
Claims ops software for messy bundles: classify files, extract cited fields, review low-confidence outputs, and generate artifacts.
I like building AI agents around messy human workflows. Most of my work starts with scattered docs, sales calls, spreadsheets, or operational chaos. I turn that into full-stack software, automations, and agent workflows that help people get work done with more clarity.
Currently building with AI to learn and explore what AI-native work actually looks like.

Claims ops software for messy bundles: classify files, extract cited fields, review low-confidence outputs, and generate artifacts.

AI CRM harness for sessions, CRM tools, files, memory, approvals, Telegram workflows, browser tasks, and evaluator traces.

AI GTM systems: scrape TAMs, enrich accounts, score fit, verify contacts, draft briefs, and route qualified leads.

LLM wiki for company memory: immutable sources, agent-maintained markdown, index/log workflows, Notion state, and reviewed updates.
Singapore
Building reviewed AI systems across legal docs, CRM, GTM, company memory, and order intake.
San Francisco
Mapped enterprise intake and prior-auth workflows, including review flows that reduced manual staffing needs from ~14 to ~3.
Singapore, San Francisco, Australia
Built AI GTM systems for 8 startups, generating $1M+ pipeline and $200K revenue.
Singapore
Second outbound hire for Singapore expansion; hit 200%+ quota and closed 22 logos.
Singapore, APAC
Built seed-to-Series A enterprise traction from $0 to $450K ARR and closed 9 super-app partnerships.
Wolfson College
Graduated top 10%; machine-learning sentencing dissertation awarded First Class.