Production-grade AI — beyond the hype
Custom AI, LLM applications and machine-learning systems that automate workflows, personalise experiences and unlock insights. Real production deployments, not demos.
AI you can put to work today
From chatbots and RAG apps to full agent teams — solutions that actually ship.
LLM Apps & Chatbots
Custom GPT, Claude and Gemini-powered chat, RAG, and knowledge assistants for your business.
- Multi-LLM (GPT, Claude, Gemini)
- Retrieval-augmented (RAG)
- Function calling & tools
- Streaming UX
AI Agents & Automation
Multi-step agents that take goals, call tools and deliver finished work — 24/7.
- Research & content agents
- Ops & bookkeeping agents
- n8n, Make.com, Zapier
- Human-in-the-loop
Semantic Search & RAG
Vector search over your docs, tickets and product data — with cited answers.
- Pinecone, Weaviate, pgvector
- Chunking & re-ranking
- Cited responses
- Hybrid keyword + vector
Predictive ML
Custom ML for forecasting, churn, credit, pricing and personalisation.
- Forecasting & churn
- Recommenders
- Anomaly detection
- MLOps deployment
Computer Vision
Image, video and document understanding — OCR, classification, detection and generation.
- OCR & document parsing
- Object detection
- Video analysis
- Vision LLMs
MLOps & Infra
Production-grade infra so your models run reliably, cheaply and safely at scale.
- LLMOps monitoring
- Cost & latency tuning
- Model gateway (LiteLLM)
- Security & guardrails
AI done the responsible way
Every AI system we ship is evaluated, monitored and safe — not a black box.
Multi-model
Best model per task — GPT, Claude, Gemini, open.
Your data, private
Self-hosted vector DBs, no vendor training.
Guardrails
PII redaction, prompt-injection defence.
Evaluation
Automated evals catch regressions before users do.
Cost-optimised
Model routing, caching, batching — 50-80% cheaper.
Composable
Modular tools, agents and pipelines.
Documented
Prompt library, runbooks and eval sets you own.
Human-in-the-loop
Review workflows for high-stakes outputs.
From idea to reliable production
A pragmatic AI delivery process — no science-project timelines.
Use-case scoping
Pick problems where AI has clear ROI — not everything needs an LLM. Written business case.
Data & retrieval
Sources identified, chunked, embedded and indexed. Retrieval quality proven before app work.
Prompt & eval sets
Prompts, tool schemas and automated evaluation sets — the tests for your AI system.
Build & integrate
App, agent or automation built and wired into your stack (Slack, HubSpot, CRM, DB).
Guardrails & security
Prompt-injection defence, PII redaction, rate limits and audit logging.
Deploy & monitor
Production launch with LLMOps observability, cost monitoring and continuous eval.
The AI stack
The best models, tools and infra — chosen per use case, never locked-in.
Frequently asked
How is this different from just using ChatGPT?
ChatGPT is a general chatbot. We build AI systems tuned to YOUR data, YOUR workflows and YOUR business logic — integrated with your stack, evaluated, monitored and safe for production.
Will you train custom models?
Only when it's justified. Modern LLMs plus RAG solve 95% of use cases without fine-tuning. When fine-tuning genuinely helps, we do it — with your data, your infra.
How do you handle privacy and data security?
Enterprise LLM providers with zero-retention agreements, self-hosted vector DBs, PII redaction, and — where required — fully on-prem open-source models.
How much does an AI project cost?
Prototypes from HK$40K. Production AI apps typically HK$150K–500K. Full AI agent teams and platforms HK$500K+. Fixed quote after scoping.
How fast can you ship something usable?
Working prototype in 2–4 weeks. Production deployment in 6–12 weeks. Continuous improvement thereafter.
Do you offer ongoing AI ops?
Yes — LLMOps retainers cover monitoring, cost optimisation, model updates and eval maintenance as models and prompts evolve.