How to Deploy a Computer Vision Model to Production
Most CV tutorials end at model training. This guide covers every layer I put in place before any vision model goes live: API design, containerisation, versioning, monitoring, and cost optimisation.
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18 articles
Deep technical articles on building production AI systems: computer vision, real-time IoT, LLM pipelines, and MLOps. Written from 6+ years of shipping software and AI in production.
Articles Published18
Avg Read Time~12 min
TopicsAI · IoT · MLOps
Taking on new engagements
Need this built
to survive production?
I take on project-based engagements, from architecture reviews and LLM pipeline audits to full production builds, plus fractional CTO work.
AI SystemsComputer VisionLLM PipelinesMLOpsIoT & BLE
6 P@SHA ICT Awards · 23 products shipped · 80+ clients
Building Real-Time IoT Systems with BLE and WebSockets: Lessons from 200Hz+ Sensor Streaming
The hardest part of building wearable tech isn't the AI. It's the 200 milliseconds between the sensor and the screen. Four years of lessons from production IoT systems: BLE reconnection, protocol selection, edge preprocessing, and monitoring.
LLM-Powered Real-Time Audio Pipelines: How I Built AI Transcription at Scale
Most developers think the hard part of voice AI is the speech-to-text model. It isn't. The hard part is everything around it. The audio ingestion pipeline, the LLM classification layer, the WebSocket architecture, and the operational infrastructure that keeps it all running under production load.
My Production Deployment Checklist for AI Systems: What I Check Before Every Launch
Every item on this checklist exists because I once shipped without it. Seven layers (crash reporting, analytics, UX feedback, bug tracking, infrastructure monitoring, device fingerprinting, and CDN) that I now run before any AI system goes live.
RAG Architecture in Production: Building a Research Intelligence System with ChromaDB and BM25
Production RAG fails in specific ways the tutorials skip. I built PaperIntel, a research intelligence system with citation-level accuracy, using hybrid retrieval, cross-encoder reranking, and systematic evaluation. This is what the full architecture actually looks like.
Model Quantization for Production: How I Cut Inference Cost by 60% Without Touching Accuracy
Your production AI model is probably 4x bigger than it needs to be. I reduced inference time from 340ms to 91ms and cut monthly cloud costs by 60% using INT8 quantization, without changing a single model layer. Here's the full pipeline.
Monolith to Microservices: How I Achieved 3x Throughput on a Live Production System
Most microservices migrations are driven by architectural fashion rather than specific engineering pain. Ours was driven by a measurable scaling problem. This is the story of migrating a live platform without downtime, what broke in ways we didn't anticipate, and what 3x throughput actually looks like.
YOLOv8 in Production: Building a Multi-Camera CCTV Anomaly Detection System
YOLOv8 benchmarks are well documented. What's not documented is what happens when you process 8 simultaneous CCTV feeds in real time, apply zone-based business rules, and deliver WebSocket alerts under 200ms while keeping false positives low enough that security staff actually trust the system.
How Much Does a Fractional CTO Cost in 2026? (A Working CTO's Honest Breakdown)
Pricing pages are vague and sales calls are worse. As a working CTO who also takes fractional engagements, here is how the market actually prices advisory, embedded, and project-based CTO work in 2026, and when hiring one is the wrong call.
Scaling High-Frequency Sensor Data with FastAPI and PostgreSQL: 200Hz Without Falling Over
Most backends die the moment wearables start streaming at 200Hz. Here is the exact architecture I used to take a clinical rehab platform to 500+ concurrent sensor sessions with sub-100ms latency: batching, backpressure, WebSockets vs UDP, and the PostgreSQL patterns that survive.
RAG vs Fine-Tuning: What I Tell Clients Who Want "ChatGPT for Their Data"
It is the most common request in AI consulting: "we want ChatGPT, but on our documents." Nine times out of ten the answer is RAG, not fine-tuning, but the tenth case matters. Here is the decision framework I use with clients, from someone who has shipped both.
Fractional CTO vs Technical Co-Founder: Which Does Your Startup Actually Need?
One costs cash, the other costs 10-40% of your company. Founders regularly pick wrong in both directions. A working CTO’s honest comparison: commitment, cost, equity, and the questions that decide it.
AI Consultant vs AI Engineer vs ML Engineer: Who Should You Hire?
An ML engineer costs $150-250k a year and takes three months to hire. An AI consultant ships a working prototype in two weeks. Both are the right answer to different problems. Here is the decision framework, from someone who has been on both sides of it.
Building Offline-First Mobile Apps That Never Lose Data (React Native + WatermelonDB)
Most "offline support" is a cache and a prayer. Building Apex Rider, a motorcycle tour app whose users are definitionally out of coverage, forced the real thing: local database as source of truth, sync as a background detail, and data loss as an engineering decision.
Voice AI for Hotels: How I Replaced Walkie-Talkies With Real-Time AI
Hotels run on radio chatter: unstructured, unrecorded, unrouted. The QuickComm build turned that audio into transcribed, classified, routed events: 94% transcription accuracy on noisy radio, ~45% faster staff response, at about $3/month per property. Here is the architecture.
Fractional CTO for Non-Technical Founders: What They Do and When You Need One
You have the idea, the customers and the pitch, but nobody on the team who can judge a technical decision. Here is what a fractional CTO actually does for a non-technical founder, what it costs, and the warning signs that you need one now.
Fractional CTO in Dubai and the UAE: Cost, Options and How to Hire One
Dubai startups are under pressure to ship fast with lean teams, and a full-time CTO is one of the most expensive hires in the city. Here is what a fractional CTO in Dubai and the UAE costs, the remote and local options, and how to make Gulf-hours collaboration work.
Working With AI, Not Under It: Trust and Accountability in Generative AI
Our peer-reviewed paper on generative AI in cybersecurity is out in the International Journal of Advanced Research. Here is what it argues, the seven propositions in plain words, and how the same ideas already shape the AI systems I build.