From knowledge retrieval to end-to-end automation, we design and deliver AI systems ready for real production use.
Enterprise Retrieval-Augmented Generation solutions that combine large language models with your private, verified documents. Secure, grounded, and auditable for internal use.
Full ingestion workflow for PDFs, Office files, scans, and images. OCR, layout analysis, smart chunking, and metadata enrichment using tools like MinerU and DeepSeek-OCR.
HR assistants, IT helpdesk, policy copilots, and customer-facing chatbots — all powered by your internal knowledge, with access control and audit logs.
Image understanding, form recognition, ID and document extraction, invoice reading, and industrial inspection for cameras and scanned content.
Speech-to-text and text-to-speech microservices using models like Whisper and custom TTS engines. Designed for Cantonese, English, Mandarin, Japanese, Korean and more.
Turn repetitive work into automated AI flows: document classification, approvals, report generation, compliance checks, and notification routing.
Private LLM hosting on your own GPUs: GPT-OSS, Qwen, Llama, DeepSeek, embeddings, and vision models — with monitoring, scaling, and lifecycle management.
Fine-tune models with your historical chats, tickets, documents, and domain examples to improve accuracy and tone while keeping data private.
Multilingual RAG, translation workflows, and user interfaces that support English, Traditional Chinese (HK), Simplified Chinese, Korean, Japanese, and more.
Metrics, dashboards, prompt logs, GPU monitoring, and error tracing using Prometheus, Grafana, and GPU observability tools.
Deploy AI to locations with limited connectivity — factories, warehouses, IoT gateways — with synchronization and local inference.
Connect AI services to ERP, CRM, HR systems, ticketing tools, email, SharePoint, and custom APIs to fit your existing environment.
A practical, step-by-step approach from idea to stable production deployment.
We review your current systems, data sources, constraints, and user journeys to propose concrete AI use cases.
A working prototype with your real data, evaluation metrics, and clear success criteria before large-scale rollout.
Hardening, security, monitoring, and ongoing support to keep your AI stack reliable and cost-efficient.