Our core services
Predictive analytics and forecasting
We build time-series and regression models that forecast business metrics: sales volume, inventory demand, customer lifetime value, equipment failure probability. The models run on your own infrastructure or on a managed cloud instance we set up for you.
A typical engagement starts with four to six weeks of data preparation and model training, followed by a two-week validation period where we compare predictions against actual outcomes. Once accuracy meets the agreed threshold, we deploy the model behind an API your existing systems can call.
- Demand forecasting for retail and distribution
- Churn prediction for subscription businesses
- Financial metric projection (revenue, cash flow)
- Predictive maintenance for manufacturing equipment
Document intelligence and data extraction
Paper documents and PDFs still drive a surprising amount of business in Hong Kong. We build pipelines that combine optical character recognition (OCR) with natural language processing to pull structured fields from invoices, purchase orders, contracts and shipping documents.
Our system handles both English and Traditional Chinese text. For mixed-language documents, we use a dual-model approach: one model identifies text regions and language, and a second model extracts the relevant fields. Accuracy on clean scans typically exceeds 96%; for lower-quality images we add a confidence flag so your team only reviews the uncertain ones.
- Invoice and receipt data extraction
- Contract clause identification
- Shipping manifest parsing (BL, packing lists)
- Automated filing and categorisation
Computer vision systems
We develop image and video analysis models for quality inspection, object counting and safety monitoring. These models run on edge devices (Nvidia Jetson, industrial PCs) or in the cloud depending on latency requirements.
One recent project involved a garment manufacturer in Shenzhen who needed to detect stitching defects on a production line running at 120 pieces per hour. We trained a YOLOv8-based detection model on 4,200 annotated images and deployed it on two Jetson Orin modules mounted above the conveyor. The system flags defective items in under 200 milliseconds, fast enough for the line speed.
- Defect detection on production lines
- People counting and occupancy monitoring
- License plate recognition for parking systems
- Retail shelf analysis (stock levels, planogram compliance)
Conversational AI and chatbots
We build task-oriented chatbots that handle customer inquiries, internal helpdesk tickets and appointment scheduling. These are not generic FAQ bots. Each one is trained on your actual knowledge base and connected to your backend systems so it can look up order status, check availability or create support tickets in real time.
We support deployment on WhatsApp Business API, WeChat Official Account, web widgets and Microsoft Teams. The bot understands English and Cantonese (written), and we can add Mandarin if needed. Average setup time is three to five weeks, including knowledge base ingestion and testing.
- Customer service bots (order tracking, returns)
- Internal IT helpdesk automation
- Appointment and reservation booking
- Lead qualification for sales teams
Data pipeline engineering
AI models are only as good as the data feeding them. We design and build the infrastructure that moves data from source systems (databases, APIs, file drops) through cleaning and transformation stages into a format your models can consume.
We work with PostgreSQL, BigQuery, Snowflake and MongoDB on the storage side, and Apache Airflow or Prefect for orchestration. If you already have a data warehouse, we integrate with it rather than replacing it. Our pipelines include monitoring dashboards that alert your team when data quality drops below a defined threshold.
- ETL and ELT pipeline design
- Data quality monitoring and alerting
- Real-time streaming with Kafka or Pub/Sub
- Data warehouse setup and optimisation
Engagement models
We offer two ways to work with us. Both include the same engineering team and the same quality standards; the difference is in how scope and billing are structured.
Fixed-scope project
Best when you have a clear problem and dataset. We agree on deliverables, timeline and price before writing a single line of code.
- Defined milestones with acceptance criteria
- Pay per milestone, not per hour
- Typical duration: 6–14 weeks
- Includes 30 days of post-launch support
Retained partnership
Best for ongoing work: model retraining, new feature development, data pipeline maintenance. You get a dedicated allocation of engineering hours each month.
- Monthly allocation of 60–160 engineering hours
- Priority response (under 2 hours during office hours)
- Quarterly performance reviews
- Cancel with 30 days notice
Not sure which service fits?
Describe your situation and we will tell you which service (or combination) makes sense. No commitment required.
Talk to us