I build AI into products end-to-end — from LLM pipelines and agent systems to the backends, mobile apps, and infrastructure that run them in production.
📹 Watch Portfolio Loom (90s) · 🐙 github.com/johnmoses
10,000+ users · FastAPI + Flutter + Next.js · AWS Lightsail · $20/month
A full-stack attendance reporting platform for hierarchical church organizations (Fellowship → Zone → District → Region → State). Built offline-first — works without internet, syncs when connected.
AI highlights:
- Voice capture pipeline — chunked MediaRecorder with real-time regex extraction per chunk for instant UX, then a final LLM pass at session end for accuracy. Handles Nigerian multilingual input (Hausa, Yoruba, Igbo, Efik, Idoma)
- Attendance anomaly detection — flags consecutive member absences (≥3) and center-level drops (≥30%) across all centers automatically
- Outreach intelligence — engagement scoring (attendance 35% + recency 30% + interactions 20% + stage 15%), churn prediction, and message variant generation by tone
- Statistical trend analysis — Redis-cached insights with cold-start handling for new centers
DevOps highlights:
- ADR-driven deployment decisions documented before any infrastructure was touched
- Docker Compose with per-service memory limits (384MB), PostgreSQL tuned for a $20 Lightsail instance
- GitHub Actions CI/CD, Nginx reverse proxy, fail2ban hardening, kernel-level SYN flood protection
- Sliding window rate limiter (5000 req/min general, 1000 req/min auth) with real IP extraction behind proxy
Code excerpts:
- Voice capture pipeline — hybrid inference, multilingual NLP, offline resilience
- Anomaly detection agent — autonomous absence + drop detection
- Offline-first sync — Flutter + Next.js dual-layer queue
- Production infrastructure — Docker, Lightsail, hardening, rate limiting
- Outreach AI — engagement scoring, churn prediction, priority queue
Pre-AI-era foundation (built without AI assistance):
- Custom transformer fine-tuning — BERT intent classifier (44 classes, 87.5% accuracy) + T5 text-to-SQL (ROUGE-L 0.961) + PEFT/LoRA on consumer hardware
- Conversational agent — multi-turn dialog state machine with entity extraction and autonomous DB writes (agentic pattern before LangChain existed)
FastAPI + Flutter + Next.js · PostgreSQL + Redis · Docker · Railway
A full-stack B2B/B2C commerce platform connecting manufacturers, distributors, retailers, and shoppers across Nigeria and West Africa. Incubated in Abuja with 20+ live retailers, scaling to the Lagos industrial corridor.
AI highlights:
- 5 agentic AI modules — Smart Reorder, Supplier Intelligence, Price Optimization, Inventory Advisor, Product Recommendations (collaborative filtering, auto-retrains every 24h)
- Arbitrage engine — 3-layer price scanner (internal + market scouts + external), landed cost calculator (product + shipping + customs + last-mile), opportunity scorer (0–100 composite)
- Borderless logistics AI — route optimization (Haversine), rider matching (composite scoring), demand forecasting (hourly heatmaps), dynamic surge pricing
- Social intelligence signals — tier-specific feed items generated from live transaction data for 3 user tiers (Connect / Trade / Supply)
Full-stack highlights:
- 3-provider payment routing (Paga / Paystack / Flutterwave) — intelligent routing saves 45% on processing costs
- Escrow with milestone releases for B2B, wallet system for instant settlements
- 7-level ambassador engine with anti-fraud detection and dormancy downgrade
- Recursive CTE for hierarchical center filtering across unlimited org depth
Private repo — architecture overview.
| Repo | What it covers |
|---|---|
| llm-foundations | LLM internals, fine-tuning, prompt engineering, inference optimization |
| rag-foundations | RAG pipelines, vector stores, chunking strategies, retrieval evaluation |
| ai-agents-foundations | Agent loops, tool use, multi-agent coordination, autonomous control |
| mcp-foundations | Model Context Protocol — building and consuming MCP servers |
| Repo | What it covers |
|---|---|
| ultra-learning | AI-powered adaptive learning system — Flask API (LLM + RAG + MCP) · Next.js web · React Native mobile |
| sure-health | Multi-party AI healthcare platform — Flask API (agents + LLM + RAG) · Next.js web · React Native mobile |
| easy-finance | AI-powered financial platform — FastAPI (wealth + community + security services) · Next.js web · React Native mobile |
| zero-to-hero-python-ai | End-to-end ML/AI roadmap — CNNs, RNNs, Transformers, LLMs, Agentic AI |
| Repo | Credential |
|---|---|
| coursera-nlp-specialization | Coursera NLP Specialization |
| coursera-mlops-specialization | Coursera MLOps for Production |
| coursera-ai-4-medicine-specialization | Coursera AI for Medicine |
| Repo | What it covers |
|---|---|
| jenkins-docker-compose-flask | Jenkins CI/CD with Docker Compose |
| jenkins-docker-flask | Jenkins + Docker pipeline |
AI/ML: LLMs · RAG · AI Agents · MCP · Transformer Fine-Tuning (BERT, T5, PEFT/LoRA) · Collaborative Filtering · Time-Series Forecasting · NLP · Computer Vision
Backend: FastAPI · Flask · PostgreSQL · Redis · SQLite · REST · WebSockets
Frontend: Next.js · TypeScript · Tailwind CSS · React
Mobile: Flutter · Dart · React Native · Offline-first (SQLite + sync queue)
DevOps: Docker · GitHub Actions · AWS Lightsail · Railway · Nginx · fail2ban
📧 johnmosesng@gmail.com · 🐙 github.com/johnmoses · 📹 Loom Portfolio