AI Consultant & Strategist
Bridging the gap between cutting-edge AI and the operational realities of enterprise systems.
Get in touch →// About
I bring a rare combination of quantitative rigor, financial expertise, project management and software development, and design thinking to AI consulting. With a background spanning astrophysics research at NASA, prime brokerage at Goldman Sachs, foreign exchange at JP Morgan, analytics leadership in consulting, and product development as a founder, I understand how organizations actually work — and where AI can genuinely move the needle.
I help companies cut through the AI hype and implement practical, high-impact solutions in operations, reporting, and data systems.
// Services
Assess where AI fits in your operations, identify high-value opportunities, and build a practical implementation plan your team can actually execute.
Map your existing processes and replace manual, repetitive work with intelligent automation — freeing your team to focus on what matters.
Build intelligent dashboards and reporting pipelines that surface insights automatically, replacing slow manual reporting with real-time clarity.
Develop bespoke AI-powered tools tailored to your specific business problems — from internal assistants to predictive models and data pipelines.
Specialized expertise in applying AI to financial operations, quantitative analysis, risk reporting, and investment data workflows.
Help your team understand, trust, and effectively use AI tools — turning skeptics into advocates and ensuring lasting organizational change.
End-to-end development of AI-powered applications — from database and backend architecture to polished, client-facing interfaces built to production standards.
From data visualization and interaction design to visual systems and brand identity — bringing aesthetic rigor and design thinking to every layer of a product, from the first concept to the final interface.
// Case Studies
A New York-based founder needed to bring a product to life but faced the prospect of a costly traditional buildout — hiring a full engineering team, long development cycles, and significant capital burn before reaching an MVP. They needed a smarter path forward.
The founder launched a functional product at a fraction of the cost of a traditional buildout. AI-first architecture eliminated the need for a large engineering team, saving significant capital while delivering a system built to scale.
A private equity portfolio manager wanted to use AI to streamline investor reporting and portfolio monitoring but had no technical foundation for it — and no internal team to evaluate or implement the right approach. The tools existed; the strategy didn't.
LP report drafting time cut by over 60%. The portfolio manager gained a clear, actionable AI integration roadmap. The team moved from AI curiosity to confident, daily use of Claude as a core part of their reporting process.
A financial services firm had invested in AI tooling but adoption was stalling. Team members were skeptical, unsure how AI fit their specific workflows, and defaulting to old habits. The tools were there — the organizational buy-in wasn't.
AI tool usage increased significantly across all teams within 30 days. Skeptics became internal advocates. The firm developed lasting AI literacy — not just familiarity with tools, but the judgment to apply them strategically to new problems.
The Met's digital archive of 200,000+ works was largely inaccessible to younger audiences — particularly young people from nearby neighborhoods who had never engaged with the museum. The data existed; the entry point didn't.
Demonstrated how combining open cultural datasets with an unexpected interface layer can unlock entirely new audiences. The project launched at rappersdelight.nyc — a model for how institutions with large, underutilized data archives can use API integration to drive discovery and engagement.
Cutting-edge microbiome research from the Mason Lab at Weill Cornell was generating rich scientific data about the microbial life of NYC — but it was invisible to the public and locked in academic formats. How do you make complex biological data not just understandable, but viscerally felt?
Presented at the Venice Biennale and featured in Wired and National Geographic. Results contributed to peer-reviewed publications in environmental microbiology. Demonstrated that rigorous scientific data, when designed with intention, can shift public perception at scale.
How do you show a user that Facebook's continuous profiling is for the purpose of building detailed personality models to target ads to you? Most users had no idea this was happening, let alone what conclusions the platform had drawn about them.
Over 70,000 installs on the Chrome Web Store. Covered by Vice, Fast Company, Mashable, The Next Web, and Big Think. Nominated for The Index Project award. Sparked mainstream conversation about algorithmic profiling and data rights — demonstrating that technical tools can be powerful instruments of public education.
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