Data lives in too many places
Customer, order, finance and support data are split across old systems, spreadsheets and chat threads.
Hong Kong · Asia-Pacific · Business systems · Controlled AI
Modernise old systems. Add AI where work actually happens.
We help growing companies rebuild CRM, ERP, data and operations workflows into usable software with clear permissions, audit trails and practical automation.
First release
4-6 weeks
AI use
Search + action
Deployment
Client cloud
Markets
HK · APAC
Focus
CRM · ERP · AI
01
The problem is usually not simply “we need AI”.
Managers cannot see what is stuck
Approvals, tickets and exceptions exist somewhere, but nobody can quickly answer what is delayed and why.
Legacy systems slow down growth
Old CRM and ERP screens force teams into manual checks, duplicated input and vendor-only changes.
AI demos do not reach operations
A generic chatbot can summarise documents, but cannot safely update records, request approval or leave an audit trail.
02
Useful software first. AI where it fits.
Start with one workflow that wastes time every week. We ship a focused first version, measure use, then extend from there.
Build 01
CRM and ERP modernisation
Assess, refactor, cloud-deploy and integrate existing business systems without forcing a risky full replacement on day one.
Build 02
Data integration and business insight
Connect fragmented operational data into a unified customer and operations view for management decisions.
Build 03
Controlled AI modules
Introduce churn prediction, demand forecasting, smart reports, anomaly alerts and workflow suggestions around real business data.
Build 04
Cross-platform automation
Integrate e-commerce, marketing, customer service, finance and internal systems with monitoring and exception handling.
03
AI belongs in workflows, not slide decks.
Ask the business, not the database
Teams ask normal questions and get answers tied back to real records, reports and source data.
Let AI prepare small actions safely
Draft replies, update fields or create tasks only after role checks, confirmations and audit logging.
Find the next process to fix
Usage data reveals repeated exceptions, manual workarounds and automations worth building next.
04
A retail platform that fixed peak-campaign stability.
Orders piled up, catalogue queries slowed down, and the team could not tell where failures started. The delivery rebuilt the data layer, added hot cache and replaced manual log checks with proper monitoring.
+500%order processing capacity
8xdatabase throughput
10 minmean time to locate issues
0subsequent peak outages
05
Senior engineers deliver it; client teams own it.
Dimension
Hong Kong Aitech
Traditional project
Starting point
Workflow first; AI only where action is possible
Spec first and long delivery cycles
Data control
Client cloud, clear permissions and audit logs
Depends on documentation and project handover
After launch
Measure usage, remove friction and keep improving
Maintenance tickets and change requests
06
A practical first release in 4-6 weeks.
01Map the workflow
Trace who starts the work, where data comes from and where it gets stuck.
02Ship a working slice
Build a small but real version with actual data shape and roles.
03Add controls
Add auth, approvals, audit logs, monitoring and backups before launch.
04Launch and measure
Watch usage, fix friction and decide the next workflow with evidence.
07
Send us the workflow that keeps causing workarounds.
A short email is enough: current systems, where time is lost, and what outcome would make the project worthwhile.
Company
Hong Kong Aitech Limited
Office
UNIT 1022A, BEVERLEY COMMERCIAL CENTRE, 87-105 CHATHAM ROAD SOUTH, TSIM SHA TSUI, HONG KONG
Business Registration No.75522619