Technical Product Manager
Two SaaS products, built and shipped solo.
Satiaphic handles team feedback operations: ingest, triage, find recurring themes, close tickets. Expenra runs multi-org accounting with real banking sync and an AI assistant over your actual numbers. Both are live.
What I bring to a team
Product
I research before I scope. For Satiaphic that meant going through 20 tools to find where the gap actually was. For Expenra it meant mapping multi-org finance workflows that most tools skip because they are annoying to build.
Delivery
I have shipped twice without a team. That means I know what slips, why estimates break, and which decisions cause problems six months later. At Osmogen I ran creator campaigns and timelines with no engineering backup.
Implementation
I wrote the code. Next.js apps with authenticated workspaces, RBAC, multi-tenant scoping, billing, API routes, and deployment. I can read a pull request and push one.
Selected Work
Selected work
Feedback intelligence
Satiaphic
Teams that collect customer feedback but never close the loop on it. Ingest, triage, find themes, create work items, track resolution.
20
Tools researched
189
Commits
3
User Roles
6-stage
AI Pipeline
Small-business accounting
Expenra
Multi-org accounting where each organization gets its own workspace, transaction history, and access control. Banking sync through Plaid. An AI assistant that answers questions against real numbers.
Multi-org workspace architecture
Stripe + validated webhooks
Plaid banking sync
Multi-model AI assistant
Capabilities
How I work
01
Research and scope
Before writing a line of code for Satiaphic, I compared 20 tools across four categories. I was trying to find where the actual gap was. For Expenra, I mapped multi-org finance workflows that most accounting tools ignore. The research is how I decide what gets built, not a phase I complete and hand off.
02
Shipping through implementation
Both products have authenticated workspaces, RBAC, multi-tenant data scoping, billing, API routes, and deployment. I stayed in the code through launch because a PM who can read the implementation catches problems before they become bugs.
03
AI workflows
Satiaphic runs a six-stage pipeline: LLM topic extraction, then deterministic clustering. The model handles extraction. Grouping and execution stay in product code. That split was a deliberate call, not a default.
04
Launch readiness
Onboarding, access tiers, billing, and release prep. Tradeoffs get documented in the same project they are made.
Skills
Skills
Product and research
Delivery and systems
AI & Automation
Frontend
Backend & architecture
Tools
Background
Background
11/2025 – Present
Satiaphic (solo project)
Feedback intelligence SaaS. Competitive research, workflow design, six-stage AI pipeline, billing, multi-tenant access control. Live at satiaphic.com.
03/2024 – Present
Expenra (co-founded)
Small-business accounting SaaS. Multi-org workspaces, Stripe, Plaid banking sync, multi-model AI assistant. Live at expenra.com.
01/2022 – 12/2023
Digital Marketing and Partnerships Manager, Osmogen
Creator partnerships, campaign tracking, recurring content deals with mid-tier creators (50K–200K followers). Ran timelines and stakeholders with no engineering support.
09/2020 – 09/2025
BEng, Telecommunications and Information Engineering, Helwan University
IEEE Systems Design Competition, 2nd place out of roughly 100 teams.