Products shipped, measured, and trusted.

Work impact in production, and personal builds where I prototype what production AI could look like next.

01 · Work Impact

Shipped in production · each opens into a full case study

Real Estate Fintech · Series D · Current

80% of requests under 10 minutes

0→1 B2B wholesale lending, 45% adoption in 6 months.

Shipping AI into mortgage operations where every output meets compliance

·Grew organic traffic 10,737% (18.7K to 2M monthly visits in 3 months) by owning analytics for a programmatic content expansion, then built the funnel instrumentation that turned it into qualified mortgage pipeline
·Took a B2B wholesale product 0 to 1: 45% adoption in 6 months, 80% of requests served in under 10 minutes
·Built AI research agents (Claude, n8n) that cut research cycle time 60% (20 hrs/week to 4), with evals designed and output monitored in production
·Designed an LLM-powered Smart Product Advisor across BBYS, Instant Equity, and FCO that replaced manual sales-to-product Q&A with instant self-serve answers
·Shipped an internal sales tool with full RBAC, removing 24 hours from top-of-funnel conversion

Climate SaaS · Series A · Founding Product Manager

30% enterprise adoption

Turning a regulation into a product a non-technical team would open on a Monday.

·Sole product leader directing a cross-functional team of 9 from discovery through delivery
·Drove 30% enterprise adoption by turning GHG Protocol and CBAM into self-service analytics non-technical teams would actually use
·Secured a Microsoft for Startups partnership (~£160K Azure credits) through a joint program with Accenture
·Ran 18 customer discovery interviews across North America and Europe to define ICP and validate PMF

Climate Tech · Founding PM

100+ analyst hours saved / month

Building ESG intelligence an auditor would accept.

·Built and shipped LLM-powered ESG risk dashboards (LangChain, OpenAI, Node.js) tracking Scope 1/2/3 emissions across 20M+ sq ft of institutional real estate
·Saved 100+ analyst hours a month, becoming the primary decision tool for enterprise clients
·Built a conversational Q&A layer over live emissions data, a first in the space
·Designed the evaluation and observability framework for LLM outputs before enterprise deployment, leading a team of 10+

Mortgage Fintech · Public · Team Lead → Product Analytics Lead

21 → 12 days

Cutting nine days out of the loan cycle.

·Cut the full lock-to-fund cycle from 21 days to 12 through internal tooling and process redesign
·Built an AI-based OCR tool for document ingestion that removed manual data entry and cut turnaround by 48 hours
·Led a team of 20 across mortgage workflows: CSAT +12%, containment +18%, NPS +9
·Owned 4 data products (SQL, Looker) used by 700 people daily across 4 teams, driving a 1.9% conversion lift (~$1.3M a month)

02 · Personal Builds

Side projects, buildathons, capstones

Where I prototype what production AI could look like next.

Currently Building

Details coming soon

Coming Soon

Next case study in progress