Six engagements. Real metrics drawn from actual work. No templates, no projections dressed as outcomes, no synthetic case studies. Every number below is something I was accountable for delivering.
The CTO and Chief Data Officer organization of one of the world's largest asset managers needed a rigorous, measurable way to run its enterprise data management program: a common definition of data maturity, a scoring model leadership could trust, and reporting that connected the program's progress to investment decisions.
I was embedded within the organization with direct accountability for the enterprise Data Management OKR program, working alongside internal data, platform, and governance leaders.
CareFirst BlueCross BlueShield, one of the nation's largest regional health insurers, needed to modernize its data and AI function at scale, moving from fragmented, siloed analytics operations to a unified, governed data platform capable of supporting enterprise AI adoption across clinical, operational, and financial domains.
The mandate was broad: own the entire data and AI P&L, build a credible leadership team, modernize the data infrastructure, and demonstrate measurable financial value within the first year.
Radiant Healthcare needed technology and AI strategy that directly connected to financial outcomes, not innovation for its own sake. The organization was navigating cost pressure, operational complexity across a 300+ person workforce, and the challenge of deploying AI in a regulated healthcare services environment where governance and compliance are non-negotiable.
Envision Healthcare's provider-side analytics function, supporting a $300M business, needed to demonstrate that AI and analytics investment could translate directly into revenue cycle performance and cash flow impact. The mandate was to use AI-enabled tooling to improve billing accuracy, accelerate invoice processing, and reduce days sales outstanding.
Through Soft Solutions Partners, we designed and built a commercial AI automation platform integrating GPT-4, Azure OpenAI, and Salesforce Einstein for a client whose sales team was spending the majority of their time on administrative tasks rather than revenue-generating activities. The platform automated proposal generation, CRM data entry, follow-up sequencing, and pipeline reporting, freeing the team to sell.
As Advisory Leader for Data, Analytics and AI, I led technical and data due diligence for a $2B+ private equity fintech transaction, surfacing $40M+ in technology exposure and defining the remediation priorities used in the investment committee's valuation. Alongside diligence work, I designed and deployed a production generative AI document intelligence solution with structured outputs and auditable human review, reducing document review time 60% and doubling analyst coverage, and built enterprise AI governance standards for AI-assisted research inside a regulated investment organization.
Every case above started with a 30-minute discovery call.