We Build AI Systems That Ship
From large language models to computer vision pipelines, we engineer production-grade AI systems. Our team writes the code, trains the models, and deploys the infrastructure that powers intelligent enterprise software.
Our Technology
Full-Stack AI Engineering
We don't just advise — we build. Our engineers design, code, and deploy production AI systems from model training to cloud infrastructure.
LLM Development & Fine-Tuning
Custom large language models fine-tuned on your domain data. RAG pipelines, prompt engineering frameworks, and multi-agent systems built for production scale and reliability.
Computer Vision & Perception
Real-time object detection, image segmentation, OCR, and video analytics. We build vision models deployed on edge devices, cloud GPUs, and embedded systems for manufacturing, security, and healthcare.
MLOps & AI Infrastructure
End-to-end ML pipelines with automated training, versioning, monitoring, and deployment. We build on Kubernetes, Ray, and custom orchestration layers for GPU-accelerated workloads at scale.
Data Platforms & Pipelines
High-throughput data ingestion, feature stores, vector databases, and real-time streaming architectures. We engineer the data backbone that feeds your AI systems.
AI Safety & Evaluation
Systematic model evaluation, red-teaming, guardrails engineering, and compliance tooling. We build safety into the system architecture — not as an afterthought.
API & Integration Engineering
RESTful and gRPC APIs, SDK development, webhook systems, and enterprise integrations. We make your AI models accessible to every part of your tech stack via clean, documented interfaces.
Case Studies
Systems We've Shipped
Production AI systems running in the real world — processing millions of requests, cutting latency, and driving measurable outcomes.
AI-Powered Personalisation Engine
A leading Hong Kong retail group integrated our recommendation engine across their online and offline channels. The AI analyses customer purchase history, browsing behaviour, and demographic data in real-time to deliver personalised product suggestions, dynamic pricing, and targeted promotions.
Intelligent Risk & Fraud Detection
We deployed a real-time fraud detection system for a regional bank processing over 2 million transactions daily. The ML model analyses transaction patterns, device fingerprints, and behavioural biometrics to flag suspicious activity within milliseconds — reducing false positives by 70% while catching 95% of fraudulent transactions.
Predictive Maintenance & Quality Control
For a Guangdong-based electronics manufacturer, we built an IoT + AI system that monitors 500+ sensors across production lines. The model predicts equipment failures 72 hours in advance and uses computer vision to detect product defects at 99.7% accuracy — eliminating unplanned downtime and reducing scrap rates.
AI-Assisted Diagnostic Imaging
We partnered with a private hospital network to develop a deep learning system that analyses X-rays, CT scans, and MRIs. The AI acts as a second pair of eyes for radiologists — highlighting potential abnormalities and prioritising urgent cases, reducing diagnostic turnaround time from 48 hours to under 4 hours.
Smart Demand Forecasting & Route Optimisation
A cross-border logistics company used our AI platform to forecast demand across 12 Asian markets and optimise delivery routes dynamically. The system integrates weather data, holiday calendars, trade volumes, and real-time traffic to reduce delivery times and warehouse overstocking — saving $4.2M annually.
Multilingual AI Customer Service Agent
We built a GPT-powered conversational AI agent for a telecoms provider that handles customer enquiries in English, Cantonese, and Mandarin. The system resolves 78% of tickets without human intervention, understands intent across languages, and seamlessly escalates complex cases to human agents with full context.
Why Aspire AI
Engineers First. Results Always.
We're a team of ML engineers, systems architects, and research scientists — not consultants with slide decks. Every member of our team writes code, trains models, and ships production systems.
Our tech stack spans PyTorch, TensorFlow, CUDA, Kubernetes, and every major cloud provider. We've deployed models processing billions of requests across fintech, healthtech, and industrial automation.
How We Ship
From Prototype to Production
An engineering-driven workflow with 2-week sprints, continuous integration, and rapid iteration. Ship fast, measure, improve.
Scope
Audit your data, infrastructure, and technical requirements. Define the system architecture, model specs, and success metrics.
Build
Train models, write inference pipelines, build APIs. Agile sprints with working demos every 2 weeks. Code reviewed and tested continuously.
Deploy
CI/CD pipelines push models to production. Load testing, canary deployments, and automated rollback. Zero-downtime releases.
Optimise
Monitor model drift, optimise inference costs, A/B test improvements. Continuous performance tuning with real production data.
Our Team
Built by Engineers, for Engineers
Researchers and engineers from top tech companies and labs, shipping production AI systems at scale.
Jacky Cheung
Founder & CEO
Serial tech entrepreneur with 3 successful exits. Former engineering lead at Google Brain and DeepMind. PhD in Computer Science from MIT. Built AI systems serving 100M+ users.
Dr. Rachel Lam
Chief Technology Officer
PhD in Machine Learning from Stanford. Former principal engineer at Microsoft Research Asia. Leads our LLM and NLP engineering. Published 30+ papers at NeurIPS, ICML, and ACL.
Kevin Tsang
VP of Engineering
Ex-Meta and Stripe. 12 years building distributed systems at scale. Leads our MLOps, infrastructure, and platform engineering. Kubernetes contributor.
Vivian Ho
Head of AI Research
Ex-Alibaba Cloud and SenseTime. Expert in computer vision, generative models, and multi-modal AI. MSc from Imperial College London. Kaggle Grandmaster. 15+ patents filed.
Client Feedback
What Our Clients Say
Aspire AI's engineers built us a real-time fraud detection pipeline processing 2M+ transactions daily. Their code quality is exceptional — clean, well-tested, production-ready from day one.
They deployed our computer vision system on 200+ edge devices across our factories in 8 weeks. Model inference runs at 15ms per frame. Their MLOps setup means we can retrain and redeploy in hours, not weeks.
Their LLM fine-tuning work was game-changing. Our customer service AI now handles 78% of tickets in 3 languages with zero hallucination issues. The engineering rigour they brought was unlike any vendor we've worked with.
Pulse
Trending Right Now
The latest trending topics across AI, technology, and finance — aggregated from social media and news.
Frequently Asked Questions
Everything You Need to Know
What industries do you work with?
How long does a typical AI project take?
Do we need a large dataset to get started with AI?
What is your pricing model?
How do you ensure AI solutions are ethical and compliant?
Can you work with our existing technology stack?
Ready to Build?
Let's Ship Your AI System
Talk to our engineering team about your AI project. We'll scope the architecture, estimate timelines, and show you what's possible with your data.