I build AI-enabled workflows for asset-management teams — process mapping, requirements, tooling, regression-tested implementation, and adoption support. My focus is the operational layer between portfolio managers and the data: compliance review, attribution, research extraction, and the long tail of admin work where practical AI actually pays off.
Hyperscaler → Supplier Attribution
A working prototype of an AI-enabled research workflow for asset-management analysts. Pulls $400B+ of annual hyperscaler capex directly from SEC EDGAR filings, runs Claude-CLI structured extraction over earnings transcripts, and routes the dollars through to specific supplier exposure via a transparent attribution model. Every figure is source-linked back to its filing — auditable end-to-end. The “Ask the Analyst” chatbot is grounded in the curated dataset, demonstrating a Human + AI design where the model assists rather than replaces analyst judgment.
Workflow-aware document review for regulated teams
A document review and approval platform for small regulated teams — built around the workflow itself, not the document. Every artifact moves through a defined review sequence with role-based approvals, parallel stages, change-request paths, and a complete audit trail. The wedge over generic e-signature or CLM tools: workflow-aware compliance evidence. AI review hooks plug into the stage state, so model-assisted checks become a controllable step rather than an opaque pre-process.