Building impact at scale.

The Customer Challenge

Independent financial advisors competed against large banks by offering personalized, high-touch service—but they lacked the time, tools, and resources to deliver on this promise. The industry's complex platforms took months to implement and required PhD-level quants to operate, making them impossible to use while running a business. Advisors needed institutional-grade analytics that were accessible, actionable, and adaptive to their unique workflows—not another rigid system that forced them to change how they worked.

The Solution & Impact

We took the expensive data and analytics from industry-leading institutional platforms and made them accessible to wealth managers without PhD quants on staff. Through 300+ customer conversations, we built experiences and workflows that gave advisors clarity on their client investments—showing them how to improve and personalize portfolios to meet each client's unique needs, in ways they could actually communicate to those clients. The platform took minutes to set up and start getting value, not the months required by competitors.

Personalized proposal creation with automated investment recommendations

Household structure management for complex client relationships

Detailed portfolio editor with drag-and-drop asset allocation

Most importantly, we practiced what we preached: just as advisors delivered personalized advice to their clients, our platform personalized itself to meet advisors where they were—adapting to their workflows and advisory approach rather than forcing them into pre-defined processes. Advisors managed $500B+ in AUM on the platform, grew an average of 5× while using Fabric (with our largest client growing 10× from $10B to $200B), and maintained 95% retention. We raised $7.5M, built an incredible 13-person team, and were acquired by MSCI to bring these capabilities to the world's largest institutions.

The Customer Challenge

After MSCI acquired Fabric, the world's largest private banks faced a critical challenge: delivering the personalized wealth management that clients demand while maintaining alignment across their entire organization—from the Chief Investment Officer's strategy down to thousands of individual client portfolios. They needed a common language and set of tools that could flow seamlessly from the home office to advisors to clients, all while addressing the complex dynamics of global investment regulation, client data privacy, and enterprise scale ($3T+ in AUM across 20+ countries). Traditional platforms forced them to choose between personalization and standardization, between agility and compliance—but they needed both.

The Solution & Impact

We evolved Fabric's advisor-focused application into MSCI's first global enterprise platform—scaling personalization from individual advisors to the world's largest private banks. The platform creates a common language across the organization: CIOs define investment strategies and risk frameworks at the home office level, which cascade down through the platform to guide advisors in constructing personalized portfolios that align with both firm strategy and individual client needs. Advisors can then communicate these recommendations to clients in clear, personalized terms.

Guided workflow for portfolio construction and rebalancing

Bulk rebalancing across multiple client portfolios simultaneously

Client-ready reports with personalized recommendations

To address the complex requirements of global private banking, we deployed the platform across 4 countries with localized instances that respect regional data privacy laws and investment regulations—enabling firms to maintain compliance while scaling operations. We integrated LLM-powered research and generative workflows that give relationship managers AI-assisted insights without compromising client data security, bringing AI capabilities to wealth management at a scale previously impossible.

The platform grew from supporting $500B in 3 countries to $3T+ across 20+ countries—proof that personalization and scale aren't mutually exclusive when you build the right common language and workflows across an organization.

The Challenge

MSCI's 6,000-person global organization was hitting their commitments but failing to achieve business goals. The initial hypothesis was simple: teams needed to build faster. But after empowering all 4,000 engineers with AI development tools like Cursor—pushing through security approvals and securing CTO buy-in—we discovered that velocity alone wasn't the answer. The real problem was deeper: siloed teams working without clear line of sight to business outcomes, quarterly planning cycles where company goals rarely reached beyond middle management, and no visibility into how individual work connected to organizational priorities. Teams were hitting their targets, but those targets weren't aligned with what actually drove business value.

The Solution & Impact

We drove a complete organizational transformation in two phases. First, we empowered the entire 4,000-person engineering organization to adopt AI development tools, securing $5M+ in investment and achieving 15% productivity gains across the board (with select teams reaching 5× velocity improvements). The success of this initiative made AI tools a strategic driving imperative from the CEO, who mandated their application across all aspects of the organization. But when faster delivery didn't translate to business outcomes, we tackled the root cause: organizational structure and goal alignment.

We transformed MSCI from siloed teams to CORE Teams—Cross-functional, Outcomes-driven, Responsible, and Empowered. We supplemented quarterly planning cycles with regular and real-time OKRs that made company goals public and visible to every team member, not just middle management. To support this shift, I built internal LLM-powered tooling that let team members ask questions like "How does my work connect to company goals?" and gave leadership visibility into how team efforts aligned with organizational investments—integrating project management, sales, and customer data into one unified platform.

Operations AI Dashboard integrating project, sales, and customer data

LLM-powered chatbot connecting individual work to company goals

Sales AI Helper automating research and client insights

Client Feedback AI Helper analyzing customer insights at scale

Beyond technology, we transformed how MSCI builds products—moving from traditional waterfall delivery to empowered product teams using OKRs to drive client and business outcomes. This organizational shift enabled the velocity and customer focus required to serve the world's most demanding wealth management and institutional investor clients across diverse global markets. The results so far: 100% of team members report having more clarity on how their work connects to broader goals, and the operations team reduced manual data collection time by 95%.

The Challenge

I believe we are hitting the limit of the "Chatbot Era." Chatbots are silos—great for one-off tasks but terrible for complex, multi-step workflows. I needed a system that could maintain context across research, drafting, and editing steps, using the best model for each specific task, without manually copy-pasting between windows. I wanted to prove that "Contextual Intelligence" could operate outside of app silos.

The Solution & Impact

I built a "Digital Command Center"—a custom CMS that treats AI models as specialized employees rather than generic assistants. The system orchestrates a workflow where Gemini performs deep web research and context gathering, and then passes that structured context to Claude for drafting and voice alignment.

This isn't just a wrapper; it's a "team of models" architecture. The system uses a custom-built MCP (Model Context Protocol) server to give the agents access to my personal data and previous writings, ensuring consistency. By moving from "using a tool" to "orchestrating an outcome," I've increased my ability to produce high-quality, researched content by 10×, while maintaining full control over the final output. This prototype serves as a living lab for the agentic workflows I advocate for at the enterprise level.