At Standard Metrics, I build AI-native products that improve how venture capital firms interact with portfolio data.

I own the frontend of AI Analyst and contribute to its backend, working on an AI product that enables investors to query and analyze portfolio-wide financial and performance data through natural language. My work focuses on creating intuitive interfaces for complex data workflows and integrating them with underlying AI agent systems.

I also built and scaled portfolio reporting workflows (tear sheets), replacing manual Excel-based processes with real-time, collaborative systems used by investment and finance teams — resulting in ~450–700 hours saved annually firm-wide.

Technically, I work across:

• AI agent systems (LLMs, tool calling, structured outputs)

• React / TypeScript frontend architecture

• Real-time data systems and APIs

Interested in how AI can reshape decision-making workflows and unlock better ways to interact with structured data.

Served as a judge for the AITEX Summit Winter hackathon, evaluating AI and data-driven projects across areas such as product, operational, and business analytics.

Reviewed solutions focused on real-world applications, including AI-powered tools for decision-making (e.g., trading assistants leveraging real-time data) and systems designed to improve workflows and usability. Provided feedback on technical architecture, product direction, and practical impact, helping teams refine solutions toward production-ready outcomes.

https://aitexsummit.com/winter2026/

Served as a judge for the AI Agents & MCP Hackathon (sponsored by OpenAI, CrewAI, and Nevermined), evaluating projects centered on AI agent systems and emerging developer tooling.

Reviewed solutions leveraging LLMs, multi-agent architectures, and tool-calling frameworks to solve real-world problems, and provided feedback on system design, product direction, and practical usability.

https://luma.com/7lww915n

At ActiveViam, I worked on Atoti, a real-time BI platform used to analyze large-scale, multidimensional datasets.

I contributed across the stack using TypeScript, React, Node.js, and Python, building and shipping product features end-to-end. My work included designing and implementing systems that translate user interactions into complex multidimensional queries, enabling fast and flexible data exploration.

I led the design and development of dozens of features across both frontend and backend, collaborating closely on product and UX decisions.

I also:

• Built an AWS-based system generating evaluation licenses daily (AWS SAM, Lambda)

• Improved codebase reliability by increasing test coverage by 50% and establishing testing best practices

• Developed internal tools to simulate backend interactions (HTTP/WebSockets) for robust testing

• Mentored junior engineers and supported onboarding

More broadly, I focused on building scalable data applications, improving developer workflows, and contributing to product quality at scale.