Sam

I build AI-native products end to end.

Senior product manager. Six years fixing growth, activation and retention problems at B2B SaaS and marketplace companies across MENA — now architecting multi-agent workflows that ship production software, spec to deployed product.

Cairo · Working across MENA, EMEA and GCC

Selected work

Orvo AI Ltd · 2026

Orvo Intelligence

AI brand monitoring across Arabic and English

Built the full product: data model, signal taxonomy, analytics layer, and an AI chat interface over noisy multi-source MENA data. Scraping and enrichment pipeline on Trigger.dev, verified end to end at 121 signals with zero errors. Automated reporting out to PDF and PPTX.

Orvo AI Ltd · 2026

A multi-agent system that ships production software

Architected a Director → Builder → Review workflow where agents plan, build, test and deploy via Claude, Supabase, Vercel, GitHub and Linear — no manual code. The review gate exists because the first version reported successful completion on work it hadn't performed. I built isolated verification to prove real execution before anything deploys.

Crowd Analyzer · 2025

Search success rate +15%. AI iteration cycles −45%.

CA-Pilot

plain English into complex Boolean queries

Enterprise analysts were losing insight to query syntax. Shipped an LLM assistant that converts natural language into structured Boolean logic, plus a validation protocol with QA and Data Science for model releases.

Crowd Analyzer

Churn 30% → 22%. A 27% reduction.

Churn from 30% to 22% in 90 days

The product worked; the request pipeline didn't. No prioritization logic, no segmentation, no SLA — so CX couldn't tell anyone when their issue would be resolved. Built a customer health scoring engine on four weighted factors, surfaced live in Metabase, and a request prioritization engine on top of it.

Crowd Analyzer

Conversion 30% → 50% in three months. A 67% lift. No discount.

Trial-to-paid from 30% to 50%

The team's instinct was that the price was too high. It wasn't — it was indefensible, with no logic anchoring it to the market. Rebuilt pricing off a full competitive analysis, stress-tested against company financials, and cut trial quota burn with a Boolean query methodology for CX so trial users saw the product at its ceiling instead of burning out on noise.

Fanni

Cancellations −25% in one quarter.

An AI risk model that cut cancellations 25%

Orders were failing late, when recovery was impossible. Built a risk scoring model on historical and behavioral signals that flagged high-probability cancellations early enough for Ops and CX to intervene.

Results

−60%

data costs

+40%

engagement

+70%

SLA

+35%

profit

+40%

BNPL activation

My Playground

Three products I built from scratch, alone, in my free time. No team. No budget. Just curiosity and too many late nights.

Writing

Soon

Build teardowns

Soon

PM × AI

Soon

The diagnosis pattern