and Executive Leadership
Senior ownership for AI strategy, governance, and execution in regulated healthcare environments
AI Strategy and Production Execution
LLMs, RAG systems, evaluation, monitoring, and human-in-the-loop workflows taken from prototype to production
Healthcare Data, Interoperability, and Analytics
FHIR, HEDIS and quality measures, population health, clinical analytics, and AI-ready data foundations
Cloud Architecture, Compliance, and Scale
HIPAA, SOC 2, NCQA, HITRUST, and FedRAMP-aligned systems, with experience scaling teams and platforms from early-stage to enterprise adoption
My Approach
Understand Your Mission
Align on goals, constraints, risk tolerance, and current reality
Define Clear Ownership and Guardrails
What AI should do, what it should not do, and how it is governed
Ship in Small, High-Value Increments
Focused 4 to 6 week cycles that deliver visible progress
Leave You Stronger Than Before
Teams, architecture, and practices that operate confidently without dependency
How I Work
You work directly with me. I lead AI strategy, architecture, and execution personally.
When additional capacity is required, I bring in trusted senior engineers across ML, data, platform, and infrastructure. No junior layers. No unnecessary overhead.